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---
layout: page
title: Comparison Operations
---
# Integer Comparision # {#icmp}
Predicates for use with `icmp` instruction are listed below. All
of these are integer constants defined in the `llvm.core` module.
##`ICMP_EQ`
Equality
##`ICMP_NE`
Inequality
##`ICMP_UGT`
Unsigned greater than
##`ICMP_UGE`
Unsigned greater than or equal
##`ICMP_ULT`
Unsigned less than
##`ICMP_ULE`
Unsigned less than or equal
##`ICMP_SGT`
Signed greater than
##`ICMP_SGE`
Signed greater than or equal
##`ICMP_SLT`
Signed less than
##`ICMP_SLE`
Signed less than or equal
# Float Comparision # {#fcmp}
Predicates for use with `fcmp` instruction are listed below. All
of these are integer constants defined in the `llvm.core` module.
##`FCMP_FALSE`
Always false
##`FCMP_OEQ`
True if ordered and equal
##`FCMP_OGT`
True if ordered and greater than
##`FCMP_OGE`
True if ordered and greater than or equal
##`FCMP_OLT`
True if ordered and less than
##`FCMP_OLE`
True if ordered and less than or equal
##`FCMP_ONE`
True if ordered and operands are unequal
##`FCMP_ORD`
True if ordered (no NaNs)
##`FCMP_UNO`
True if unordered: `isnan(X) | isnan(Y)`
##`FCMP_UEQ`
True if unordered or equal
##`FCMP_UGT`
True if unordered or greater than
##`FCMP_UGE`
True if unordered, greater than or equal
##`FCMP_ULT`
True if unordered, or less than
##`FCMP_ULE`
True if unordered, less than or equal
##`FCMP_UNE`
True if unordered or not equal
##`FCMP_TRUE`
Always true

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+--------------------------------+
| layout: page |
+--------------------------------+
| title: Comparison Operations |
+--------------------------------+
Integer Comparision # {#icmp}
=============================
Predicates for use with ``icmp`` instruction are listed below. All of
these are integer constants defined in the ``llvm.core`` module.
``ICMP_EQ``
-----------
Equality
``ICMP_NE``
-----------
Inequality
``ICMP_UGT``
------------
Unsigned greater than
``ICMP_UGE``
------------
Unsigned greater than or equal
``ICMP_ULT``
------------
Unsigned less than
``ICMP_ULE``
------------
Unsigned less than or equal
``ICMP_SGT``
------------
Signed greater than
``ICMP_SGE``
------------
Signed greater than or equal
``ICMP_SLT``
------------
Signed less than
``ICMP_SLE``
------------
Signed less than or equal
Float Comparision # {#fcmp}
===========================
Predicates for use with ``fcmp`` instruction are listed below. All of
these are integer constants defined in the ``llvm.core`` module.
``FCMP_FALSE``
--------------
Always false
``FCMP_OEQ``
------------
True if ordered and equal
``FCMP_OGT``
------------
True if ordered and greater than
``FCMP_OGE``
------------
True if ordered and greater than or equal
``FCMP_OLT``
------------
True if ordered and less than
``FCMP_OLE``
------------
True if ordered and less than or equal
``FCMP_ONE``
------------
True if ordered and operands are unequal
``FCMP_ORD``
------------
True if ordered (no NaNs)
``FCMP_UNO``
------------
True if unordered: ``isnan(X) | isnan(Y)``
``FCMP_UEQ``
------------
True if unordered or equal
``FCMP_UGT``
------------
True if unordered or greater than
``FCMP_UGE``
------------
True if unordered, greater than or equal
``FCMP_ULT``
------------
True if unordered, or less than
``FCMP_ULE``
------------
True if unordered, less than or equal
``FCMP_UNE``
------------
True if unordered or not equal
``FCMP_TRUE``
-------------
Always true

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---
layout: page
title: Examples and LLVM Tutorials
---
* This will become a table of contents (this text will be scraped).
{:toc}
# Examples
## A Simple Function
Let's create a (LLVM) module containing a single function, corresponding
to the `C` function:
{% highlight c %}
int sum(int a, int b)
{
return a + b;
}
{% endhighlight %}
Here's how it looks like:
{% highlight python %}
#!/usr/bin/env python
# Import the llvm-py modules.
from llvm import *
from llvm.core import *
# Create an (empty) module.
my_module = Module.new('my_module')
# All the types involved here are "int"s. This type is represented
# by an object of the llvm.core.Type class:
ty_int = Type.int() # by default 32 bits
# We need to represent the class of functions that accept two integers
# and return an integer. This is represented by an object of the
# function type (llvm.core.FunctionType):
ty_func = Type.function(ty_int, [ty_int, ty_int])
# Now we need a function named 'sum' of this type. Functions are not
# free-standing (in llvm-py); it needs to be contained in a module.
f_sum = my_module.add_function(ty_func, "sum")
# Let's name the function arguments as 'a' and 'b'.
f_sum.args[0].name = "a"
f_sum.args[1].name = "b"
# Our function needs a "basic block" -- a set of instructions that
# end with a terminator (like return, branch etc.). By convention
# the first block is called "entry".
bb = f_sum.append_basic_block("entry")
# Let's add instructions into the block. For this, we need an
# instruction builder:
builder = Builder.new(bb)
# OK, now for the instructions themselves. We'll create an add
# instruction that returns the sum as a value, which we'll use
# a ret instruction to return.
tmp = builder.add(f_sum.args[0], f_sum.args[1], "tmp")
builder.ret(tmp)
# We've completed the definition now! Let's see the LLVM assembly
# language representation of what we've created:
print my_module
{% endhighlight %}
Here is the output:
{% highlight llvm %}
; ModuleID = 'my_module'
define i32 @sum(i32 %a, i32 %b) {
entry:
%tmp = add i32 %a, %b ; <i32> [#uses=1]
ret i32 %tmp
}
{% endhighlight %}
## Adding JIT Compilation
Let's compile this function in-memory and run it.
{% highlight python %}
#!/usr/bin/env python
# Import the llvm-py modules.
from llvm import *
from llvm.core import *
from llvm.ee import * # new import: ee = Execution Engine
# Create a module, as in the previous example.
my_module = Module.new('my_module')
ty_int = Type.int() # by default 32 bits
ty_func = Type.function(ty_int, [ty_int, ty_int])
f_sum = my_module.add_function(ty_func, "sum")
f_sum.args[0].name = "a"
f_sum.args[1].name = "b"
bb = f_sum.append_basic_block("entry")
builder = Builder.new(bb)
tmp = builder.add(f_sum.args[0], f_sum.args[1], "tmp")
builder.ret(tmp)
# Create an execution engine object. This will create a JIT compiler
# on platforms that support it, or an interpreter otherwise.
ee = ExecutionEngine.new(my_module)
# The arguments needs to be passed as "GenericValue" objects.
arg1 = GenericValue.int(ty_int, 100)
arg2 = GenericValue.int(ty_int, 42)
# Now let's compile and run!
retval = ee.run_function(f_sum, [arg1, arg2])
# The return value is also GenericValue. Let's print it.
print "returned", retval.as_int()
{% endhighlight %}
And here's the output:
returned 142
* * *
# LLVM Tutorials
## Simple JIT Tutorials
The following JIT tutorials were contributed by Sebastien Binet.
1. [A First Function](examples/JITTutorial1.html)
2. [A More Complicated Function](examples/JITTutorial2.html)
## Kaleidoscope ## {#kaleidoscope}
Implementing a Language with LLVM
The LLVM [Kaleidoscope](http://www.llvm.org/docs/tutorial/) tutorial
has been ported to llvm-py by Max Shawabkeh.
1. [Tutorial Introduction and the Lexer](kaleidoscope/PythonLangImpl1.html)
2. [Implementing a Parser and AST](kaleidoscope/PythonLangImpl2.html)
3. [Implementing Code Generation to LLVM IR](kaleidoscope/PythonLangImpl3.html)
4. [Adding JIT and Optimizer Support](kaleidoscope/PythonLangImpl4.html)
5. [Extending the language: control flow](kaleidoscope/PythonLangImpl5.html)
6. [Extending the language: user-defined operators](kaleidoscope/PythonLangImpl6.html)
7. [Extending the language: mutable variables / SSA construction](kaleidoscope/PythonLangImpl7.html)
8. [Conclusion and other useful LLVM tidbits](kaleidoscope/PythonLangImpl8.html)

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---
layout: page
title: JIT Tutorial 1
---
{% highlight python %}
#!/usr/bin/env python
from llvm.core import *
# create a module
module = Module.new ("tut1")
# create a function type taking 3 32-bit integers, return a 32-bit integer
ty_int = Type.int (32)
func_type = Type.function (ty_int, (ty_int,)*3)
# create a function of that type
mul_add = Function.new (module, func_type, "mul_add")
mul_add.calling_convention = CC_C
x = mul_add.args[0]; x.name = "x"
y = mul_add.args[1]; y.name = "y"
z = mul_add.args[2]; z.name = "z"
# implement the function
# new block
blk = mul_add.append_basic_block ("entry")
# IR builder
bldr = Builder.new (blk)
tmp_1 = bldr.mul (x, y, "tmp_1")
tmp_2 = bldr.add (tmp_1, z, "tmp_2")
bldr.ret (tmp_2)
print(module)
{% endhighlight %}

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---
layout: page
title: JIT Tutorial 2
---
{% highlight python %}
#!/usr/bin/env python
from llvm.core import *
# create a module
module = Module.new ("tut2")
# create a function type taking 2 integers, return a 32-bit integer
ty_int = Type.int (32)
func_type = Type.function (ty_int, (ty_int, ty_int))
# create a function of that type
gcd = Function.new (module, func_type, "gcd")
# name function args
x = gcd.args[0]; x.name = "x"
y = gcd.args[1]; y.name = "y"
# implement the function
# blocks...
entry = gcd.append_basic_block ("entry")
ret = gcd.append_basic_block ("return")
cond_false = gcd.append_basic_block ("cond_false")
cond_true = gcd.append_basic_block ("cond_true")
cond_false_2 = gcd.append_basic_block ("cond_false_2")
# create a llvm::IRBuilder
bldr = Builder.new (entry)
x_eq_y = bldr.icmp (IPRED_EQ, x, y, "tmp")
bldr.cbranch (x_eq_y, ret, cond_false)
bldr.position_at_end (ret)
bldr.ret(x)
bldr.position_at_end (cond_false)
x_lt_y = bldr.icmp (IPRED_ULT, x, y, "tmp")
bldr.cbranch (x_lt_y, cond_true, cond_false_2)
bldr.position_at_end (cond_true)
y_sub_x = bldr.sub (y, x, "tmp")
recur_1 = bldr.call (gcd, (x, y_sub_x,), "tmp")
bldr.ret (recur_1)
bldr.position_at_end (cond_false_2)
x_sub_y = bldr.sub (x, y, "x_sub_y")
recur_2 = bldr.call (gcd, (x_sub_y, y,), "tmp")
bldr.ret (recur_2)
print(module)
{% endhighlight %}

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---
layout: page
title: Functions
---
Functions are represented by [llvm.core.Function][] objects.
They are contained within modules, and can be created either with the method
`module_obj.add_function` or the static constructor `Function.new`.
References to functions already present in a module can be retrieved via
`module.get_function_named` or by the static constructor method
`Function.get`. All functions in a module can be enumerated by iterating
over `module_obj.functions`.
{% highlight python %}
# create a type, representing functions that take an integer and return
# a floating point value.
ft = Type.function( Type.float(), [ Type.int() ] )
# create a function of this type
f1 = module_obj.add_function(ft, "func1")
# or equivalently, like this:
f2 = Function.new(module_obj, ft, "func2")
# get a reference to an existing function
f3 = module_obj.get_function_named("func3")
# or like this:
f4 = Function.get(module_obj, "func4")
# list all function names in a module
for f in module_obj.functions:
print f.name
{% endhighlight %}
# Intrinsic
References to intrinsic functions can be got via the static constructor
`intrinsic`. This returns a `Function` object, calling which is
equivalent to invoking the intrinsic. The `intrinsic` method has to be
called with a module object, an intrinsic ID (which is a numeric
constant) and a list of the types of arguments (which LLVM uses to
resolve overloaded intrinsic functions).
{% highlight python %}
# get a reference to the llvm.bswap intrinsic
bswap = Function.intrinsic(mod, INTR_BSWAP, [Type.int()])
# call it
builder.call(bswap, [value])
{% endhighlight %}
Here, the constant `INTR_BSWAP`, available from `llvm.core`, represents the
LLVM intrinsic [llvm.bswap](http://www.llvm.org/docs/LangRef.html#int_bswap).
The `[Type.int()]` selects the version of `llvm.bswap` that has a single 32-bit
integer argument. The list of intrinsic IDs defined as integer constants
in `llvm.core`. These are:
{% include intrinsics.csv %}
There are also target-specific intrinsics (which correspond to that
target's CPU instructions) available, but are omitted here for brevity.
Full list can be seen from
[_intrinsic_ids.py](https://github.com/numba/llvm-py/blob/master/llvm/_intrinsic_ids.py).
See the [LLVM Language Reference](http://www.llvm.org/docs/LangRef.html)
for more information on the intrinsics, and the
[test](https://github.com/numba/llvm-py/blob/master/test/intrinsic.py)
directory in the source distribution for more examples. The intrinsic ID
can be retrieved from a function object with the read-only property
`intrinsic_id`.
> **Auto-generation of Intrinsic IDs**
>
>
> A script (tool/intrgen.py in source tree) generates the intrinsic IDs
> automatically. This is necessary when compiling llvm-py with a different
> version of LLVM.
# Calling Convention # {#callconv}
The function's calling convention can be set using the
`calling_convention` property. The following (integer) constants defined
in `llvm.core` can be used as values:
Value | Equivalent LLVM Assembly Keyword |
------|----------------------------------|
`CC_C` | `ccc` |
`CC_FASTCALL` | `fastcc` |
`CC_COLDCALL` | `coldcc` |
`CC_X86_STDCALL` | `x86_stdcallcc` |
`CC_X86_FASTCALL` | `x86_fastcallcc` |
See the [LLVM docs](http://www.llvm.org/docs/LangRef.html#callingconv) for
more information on each. Backend-specific numbered conventions can be
directly passed as integers.
An arbitrary string identifying which garbage collector to use can be
set or got with the property `collector`.
The value objects corresponding to the arguments of a function can be
got using the read-only property `args`. These can be iterated over, and
also be indexed via integers. An example:
{% highlight python %}
# list all argument names and types
for arg in fn.args:
print arg.name, "of type", arg.type
# change the name of the first argument
fn.args[0].name = "objptr"
{% endhighlight %}
Basic blocks (see later) are contained within functions. When newly
created, a function has no basic blocks. They have to be added
explicitly, using the `append_basic_block` method, which adds a new,
empty basic block as the last one in the function. The first basic block
of the function can be retrieved using the `get_entry_basic_block`
method. The existing basic blocks can be enumerated by iterating over
using the read-only property `basic_blocks`. The number of basic blocks
can be got via `basic_block_count` method. Note that
`get_entry_basic_block` is slightly faster than `basic_blocks[0]` and so
is `basic_block_count`, over `len(f.basic_blocks)`.
{% highlight python %}
# add a basic block
b1 = fn.append_basic_block("entry")
# get the first one
b2 = fn.get_entry_basic_block()
b2 = fn.basic_mdblocks[0] # slower than previous method
# print names of all basic blocks
for b in fn.basic_blocks:
print b.name
# get number of basic blocks
n = fn.basic_block_count
n = len(fn.basic_blocks) # slower than previous method
{% endhighlight %}
Functions can be deleted using the method `delete`. This deletes them
from their containing module. All references to the function object
should be dropped after `delete` has been called.
Functions can be verified with the `verify` method. Note that this may
not work properly (aborts on errors).
# Function Attributes # {#fnattr}
Function attributes, as documented
[here](http://www.llvm.org/docs/LangRef.html#fnattrs), can be
set on functions using the methods `add_attribute` and
`remove_attribute`. The following values may be used to refer to the
LLVM attributes:
Value | Equivalent LLVM Assembly Keyword |
------|----------------------------------|
`ATTR_ALWAYS_INLINE`|`alwaysinline` |
`ATTR_INLINE_HINT`|`inlinehint` |
`ATTR_NO_INLINE`|`noinline` |
`ATTR_OPTIMIZE_FOR_SIZE`|`optsize` |
`ATTR_NO_RETURN`|`noreturn` |
`ATTR_NO_UNWIND`|`nounwind` |
`ATTR_READ_NONE`|`readnone` |
`ATTR_READONLY`|`readonly` |
`ATTR_STACK_PROTECT`|`ssp` |
`ATTR_STACK_PROTECT_REQ`|`sspreq` |
`ATTR_NO_REDZONE`|`noredzone` |
`ATTR_NO_IMPLICIT_FLOAT`|`noimplicitfloat` |
`ATTR_NAKED`|`naked` |
Here is how attributes can be set and removed:
{% highlight python %}
# create a function
ti = Type.int(32)
tf = Type.function(ti, [ti, ti])
m = Module.new('mod')
f = m.add_function(tf, 'sum')
print f
# declare i32 @sum(i32, i32)
# add a couple of attributes
f.add_attribute(ATTR_NO_UNWIND)
f.add_attribute(ATTR_READONLY)
print f
# declare i32 @sum(i32, i32) nounwind readonly
{% endhighlight %}
**Related Links**
[llvm.core.Function][],
[llvm.core.Argument][]
[llvm.core.Function]: llvm.core.Function.html
[llvm.core.Argument]: llvm.core.Argument.html

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---
layout: page
title: "Kaleidoscope: Chapter 1"
---
# Tutorial Introduction and the Lexer
Written by [Chris Lattner](mailto:sabre@nondot.org)
and [Max Shawabkeh](http://max99x.com)
**Chapter 1**
* This will become a table of contents (this text will be scraped).
{:toc}
[**Chapter 2: Implementing a Parser and AST**](PythonLangImpl2.html)
# Introduction
Welcome to the "Implementing a language with LLVM" tutorial. This tutorial
runs through the implementation of a simple language, showing how fun and
easy it can be. This tutorial will get you up and started as well as help to
build a framework you can extend to other languages. The code in this
tutorial can also be used as a playground to hack on other LLVM specific
things.
It is useful to point out ahead of time that this tutorial is really about
teaching compiler techniques and LLVM specifically, *not* about teaching
modern and sane software engineering principles. In practice, this means that
we'll take a number of shortcuts to simplify the exposition. If you dig in and
use the code as a basis for future projects, fixing its deficiencies shouldn't
be hard.
We've tried to put this tutorial together in a way that makes chapters easy
to skip over if you are already familiar with or are uninterested in the
various pieces. The structure of the tutorial is:
* **[Chapter 1](#language): Introduction to the Kaleidoscope language,
and the definition of its Lexer** -- This shows where we are going
and the basic functionality that we want it to do. In order to make this
tutorial maximally understandable and hackable, we choose to implement
everything in Python instead of using lexer and parser generators. LLVM
obviously works just fine with such tools, feel free to use one if you prefer.
* **[Chapter 2](PythonLangImpl2.html): Implementing a Parser and AST** --
With the lexer in place, we can talk about parsing techniques and
basic AST construction. This tutorial describes recursive descent parsing and
operator precedence parsing. Nothing in Chapters 1 or 2 is LLVM-specific,
the code doesn't even import the LLVM modules at this point. :)
* **[Chapter 3](PythonLangImpl3.html): Code generation to LLVM IR** -- With
the AST ready, we can show off how easy generation of LLVM IR really is.
* **[Chapter 4](PythonLangImpl4.html): Adding JIT and Optimizer support** --
Because a lot of people are interested in using LLVM as a JIT,
we'll dive right into it and show you the 3 lines it takes to add JIT support.
LLVM is also useful in many other ways, but this is one simple and "sexy" way
to shows off its power. :)
* **[Chapter 5](PythonLangImpl5.html): Extending the Language: Control Flow**
-- With the language up and running, we show how to extend it
with control flow operations (if/then/else and a 'for' loop). This gives us a
chance to talk about simple SSA construction and control flow.
* **[Chapter 6](PythonLangImpl6.html): Extending the Language:
User-defined Operators** -- This is a silly but fun chapter that talks about
extending the language to let the user program define their own arbitrary
unary and binary operators (with assignable precedence!). This lets us build
a significant piece of the "language" as library routines.
* **[Chapter 7](PythonLangImpl7.html): Extending the Language:
Mutable Variables** -- This chapter talks about adding user-defined local
variables along with an assignment operator. The interesting part about this
is how easy and trivial it is to construct SSA form in LLVM: no, LLVM does
*not* require your front-end to construct SSA form!
* **[Chapter 8](PythonLangImpl8.html): Conclusion and other
useful LLVM tidbits** -- This chapter wraps up the series by talking about
potential ways to extend the language, but also includes a bunch of pointers to
info about "special topics" like adding garbage collection support, exceptions,
debugging, support for "spaghetti stacks", and a bunch of other tips and
tricks.
By the end of the tutorial, we'll have written a bit less than 540 lines of
non-comment, non-blank, lines of code. With this small amount of code, we'll
have built up a very reasonable compiler for a non-trivial language including
a hand-written lexer, parser, AST, as well as code generation support with a JIT
compiler. While other systems may have interesting "hello world" tutorials,
I think the breadth of this tutorial is a great testament to the strengths of
LLVM and why you should consider it if you're interested in language or compiler
design.
A note about this tutorial: we expect you to extend the language and play
with it on your own. Take the code and go crazy hacking away at it, compilers
don't need to be scary creatures - it can be a lot of fun to play with
languages!
* * *
# The Basic Language # {#language}
This tutorial will be illustrated with a toy language that we'll call
"[Kaleidoscope](http://en.wikipedia.org/wiki/Kaleidoscope)" (derived
from "meaning beautiful, form, and view").
Kaleidoscope is a procedural language that allows you to define functions, use
conditionals, math, etc. Over the course of the tutorial, we'll extend
Kaleidoscope to support the if/then/else construct, a for loop, user defined
operators, JIT compilation with a simple command line interface, etc.
Because we want to keep things simple, the only datatype in Kaleidoscope is a
64-bit floating point type. As such, all values are implicitly double precision
and the language doesn't require type declarations. This gives the language a
very nice and simple syntax. For example, the following simple example computes
[Fibonacci numbers](http://en.wikipedia.org/wiki/Fibonacci_number):
{% highlight python %}
# Compute the x'th fibonacci number.
def fib(x)
if x &lt; 3 then
1
else
fib(x-1)+fib(x-2)
# This expression will compute the 40th number.
fib(40)
{% endhighlight %}
We also allow Kaleidoscope to call into standard library functions (the LLVM
JIT makes this completely trivial). This means that you can use the 'extern'
keyword to define a function before you use it (this is also useful for mutually
recursive functions). For example:
{% highlight python %}
extern sin(arg);
extern cos(arg);
extern atan2(arg1 arg2);
atan2(sin(0.4), cos(42))
{% endhighlight %}
A more interesting example is included in Chapter 6 where we write a little
Kaleidoscope application that [displays](PythonLangImpl6.html#example)
a Mandelbrot Set</a> at various levels of magnification.
Lets dive into the implementation of this language!
* * *
# The Lexer # {#lexer}
When it comes to implementing a language, the first thing needed is
the ability to process a text file and recognize what it says.
The traditional way to do this is to use a
[lexer](http://en.wikipedia.org/wiki/Lexical_analysis)" (aka 'scanner')
to break the input up into "tokens". Each token returned by the lexer includes
a token type and potentially some metadata (e.g. the numeric value of a number).
First, we define the possibilities:
{% highlight python %}
# The lexer yields one of these types for each token.
class EOFToken(object):
pass
class DefToken(object):
pass
class ExternToken(object):
pass
class IdentifierToken(object):
def __init__(self, name): self.name = name
class NumberToken(object):
def __init__(self, value): self.value = value
class CharacterToken(object):
def __init__(self, char): self.char = char
def __eq__(self, other):
return isinstance(other, CharacterToken) and self.char == other.char
def __ne__(self, other): return not self == other
{% endhighlight %}
Each token yielded by our lexer will be of one of the above types. For simple
tokens that are always the same, like the "def" keyword, the lexer will yield
`DefToken()`>. Identifiers, numbers and characters, on the other
hand, have extra data, so when the lexer encounteres the number 123.45, it will
emit it as `NumberToken(123.45)`. An identifier `foo` will be
emitted as `IdentifierToken('foo')`. And finally, an unknown character
like '+' will be returned as `CharacterToken('+')`. You may notice that
we overload the equality and inequality operators for the characters; this will
later simplify character comparisons in the parser code.
The actual implementation of the lexer is a single function called `Tokenize`,
which takes a string and
[yields](http://docs.python.org/reference/simple_stmts.html#the-yield-statement)
tokens. For simplicity, we will use
[regular expressions](http://docs.python.org/library/re.html)
to parse out the tokens. This is terribly inefficient, but
perfectly sufficient for our needs.
First, we define the regular expressions for our tokens. Numbers and strings
of digits, optionally followed by a period and another string of digits.
Identifiers (and keywords) are alphanumeric string starting with a letter and
comments are anything between a hash (`#`) and the end of the line.
{% highlight python %}
import re
...
# Regular expressions that tokens and comments of our language.
REGEX_NUMBER = re.compile('[0-9]+(?:\.[0-9]+)?')
REGEX_IDENTIFIER = re.compile('[a-zA-Z][a-zA-Z0-9]*')
REGEX_COMMENT = re.compile('#.*')
{% endhighlight %}
Next, let's start defining the `Tokenize` function itself. The first
thing we need to do is set up a loop that scans the string, while ignoring
whitespace between tokens:
{% highlight python %}
def Tokenize(string):
while string:
# Skip whitespace.
if string[0].isspace():
string = string[1:]
continue
...
{% endhighlight %}
Next we want to find out what the next token is. For this we run the regexes
we defined above on the remainder of the string. To simplify the rest of the
code, we run all three regexes each time. As mentioned above, inefficiencies are
ignored for the purpose of this tutorial:
{% highlight python %}
# Run regexes.
comment_match = REGEX_COMMENT.match(string)
number_match = REGEX_NUMBER.match(string)
identifier_match = REGEX_IDENTIFIER.match(string)
{% endhighlight %}
Now se check if any of the regexes matched. For comments, we simply
ignore the captured match:
{% highlight python %}
# Check if any of the regexes matched and yield the appropriate result.
if comment_match:
comment = comment_match.group(0)
string = string[len(comment):]
{% endhighlight python %}
For numbers, we yield the captured match, converted to a float and tagged
with the appropriate token type:
{% highlight python %}
elif number_match:
number = number_match.group(0)
yield NumberToken(float(number))
string = string[len(number):]
{% endhighlight %}
The identifier case is a little more complex. We have to check for keywords
to decide whether we have captured an identifier or a keyword:
{% highlight python %}
elif identifier_match:
identifier = identifier_match.group(0)
# Check if we matched a keyword.
if identifier == 'def':
yield DefToken()
elif identifier == 'extern':
yield ExternToken()
else:
yield IdentifierToken(identifier)
string = string[len(identifier):]
{% endhighlight %}
Finally, if we haven't recognized a comment, a number of an identifier, we
yield the current character as an "unknown character" token. This is used, for
example, for operators like `+` or `*`:
{% highlight python %}
else:
# Yield the unknown character.
yield CharacterToken(string[0])
string = string[1:]
{% endhighlight %}
Once we're done with the loop, we return a final end-of-file token:
{% highlight python %}
yield EOFToken()
{% endhighlight %}
With this, we have the complete lexer for the basic Kaleidoscope language
(the [full code listing](PythonLangImpl2.html#code) for the Lexer is
available in the [next chapter](PythonLangImpl2.html) of the
tutorial). Next we'll [build a simple parser that
uses this to build an Abstract Syntax Tree](PythonLangImpl2.html).
When we have that, we'll
include a driver so that you can use the lexer and parser together.
* * *
**[Next: Implementing a Parser and AST](PythonLangImpl2.html)**

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---
layout: page
title: "Kaleidoscope: Chapter 2"
---
# Implementing a Parser and AST
Written by [Chris Lattner](mailto:sabre@nondot.org)
and [Max Shawabkeh](http://max99x.com)
**Chapter 2**
* This will become a table of contents (this text will be scraped).
{:toc}
**[Chapter 3: Code generation to LLVM IR](PythonLangImpl3.html)**
# Introduction # {#intro}
Welcome to Chapter 2 of the
[Implementing a language with LLVM](http://www.llvm.org/docs/tutorial/index.html)
tutorial.
This chapter shows you how to use the lexer, built in
[Chapter 1](PythonLangImpl1.html), to build a full
[parser](http://en.wikipedia.org/wiki/Parsing) for
our Kaleidoscope language. Once we have a parser, we'll define and build an
[Abstract Syntax Tree](http://en.wikipedia.org/wiki/Abstract_syntax_tree)
(AST).
The parser we will build uses a combination of [Recursive Descent
Parsing](http://en.wikipedia.org/wiki/Recursive_descent_parser) and
[Operator-Precedence Parsing](http://en.wikipedia.org/wiki/Operator-precedence_parser)
to parse the Kaleidoscope language (the latter for
binary expressions and the former for everything else). Before we get to
parsing though, lets talk about the output of the parser: the Abstract Syntax
Tree.
* * *
# The Abstract Syntax Tree (AST) # {#ast}
The AST for a program captures its behavior in such a way that it is easy for
later stages of the compiler (e.g. code generation) to interpret. We basically
want one object for each construct in the language, and the AST should closely
model the language. In Kaleidoscope, we have expressions, a prototype, and a
function object. We'll start with expressions first:
{% highlight python %}
# Base class for all expression nodes.
class ExpressionNode(object):
pass
# Expression class for numeric literals like "1.0".
class NumberExpressionNode(ExpressionNode):
def __init__(self, value):
self.value = value
{% endhighlight %}
The code above shows the definition of the base ExpressionNode class and one
subclass which we use for numeric literals. The important thing to note about
this code is that the NumberExpressionNode class captures the numeric value of
the literal as an instance variable. This allows later phases of the compiler to
know what the stored numeric value is.
Right now we only create the AST, so there are no useful methods on them.
It would be very easy to add a virtual method to pretty print the code, for
example. Here are the other expression AST node definitions that we'll use
in the basic form of the Kaleidoscope language:
{% highlight python %}
# Expression class for referencing a variable, like "a".
class VariableExpressionNode(ExpressionNode):
def __init__(self, name):
self.name = name
# Expression class for a binary operator.
class BinaryOperatorExpressionNode(ExpressionNode):
def __init__(self, operator, left, right):
self.operator = operator
self.left = left
self.right = right
# Expression class for function calls.
class CallExpressionNode(ExpressionNode):
def __init__(self, callee, args):
self.callee = callee
self.args = args
{% endhighlight %}
This is all (intentionally) rather straight-forward: variables capture the
variable name, binary operators capture their opcode (e.g. '+'), and calls
capture a function name as well as a list of any argument expressions. One thing
that is nice about our AST is that it captures the language features without
talking about the syntax of the language. Note that there is no discussion about
precedence of binary operators, lexical structure, etc.
For our basic language, these are all of the expression nodes we'll define.
Because it doesn't have conditional control flow, it isn't Turing-complete;
we'll fix that in a later installment. The two things we need next are a way
to talk about the interface to a function, and a way to talk about functions
themselves:
{% highlight python %}
# This class represents the "prototype" for a function, which captures its name,
# and its argument names (thus implicitly the number of arguments the function
# takes).
class PrototypeNode(object):
def __init__(self, name, args):
self.name = name
self.args = args
# This class represents a function definition itself.
class FunctionNode(object):
def __init__(self, prototype, body):
self.prototype = prototype
self.body = body
{% endhighlight %}
In Kaleidoscope, functions are typed with just a count of their arguments.
Since all values are double precision floating point, the type of each argument
doesn't need to be stored anywhere. In a more aggressive and realistic
language, the `ExpressionNode` class would probably have a type field.
With this scaffolding, we can now talk about parsing expressions and function
bodies in Kaleidoscope.
* * *
# Parser Basics # {#parserbasics}
Now that we have an AST to build, we need to define the parser code to build
it. The idea here is that we want to parse something like `x + y` (which
is returned as three tokens by the lexer) into an AST that could be generated
with calls like this:
{% highlight python %}
x = VariableExpressionNode('x')
y = VariableExpressionNode('y')
result = BinaryOperatorExpressionNode('+', x, y)
{% endhighlight %}
In order to do this, we'll start by defining a lightweight `Parser`
class with some basic helper routines:
{% highlight python %}
class Parser(object):
def __init__(self, tokens, binop_precedence):
self.tokens = tokens
self.binop_precedence = binop_precedence
self.Next()
# Provide a simple token buffer. Parser.current is the current token the
# parser is looking at. Parser.Next() reads another token from the lexer and
# updates Parser.current with its results.
def Next(self):
self.current = self.tokens.next()
{% endhighlight %}
This implements a simple token buffer around the lexer. This allows
us to look one token ahead at what the lexer is returning. Every function in
our parser will assume that `self.current` is the current token that
needs to be parsed. Note that the first token is read as soon as the parser is
instantiated. Let us ignore the `binop_precedence` parameter for now. It
will be explained when we start [parsing binary operators](#parserbinops).
With these basic helper functions, we can implement the first
piece of our grammar: numeric literals.
* * *
# Basic Expression Parsing # {#parserprimexprs}
We start with numeric literals, because they are the simplest to process.
For each production in our grammar, we'll define a function which parses that
production. For numeric literals, we have:
{% highlight python %}
# numberexpr ::= number
def ParseNumberExpr(self):
result = NumberExpressionNode(self.current.value)
self.Next() # consume the number.
return result
{% endhighlight %}
This method is very simple: it expects to be called when the current token
is a `NumberToken`. It takes the current number value, creates a
`NumberExpressionNode`, advances to the next token, and finally returns.
There are some interesting aspects to this. The most important one is that
this routine eats all of the tokens that correspond to the production and
returns the lexer buffer with the next token (which is not part of the grammar
production) ready to go. This is a fairly standard way to go for recursive
descent parsers. For a better example, the parenthesis operator is defined like
this:
{% highlight python %}
# parenexpr ::= '(' expression ')'
def ParseParenExpr(self):
self.Next() # eat '('.
contents = self.ParseExpression()
if self.current != CharacterToken(')'):
raise RuntimeError('Expected ")".')
self.Next() # eat ')'.
return contents
{% endhighlight %}
This function illustrates an interesting aspect of the parser. The function
uses recursion by calling `ParseExpression` (we will soon see that
`ParseExpression` can call `ParseParenExpr`). This is powerful
because it allows us to handle recursive grammars, and keeps each production
very simple. Note that parentheses do not cause construction of AST nodes
themselves. While we could do it this way, the most important role of
parentheses are to guide the parser and provide grouping. Once the parser
constructs the AST, parentheses are not needed.
The next simple production is for handling variable references and function
calls:
{% highlight python %}
# identifierexpr ::= identifier | identifier '(' expression* ')'
def ParseIdentifierExpr(self):
identifier_name = self.current.name
self.Next() # eat identifier.
if self.current != CharacterToken('('): # Simple variable reference.
return VariableExpressionNode(identifier_name);
# Call.
self.Next() # eat '('.
args = []
if self.current != CharacterToken(')'):
while True:
args.append(self.ParseExpression())
if self.current == CharacterToken(')'):
break
elif self.current != CharacterToken(','):
raise RuntimeError('Expected ")" or "," in argument list.')
self.Next()
self.Next() # eat ')'.
return CallExpressionNode(identifier_name, args)
{% endhighlight %}
This routine follows the same style as the other routines. It expects to be
called if the current token is an `IdentifierToken`. It also has
recursion and error handling. One interesting aspect of this is that it uses
*look-ahead* to determine if the current identifier is a stand alone
variable reference or if it is a function call expression. It handles this by
checking to see if the token after the identifier is a '(' token, constructing
either a `VariableExpressionNode` or `CallExpressionNode` as
appropriate.
Now that we have all of our simple expression-parsing logic in place, we can
define a helper function to wrap it together into one entry point. We call this
class of expressions "primary" expressions, for reasons that will become more
clear [later in the tutorial](PythonLangImpl6.html#unary). In order
to parse an arbitrary primary expression, we need to determine what sort of
expression it is:
{% highlight python %}
# primary ::= identifierexpr | numberexpr | parenexpr
def ParsePrimary(self):
if isinstance(self.current, IdentifierToken):
return self.ParseIdentifierExpr()
elif isinstance(self.current, NumberToken):
return self.ParseNumberExpr();
elif self.current == CharacterToken('('):
return self.ParseParenExpr()
else:
raise RuntimeError('Unknown token when expecting an expression.')
{% endhighlight %}
Now that you see the definition of this function, it is more obvious why we
can assume the state of `Parser.current` in the various functions. This
uses look-ahead to determine which sort of expression is being inspected, and
then parses it with a function call.
Now that basic expressions are handled, we need to handle binary expressions.
They are a bit more complex.
* * *
# Binary Expression Parsing # {#parserbinops}
Binary expressions are significantly harder to parse because they are often
ambiguous. For example, when given the string `x+y*z`, the parser can choose
to parse it as either `(x+y)*z` or `x+(y*z)`. With common definitions from
mathematics, we expect the later parse, because `*` (multiplication) has
higher *precedence* than `+` (addition).
There are many ways to handle this, but an elegant and efficient way is
to use [Operator-Precedence Parsing](http://en.wikipedia.org/wiki/Operator-precedence_parser).
This parsing technique uses the precedence of binary operators to
guide recursion. To start with, we need a table of precedences. Remember the
`binop_precedence` parameter we passed to the `Parser`
constructor? Now is the time to use it:
{% highlight python %}
def main():
# Install standard binary operators.
# 1 is lowest possible precedence. 40 is the highest.
operator_precedence = {
'<': 10,
'+': 20,
'-': 20,
'*': 40
}
# Run the main `interpreter loop`.
while True:
...
parser = Parser(Tokenize(raw), operator_precedence)
{% endhighlight %}
For the basic form of Kaleidoscope, we will only support 4 binary operators
(this can obviously be extended by you, our brave and intrepid reader). Having a
dictionary makes it easy to add new operators and makes it clear that the
algorithm doesn't depend on the specific operators involved, but it would be
easy enough to eliminate the map and hardcode the comparisons.
We also define a helper function to get the precedence of the current token,
or -1 if the token is not a binary operator:
{% highlight python %}
# Gets the precedence of the current token, or -1 if the token is not a binary
# operator.
def GetCurrentTokenPrecedence(self):
if isinstance(self.current, CharacterToken):
return self.binop_precedence.get(self.current.char, -1)
else:
return -1
{% endhighlight %}
With the helper above defined, we can now start parsing binary expressions.
The basic idea of operator precedence parsing is to break down an expression
with potentially ambiguous binary operators into pieces. Consider, for example,
the expression `a+b+(c+d)*e*f+g`. Operator precedence parsing considers this
as a stream of primary expressions separated by binary operators. As such,
it will first parse the leading primary expression `a`, then it will see the
pairs `[+, b] [+, (c+d)] [*, e] [*, f] and [+, g]`. Note that because parentheses
are primary expressions, the binary expression parser doesn't need to worry
about nested subexpressions like (c+d) at all.
To start, an expression is a primary expression potentially followed by a
sequence of `[binop,primaryexpr]` pairs:
{% highlight python %}
# expression ::= primary binoprhs
def ParseExpression(self):
left = self.ParsePrimary()
return self.ParseBinOpRHS(left, 0)
{% endhighlight %}
`ParseBinOpRHS` is the function that parses the sequence of pairs for
us. It takes a precedence and a pointer to an expression for the part that has
been parsed so far. Note that `x` is a perfectly valid expression: As such,
`binoprhs` is allowed to be empty, in which case it returns the expression that
is passed into it. In our example above, the code passes the expression for `a`
into `ParseBinOpRHS` and the current token is `+`.
The precedence value passed into `ParseBinOpRHS` indicates the *
minimal operator precedence* that the function is allowed to eat. For
example, if the current pair stream is `[+, x]` and `ParseBinOpRHS` is
passed in a precedence of 40, it will not consume any tokens (because the
precedence of '+' is only 20). With this in mind, `ParseBinOpRHS` starts
with:
{% highlight python %}
# binoprhs ::= (operator primary)*
def ParseBinOpRHS(self, left, left_precedence):
# If this is a binary operator, find its precedence.
while True:
precedence = self.GetCurrentTokenPrecedence()
# If this is a binary operator that binds at least as tightly as the
# current one, consume it; otherwise we are done.
if precedence < left_precedence:
return left
{% endhighlight %}
This code gets the precedence of the current token and checks to see if if is
too low. Because we defined invalid tokens to have a precedence of -1, this
check implicitly knows that the pair-stream ends when the token stream runs out
of binary operators. If this check succeeds, we know that the token is a binary
operator and that it will be included in this expression:
{% highlight python %}
binary_operator = self.current.char
self.Next() # eat the operator.
# Parse the primary expression after the binary operator.
right = self.ParsePrimary()
{% endhighlight %}
As such, this code eats (and remembers) the binary operator and then parses
the primary expression that follows. This builds up the whole pair, the first of
which is `[+, b]` for the running example.
Now that we parsed the left-hand side of an expression and one pair of the
RHS sequence, we have to decide which way the expression associates. In
particular, we could have `(a+b) binop unparsed` or `a + (b binop unparsed)`.
To determine this, we look ahead at `binop` to determine its precedence and
compare it to BinOp's precedence (which is '+' in this case):
{% highlight python %}
# If binary_operator binds less tightly with right than the operator after
# right, let the pending operator take right as its left.
next_precedence = self.GetCurrentTokenPrecedence()
if precedence < next_precedence:
{% endhighlight %}
If the precedence of the binop to the right of `RHS` is lower or equal to the
precedence of our current operator, then we know that the parentheses associate
as `(a+b) binop ...`. In our example, the current operator is `+` and the next
operator is `+`, we know that they have the same precedence. In this case we'll
create the AST node for `a+b`, and then continue parsing:
{% highlight python %}
if precedence < next_precedence:
... if body omitted ...
# Merge left/right.
left = BinaryOperatorExpressionNode(binary_operator, left, right);
{% endhighlight %}
In our example above, this will turn `a+b+` into `(a+b)` and execute the next
iteration of the loop, with `+` as the current token. The code above will eat,
remember, and parse `(c+d)` as the primary expression, which makes the
current pair equal to `[+, (c+d)]`. It will then evaluate the 'if' conditional
above with `*` as the binop to the right of the primary. In this case, the
precedence of `*` is higher than the precedence of `+` so the if condition will
be entered.
The critical question left here is `how can the if condition parse the right
hand side in full`? In particular, to build the AST correctly for our example,
it needs to get all of ` ( c + d ) * e * f` as the RHS expression variable. The code to
do this is surprisingly simple (code from the above two blocks duplicated for
context):
{% highlight python %}
# If binary_operator binds less tightly with right than the operator after
# right, let the pending operator take right as its left.
next_precedence = self.GetCurrentTokenPrecedence()
if precedence < next_precedence:
right = self.ParseBinOpRHS(right, precedence + 1)
# Merge left/right.
left = BinaryOperatorExpressionNode(binary_operator, left, right)
{% endhighlight %}
At this point, we know that the binary operator to the RHS of our primary
has higher precedence than the binop we are currently parsing. As such, we know
that any sequence of pairs whose operators are all higher precedence than `+`
should be parsed together and returned as `RHS`. To do this, we recursively
invoke the `ParseBinOpRHS` function specifying `precedence + 1` as the
minimum precedence required for it to continue. In our example above, this
will cause it to return the AST node for `(c+d)*e*f` as RHS, which is then set
as the RHS of the '+' expression.
Finally, on the next iteration of the while loop, the `+g` piece is parsed
and added to the AST. With this little bit of code (11 non-trivial lines), we
correctly handle fully general binary expression parsing in a very elegant way.
This was a whirlwind tour of this code, and it is somewhat subtle. I recommend
running through it with a few tough examples to see how it works.
This wraps up handling of expressions. At this point, we can point the
parser at an arbitrary token stream and build an expression from it, stopping
at the first token that is not part of the expression. Next up we need to
handle function definitions, etc.
* * *
# Parsing the Rest # {#parsertop}
The next thing missing is handling of function prototypes. In Kaleidoscope,
these are used both for 'extern' function declarations as well as function body
definitions. The code to do this is straight-forward and not very interesting
(once you've survived expressions):
{% highlight python %}
# prototype ::= id '(' id* ')'
def ParsePrototype(self):
if not isinstance(self.current, IdentifierToken):
raise RuntimeError('Expected function name in prototype.')
function_name = self.current.name
self.Next() # eat function name.
if self.current != CharacterToken('('):
raise RuntimeError('Expected "(" in prototype.')
self.Next() # eat '('.
arg_names = []
while isinstance(self.current, IdentifierToken):
arg_names.append(self.current.name)
self.Next()
if self.current != CharacterToken(')'):
raise RuntimeError('Expected ")" in prototype.')
# Success.
self.Next() # eat ')'.
return PrototypeNode(function_name, arg_names)
{% endhighlight %}
Given this, a function definition is very simple, just a prototype plus
an expression to implement the body:
{% highlight python %}
# definition ::= 'def' prototype expression
def ParseDefinition(self):
self.Next() # eat def.
proto = self.ParsePrototype()
body = self.ParseExpression()
return FunctionNode(proto, body)
{% endhighlight %}
In addition, we support 'extern' to declare functions like 'sin' and 'cos' as
well as to support forward declaration of user functions. These 'extern's are
just prototypes with no body:
{% highlight python %}
# external ::= 'extern' prototype
def ParseExtern(self):
self.Next() # eat extern.
return self.ParsePrototype()
{% endhighlight %}
Finally, we'll also let the user type in arbitrary top-level expressions and
evaluate them on the fly. We will handle this by defining anonymous nullary
(zero argument) functions for them:
{% highlight python %}
# toplevelexpr ::= expression
def ParseTopLevelExpr(self):
proto = PrototypeNode('', [])
return FunctionNode(proto, self.ParseExpression())
{% endhighlight %}
Now that we have all the pieces, let's build a little driver that will let us
actually *execute* this code we've built!
* * *
# The Driver # {#driver}
The driver for this simply invokes all of the parsing pieces with a top-level
dispatch loop. There isn't much interesting here, so I'll just include the
top-level loop. See [below](#code) for full code.
{% highlight python %}
# Run the main "interpreter loop".
while True:
print 'ready>',
try:
raw = raw_input()
except KeyboardInterrupt:
return
parser = Parser(Tokenize(raw), operator_precedence)
while True:
# top ::= definition | external | expression | EOF
if isinstance(parser.current, EOFToken):
break
if isinstance(parser.current, DefToken):
parser.HandleDefinition()
elif isinstance(parser.current, ExternToken):
parser.HandleExtern()
else:
parser.HandleTopLevelExpression()
{% endhighlight %}
Here we create a new `Parser` for each line read, and try to parse out
all the expressions, declarations and definitions in the line. We also allow the
user to quit using Ctrl+C.
* * *
# Conclusions # {#conclusions}
With just under 330 lines of commented code (200 lines of non-comment,
non-blank code), we fully defined our minimal language, including a lexer,
parser, and AST builder. With this done, the executable will validate
Kaleidoscope code and tell us if it is grammatically invalid. For
example, here is a sample interaction:
{% highlight python %}
$ python kaleidoscope.py
ready> def foo(x y) x+foo(y, 4.0)
Parsed a function definition.
ready> def foo(x y) x+y y
Parsed a function definition.
Parsed a top-level expression.
ready> def foo(x y) x+y )
Parsed a function definition.
Error: Unknown token when expecting an expression.
ready> extern sin(a);
Parsed an extern.
ready> ^C
$
{% endhighlight %}
There is a lot of room for extension here. You can define new AST nodes,
extend the language in many ways, etc. In the
[next installment](PythonLangImpl3.html), we will describe how to
generate LLVM Intermediate Representation (IR) from the AST.
* * *
# Full Code Listing # {#code}
Here is the complete code listing for this and the previous chapter.
Note that it is fully self-contained: you don't need LLVM or any external
libraries at all for this.
{% highlight python %}
#!/usr/bin/env python
import re
################################################################################
## Lexer
################################################################################
# The lexer yields one of these types for each token.
class EOFToken(object):
pass
class DefToken(object):
pass
class ExternToken(object):
pass
class IdentifierToken(object):
def __init__(self, name): self.name = name
class NumberToken(object):
def __init__(self, value): self.value = value
class CharacterToken(object):
def __init__(self, char): self.char = char
def __eq__(self, other):
return isinstance(other, CharacterToken) and self.char == other.char
def __ne__(self, other): return not self == other
# Regular expressions that tokens and comments of our language.
REGEX_NUMBER = re.compile('[0-9]+(?:\.[0-9]+)?')
REGEX_IDENTIFIER = re.compile('[a-zA-Z][a-zA-Z0-9]*')
REGEX_COMMENT = re.compile('#.*')
def Tokenize(string):
while string:
# Skip whitespace.
if string[0].isspace():
string = string[1:]
continue
# Run regexes.
comment_match = REGEX_COMMENT.match(string)
number_match = REGEX_NUMBER.match(string)
identifier_match = REGEX_IDENTIFIER.match(string)
# Check if any of the regexes matched and yield the appropriate result.
if comment_match:
comment = comment_match.group(0)
string = string[len(comment):]
elif number_match:
number = number_match.group(0)
yield NumberToken(float(number))
string = string[len(number):]
elif identifier_match:
identifier = identifier_match.group(0)
# Check if we matched a keyword.
if identifier == 'def':
yield DefToken()
elif identifier == 'extern':
yield ExternToken()
else:
yield IdentifierToken(identifier)
string = string[len(identifier):]
else:
# Yield the ASCII value of the unknown character.
yield CharacterToken(string[0])
string = string[1:]
yield EOFToken()
################################################################################
## Abstract Syntax Tree (aka Parse Tree)
################################################################################
# Base class for all expression nodes.
class ExpressionNode(object):
pass
# Expression class for numeric literals like "1.0".
class NumberExpressionNode(ExpressionNode):
def __init__(self, value):
self.value = value
# Expression class for referencing a variable, like "a".
class VariableExpressionNode(ExpressionNode):
def __init__(self, name):
self.name = name
# Expression class for a binary operator.
class BinaryOperatorExpressionNode(ExpressionNode):
def __init__(self, operator, left, right):
self.operator = operator
self.left = left
self.right = right
# Expression class for function calls.
class CallExpressionNode(ExpressionNode):
def __init__(self, callee, args):
self.callee = callee
self.args = args
# This class represents the "prototype" for a function, which captures its name,
# and its argument names (thus implicitly the number of arguments the function
# takes).
class PrototypeNode(object):
def __init__(self, name, args):
self.name = name
self.args = args
# This class represents a function definition itself.
class FunctionNode(object):
def __init__(self, prototype, body):
self.prototype = prototype
self.body = body
################################################################################
## Parser
################################################################################
class Parser(object):
def __init__(self, tokens, binop_precedence):
self.tokens = tokens
self.binop_precedence = binop_precedence
self.Next()
# Provide a simple token buffer. Parser.current is the current token the
# parser is looking at. Parser.Next() reads another token from the lexer and
# updates Parser.current with its results.
def Next(self):
self.current = self.tokens.next()
# Gets the precedence of the current token, or -1 if the token is not a binary
# operator.
def GetCurrentTokenPrecedence(self):
if isinstance(self.current, CharacterToken):
return self.binop_precedence.get(self.current.char, -1)
else:
return -1
# identifierexpr ::= identifier | identifier '(' expression* ')'
def ParseIdentifierExpr(self):
identifier_name = self.current.name
self.Next() # eat identifier.
if self.current != CharacterToken('('): # Simple variable reference.
return VariableExpressionNode(identifier_name)
# Call.
self.Next() # eat '('.
args = []
if self.current != CharacterToken(')'):
while True:
args.append(self.ParseExpression())
if self.current == CharacterToken(')'):
break
elif self.current != CharacterToken(','):
raise RuntimeError('Expected ")" or "," in argument list.')
self.Next()
self.Next() # eat ')'.
return CallExpressionNode(identifier_name, args)
# numberexpr ::= number
def ParseNumberExpr(self):
result = NumberExpressionNode(self.current.value)
self.Next() # consume the number.
return result
# parenexpr ::= '(' expression ')'
def ParseParenExpr(self):
self.Next() # eat '('.
contents = self.ParseExpression()
if self.current != CharacterToken(')'):
raise RuntimeError('Expected ")".')
self.Next() # eat ')'.
return contents
# primary ::= identifierexpr | numberexpr | parenexpr
def ParsePrimary(self):
if isinstance(self.current, IdentifierToken):
return self.ParseIdentifierExpr()
elif isinstance(self.current, NumberToken):
return self.ParseNumberExpr()
elif self.current == CharacterToken('('):
return self.ParseParenExpr()
else:
raise RuntimeError('Unknown token when expecting an expression.')
# binoprhs ::= (operator primary)*
def ParseBinOpRHS(self, left, left_precedence):
# If this is a binary operator, find its precedence.
while True:
precedence = self.GetCurrentTokenPrecedence()
# If this is a binary operator that binds at least as tightly as the
# current one, consume it; otherwise we are done.
if precedence < left_precedence:
return left
binary_operator = self.current.char
self.Next() # eat the operator.
# Parse the primary expression after the binary operator.
right = self.ParsePrimary()
# If binary_operator binds less tightly with right than the operator after
# right, let the pending operator take right as its left.
next_precedence = self.GetCurrentTokenPrecedence()
if precedence < next_precedence:
right = self.ParseBinOpRHS(right, precedence + 1)
# Merge left/right.
left = BinaryOperatorExpressionNode(binary_operator, left, right)
# expression ::= primary binoprhs
def ParseExpression(self):
left = self.ParsePrimary()
return self.ParseBinOpRHS(left, 0)
# prototype ::= id '(' id* ')'
def ParsePrototype(self):
if not isinstance(self.current, IdentifierToken):
raise RuntimeError('Expected function name in prototype.')
function_name = self.current.name
self.Next() # eat function name.
if self.current != CharacterToken('('):
raise RuntimeError('Expected "(" in prototype.')
self.Next() # eat '('.
arg_names = []
while isinstance(self.current, IdentifierToken):
arg_names.append(self.current.name)
self.Next()
if self.current != CharacterToken(')'):
raise RuntimeError('Expected ")" in prototype.')
# Success.
self.Next() # eat ')'.
return PrototypeNode(function_name, arg_names)
# definition ::= 'def' prototype expression
def ParseDefinition(self):
self.Next() # eat def.
proto = self.ParsePrototype()
body = self.ParseExpression()
return FunctionNode(proto, body)
# toplevelexpr ::= expression
def ParseTopLevelExpr(self):
proto = PrototypeNode('', [])
return FunctionNode(proto, self.ParseExpression())
# external ::= 'extern' prototype
def ParseExtern(self):
self.Next() # eat extern.
return self.ParsePrototype()
# Top-Level parsing
def HandleDefinition(self):
self.Handle(self.ParseDefinition, 'Parsed a function definition.')
def HandleExtern(self):
self.Handle(self.ParseExtern, 'Parsed an extern.')
def HandleTopLevelExpression(self):
self.Handle(self.ParseTopLevelExpr, 'Parsed a top-level expression.')
def Handle(self, function, message):
try:
function()
print message
except Exception, e:
print 'Error:', e
try:
self.Next() # Skip for error recovery.
except:
pass
################################################################################
## Main driver code.
################################################################################
def main():
# Install standard binary operators.
# 1 is lowest possible precedence. 40 is the highest.
operator_precedence = {
'<': 10,
'+': 20,
'-': 20,
'*': 40
}
# Run the main "interpreter loop".
while True:
print 'ready>',
try:
raw = raw_input()
except KeyboardInterrupt:
return
parser = Parser(Tokenize(raw), operator_precedence)
while True:
# top ::= definition | external | expression | EOF
if isinstance(parser.current, EOFToken):
break
if isinstance(parser.current, DefToken):
parser.HandleDefinition()
elif isinstance(parser.current, ExternToken):
parser.HandleExtern()
else:
parser.HandleTopLevelExpression()
if __name__ == '__main__':
main()
{% endhighlight %}
* * *
**[Next: Implementing Code Generation to LLVM IR](PythonLangImpl3.html)**

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---
layout: page
title: "Kaleidoscope: Chapter 4"
---
# Adding JIT and Optimizer Support
Written by [Chris Lattner](mailto:sabre@nondot.org)
and [Max Shawabkeh](http://max99x.com)
**Chapter 4**
* This will become a table of contents (this text will be scraped).
{:toc}
**[Chapter 5: Extending the Language: Control Flow](PythonLangImpl5.html)**
# Introduction # {#intro}
Welcome to Chapter 4 of the
[Implementing a language with LLVM](http://www.llvm.org/docs/tutorial/index.html)
tutorial. Chapters 1-3 described the implementation of a simple
language and added support for generating LLVM IR. This chapter describes
two new techniques: adding optimizer support to your language, and adding JIT
compiler support. These additions will demonstrate how to get nice, efficient
code for the Kaleidoscope language.
* * *
# Trivial Constant Folding # {#trivialconstfold}
Our demonstration for Chapter 3 is elegant and easy to extend. Unfortunately,
it does not produce wonderful code. The LLVM Builder, however, does give us
obvious optimizations when compiling simple code:
{% highlight bash %}
ready> def test(x) 1+2+x
Read function definition:
define double @test(double %x) {
entry:
%addtmp = fadd double 3.000000e+00, %x
ret double %addtmp
}
{% endhighlight %}
This code is not a literal transcription of the AST built by parsing the
input. That would be:
{% highlight bash %}
ready> def test(x) 1+2+x
Read function definition:
define double @test(double %x) {
entry:
%addtmp = fadd double 2.000000e+00, 1.000000e+00
%addtmp1 = fadd double %addtmp, %x
ret double %addtmp1
}
{% endhighlight %}
Constant folding, as seen above, in particular, is a very common and very
important optimization: so much so that many language implementors implement
constant folding support in their AST representation.
With LLVM, you don't need this support in the AST. Since all calls to build
LLVM IR go through the LLVM IR builder, the builder itself checked to see if
there was a constant folding opportunity when you call it. If so, it just does
the constant fold and return the constant instead of creating an instruction.
Well, that was easy :). In practice, we recommend always using
`llvm.core.Builder` when generating code like this. It has no
"syntactic overhead" for its use (you don't have to uglify your compiler with
constant checks everywhere) and it can dramatically reduce the amount of
LLVM IR that is generated in some cases (particular for languages with a macro
preprocessor or that use a lot of constants).
On the other hand, the `Builder` is limited by the fact that it does
all of its analysis inline with the code as it is built. If you take a slightly
more complex example:
{% highlight bash %}
ready> def test(x) (1+2+x)*(x+(1+2))
Read a function definition:
define double @test(double %x) {
entry:
%addtmp = fadd double 3.000000e+00, %x ; <double> [#uses=1]
%addtmp1 = fadd double %x, 3.000000e+00 ; <double> [#uses=1]
%multmp = fmul double %addtmp, %addtmp1 ; <double> [#uses=1]
ret double %multmp
}
{% endhighlight %}
In this case, the LHS and RHS of the multiplication are the same value. We'd
really like to see this generate"`tmp = x+3; result = tmp*tmp;` instead
of computing `x+3` twice.
Unfortunately, no amount of local analysis will be able to detect and correct
this. This requires two transformations: reassociation of expressions (to
make the add's lexically identical) and Common Subexpression Elimination (CSE)
to delete the redundant add instruction. Fortunately, LLVM provides a broad
range of optimizations that you can use, in the form of "passes".
* * *
# LLVM Optimization Passes # {#optimizerpasses}
LLVM provides many optimization passes, which do many different sorts of
things and have different tradeoffs. Unlike other systems, LLVM doesn't hold
to the mistaken notion that one set of optimizations is right for all languages
and for all situations. LLVM allows a compiler implementor to make complete
decisions about what optimizations to use, in which order, and in what
situation.
As a concrete example, LLVM supports both "whole module" passes, which look
across as large of body of code as they can (often a whole file, but if run
at link time, this can be a substantial portion of the whole program). It also
supports and includes "per-function" passes which just operate on a single
function at a time, without looking at other functions. For more information
on passes and how they are run, see the
[How to Write a Pass](http://www.llvm.org/docs/WritingAnLLVMPass.html)
document and the
[List of LLVM Passes](http://www.llvm.org/docs/Passes.html).
For Kaleidoscope, we are currently generating functions on the fly, one at
a time, as the user types them in. We aren't shooting for the ultimate
optimization experience in this setting, but we also want to catch the easy and
quick stuff where possible. As such, we will choose to run a few per-function
optimizations as the user types the function in. If we wanted to make a "static
Kaleidoscope compiler", we would use exactly the code we have now, except that
we would defer running the optimizer until the entire file has been parsed.
In order to get per-function optimizations going, we need to set up a
[FunctionPassManager](http://www.llvm.org/docs/WritingAnLLVMPass.html#passmanager)
to hold and organize the LLVM optimizations that we want
to run. Once we have that, we can add a set of optimizations to run. The code
looks like this:
{% highlight python %}
# The function optimization passes manager.
g_llvm_pass_manager = FunctionPassManager.new(g_llvm_module)
# The LLVM execution engine.
g_llvm_executor = ExecutionEngine.new(g_llvm_module)
...
def main():
# Set up the optimizer pipeline. Start with registering info about how the
# target lays out data structures.
g_llvm_pass_manager.add(g_llvm_executor.target_data)
# Do simple "peephole" optimizations and bit-twiddling optzns.
g_llvm_pass_manager.add(PASS_INSTRUCTION_COMBINING)
# Reassociate expressions.
g_llvm_pass_manager.add(PASS_REASSOCIATE)
# Eliminate Common SubExpressions.
g_llvm_pass_manager.add(PASS_GVN)
# Simplify the control flow graph (deleting unreachable blocks, etc).
g_llvm_pass_manager.add(PASS_CFG_SIMPLIFICATION)
g_llvm_pass_manager.initialize()
{% endhighlight %}
This code defines a `FunctionPassManager`,
`g_llvm_pass_manager`. Once it is set up, we use a series of "add" calls
to add a bunch of LLVM passes. The first pass is basically boilerplate, it adds
a pass so that later optimizations know how the data structures in the program
are laid out. (The "`g_llvm_executor`" variable is related to the JIT,
which we will get to in the next section.) In this case, we choose to add 4
optimization passes. The passes we chose here are a pretty standard set of
"cleanup" optimizations that are useful for a wide variety of code. I won't
delve into what they do but, believe me, they are a good starting place :).
Once the pass manager is set up, we need to make use of it. We do this by
running it after our newly created function is constructed (in
`FunctionNode.CodeGen`), but before it is returned to the client:
{% highlight python %}
return_value = self.body.CodeGen()
g_llvm_builder.ret(return_value)
# Validate the generated code, checking for consistency.
function.verify()
# Optimize the function.
g_llvm_pass_manager.run(function)
{% endhighlight %}
As you can see, this is pretty straightforward. The
`FunctionPassManager` optimizes and updates the LLVM Function in place,
improving (hopefully) its body. With this in place, we can try our test above
again:
{% highlight bash %}
ready> def test(x) (1+2+x)*(x+(1+2))
Read a function definition:
define double @test(double %x) {
entry:
%addtmp = fadd double %x, 3.000000e+00 ; <double> [#uses=2]
%multmp = fmul double %addtmp, %addtmp ; <double> [#uses=1]
ret double %multmp
}
{% endhighlight %}
As expected, we now get our nicely optimized code, saving a floating point
add instruction from every execution of this function.
LLVM provides a wide variety of optimizations that can be used in certain
circumstances. Some
[documentation about the various passes](http://www.llvm.org/docs/Passes.html)
is available, but it isn't very complete. Another good source of
ideas can come from looking at the passes that `llvm-gcc` or
`llvm-ld` run to get started. The `opt` tool allows you to
experiment with passes from the command line, so you can see if they do
anything.
Now that we have reasonable code coming out of our front-end, lets talk about
executing it!
* * *
# Adding a JIT Compiler # {#jit}
Code that is available in LLVM IR can have a wide variety of tools
applied to it. For example, you can run optimizations on it (as we did above),
you can dump it out in textual or binary forms, you can compile the code to an
assembly file (.s) for some target, or you can JIT compile it. The nice thing
about the LLVM IR representation is that it is the "common currency" between
many different parts of the compiler.
In this section, we'll add JIT compiler support to our interpreter. The
basic idea that we want for Kaleidoscope is to have the user enter function
bodies as they do now, but immediately evaluate the top-level expressions they
type in. For example, if they type in "1 + 2", we should evaluate and print
out 3. If they define a function, they should be able to call it from the
command line.
In order to do this, we first declare and initialize the JIT. This is done
by adding and initializing a global variable:
{% highlight python %}
# The LLVM execution engine.
g_llvm_executor = ExecutionEngine.new(g_llvm_module)
{% endhighlight %}
This creates an abstract "Execution Engine" which can be either a JIT
compiler or the LLVM interpreter. LLVM will automatically pick a JIT compiler
for you if one is available for your platform, otherwise it will fall back to
the interpreter.
Once the `ExecutionEngine` is created, the JIT is ready to be used.
We can use the `run_function` method of the execution engine to execute
a compiled function and get its return value. In our case, this means that we
can change the code that parses a top-level expression to look like this:
{% highlight python %}
def HandleTopLevelExpression(self):
try:
function = self.ParseTopLevelExpr().CodeGen()
result = g_llvm_executor.run_function(function, [])
print 'Evaluated to:', result.as_real(Type.double())
except Exception, e:
print 'Error:', e
try:
self.Next() # Skip for error recovery.
except:
pass
{% endhighlight %}
Recall that we compile top-level expressions into a self-contained LLVM
function that takes no arguments and returns the computed double.
With just these two changes, lets see how Kaleidoscope works now!
{% highlight python %}
ready> 4+5
Read a top level expression:
define double @0() {
entry:
ret double 9.000000e+00
}
Evaluated to: 9.0
{% endhighlight %}
Well this looks like it is basically working. The dump of the function
shows the "no argument function that always returns double" that we synthesize
for each top-level expression that is typed in. This demonstrates very basic
functionality, but can we do more?
{% highlight python %}
ready> def testfunc(x y) x + y*2
Read a function definition:
define double @testfunc(double %x, double %y) {
entry:
%multmp = fmul double %y, 2.000000e+00 ; <double> [#uses=1]
%addtmp = fadd double %multmp, %x ; <double> [#uses=1]
ret double %addtmp
}
ready> testfunc(4, 10)
Read a top level expression:
define double @0() {
entry:
%calltmp = call double @testfunc(double 4.000000e+00, double 1.000000e+01) ; <double> [#uses=1]
ret double %calltmp
}
*Evaluated to: 24.0*
{% endhighlight %}
This illustrates that we can now call user code, but there is something a bit
subtle going on here. Note that we only invoke the JIT on the anonymous
functions that *call testfunc*, but we never invoked it
on *testfunc* itself. What actually happened here is that the JIT
scanned for all non-JIT'd functions transitively called from the anonymous
function and compiled all of them before returning from `run_function()`.
The JIT provides a number of other more advanced interfaces for things like
freeing allocated machine code, rejit'ing functions to update them, etc.
However, even with this simple code, we get some surprisingly powerful
capabilities - check this out (I removed the dump of the anonymous functions,
you should get the idea by now :) :
{% highlight bash %}
ready> extern sin(x)
Read an extern:
declare double @sin(double)
ready> extern cos(x)
Read an extern:
declare double @cos(double)
ready> sin(1.0)
*Evaluated to: 0.841470984808*
ready> def foo(x) sin(x)*sin(x) + cos(x)*cos(x)
Read a function definition:
define double @foo(double %x) {
entry:
%calltmp = call double @sin(double %x) ; <double> [#uses=1]
%calltmp1 = call double @sin(double %x) ; <double> [#uses=1]
%multmp = fmul double %calltmp, %calltmp1 ; <double> [#uses=1]
%calltmp2 = call double @cos(double %x) ; <double> [#uses=1]
%calltmp3 = call double @cos(double %x) ; <double> [#uses=1]
%multmp4 = fmul double %calltmp2, %calltmp3 ; <double> [#uses=1]
%addtmp = fadd double %multmp, %multmp4 ; <double> [#uses=1]
ret double %addtmp
}
ready> foo(4.0)
*Evaluated to: 1.000000*
{% endhighlight %}
Whoa, how does the JIT know about sin and cos? The answer is surprisingly
simple: in this example, the JIT started execution of a function and got to a
function call. It realized that the function was not yet JIT compiled and
invoked the standard set of routines to resolve the function. In this case,
there is no body defined for the function, so the JIT ended up calling
`dlsym("sin")` on the Python process that is hosting our Kaleidoscope
prompt. Since `sin` is defined within the JIT's address space, it
simply patches up calls in the module to call the libm version of `sin`
directly.
One interesting application of this is that we can now extend the language
by writing arbitrary C++ code to implement operations. For example, we can
create a C file with the following simple function:
{% highlight c %}
#include <stdio.h>
double putchard(double x) {
putchar((char)x);
return 0;
}
{% endhighlight %}
We can then compile this into a shared library with GCC:
{% highlight bash %}
gcc -shared -fPIC -o putchard.so putchard.c
{% endhighlight %}
Now we can load this library into the Python process using
`llvm.core.load_library_permanently` and access it from Kaleidoscope to
produce simple output to the console:
{% highlight python %}
>>> import llvm.core
>>> llvm.core.load_library_permanently('/home/max/llvm-py-tutorial/putchard.so')
>>> import kaleidoscope
>>> kaleidoscope.main()
ready> extern putchard(x)
Read an extern:
declare double @putchard(double)
ready> putchard(65) + putchard(66) + putchard(67) + putchard(10)
*ABC*
Evaluated to: 0.0
{% endhighlight %}
Similar code could be used to implement file I/O, console input, and many
other capabilities in Kaleidoscope.
This completes the JIT and optimizer chapter of the Kaleidoscope tutorial. At
this point, we can compile a non-Turing-complete programming language, optimize
and JIT compile it in a user-driven way. Next up we'll look into
[extending the language with control flow constructs](PythonLangImpl5.html),
tackling some interesting LLVM IR issues along the way.
* * *
# Full Code Listing # {#code}
Here is the complete code listing for our running example, enhanced with the
LLVM JIT and optimizer:
{% highlight python %}
#!/usr/bin/env python
import re
from llvm.core import Module, Constant, Type, Function, Builder, FCMP_ULT
from llvm.ee import ExecutionEngine, TargetData
from llvm.passes import FunctionPassManager
from llvm.passes import (PASS_INSTRUCTION_COMBINING,
PASS_REASSOCIATE,
PASS_GVN,
PASS_CFG_SIMPLIFICATION)
################################################################################
## Globals
################################################################################
# The LLVM module, which holds all the IR code.
g_llvm_module = Module.new('my cool jit')
# The LLVM instruction builder. Created whenever a new function is entered.
g_llvm_builder = None
# A dictionary that keeps track of which values are defined in the current scope
# and what their LLVM representation is.
g_named_values = {}
# The function optimization passes manager.
g_llvm_pass_manager = FunctionPassManager.new(g_llvm_module)
# The LLVM execution engine.
g_llvm_executor = ExecutionEngine.new(g_llvm_module)
################################################################################
## Lexer
################################################################################
# The lexer yields one of these types for each token.
class EOFToken(object):
pass
class DefToken(object):
pass
class ExternToken(object):
pass
class IdentifierToken(object):
def __init__(self, name): self.name = name
class NumberToken(object):
def __init__(self, value): self.value = value
class CharacterToken(object):
def __init__(self, char): self.char = char
def __eq__(self, other):
return isinstance(other, CharacterToken) and self.char == other.char
def __ne__(self, other): return not self == other
# Regular expressions that tokens and comments of our language.
REGEX_NUMBER = re.compile('[0-9]+(?:\.[0-9]+)?')
REGEX_IDENTIFIER = re.compile('[a-zA-Z][a-zA-Z0-9]*')
REGEX_COMMENT = re.compile('#.*')
def Tokenize(string):
while string:
# Skip whitespace.
if string[0].isspace():
string = string[1:]
continue
# Run regexes.
comment_match = REGEX_COMMENT.match(string)
number_match = REGEX_NUMBER.match(string)
identifier_match = REGEX_IDENTIFIER.match(string)
# Check if any of the regexes matched and yield the appropriate result.
if comment_match:
comment = comment_match.group(0)
string = string[len(comment):]
elif number_match:
number = number_match.group(0)
yield NumberToken(float(number))
string = string[len(number):]
elif identifier_match:
identifier = identifier_match.group(0)
# Check if we matched a keyword.
if identifier == 'def':
yield DefToken()
elif identifier == 'extern':
yield ExternToken()
else:
yield IdentifierToken(identifier)
string = string[len(identifier):]
else:
# Yield the ASCII value of the unknown character.
yield CharacterToken(string[0])
string = string[1:]
yield EOFToken()
################################################################################
## Abstract Syntax Tree (aka Parse Tree)
################################################################################
# Base class for all expression nodes.
class ExpressionNode(object):
pass
# Expression class for numeric literals like "1.0".
class NumberExpressionNode(ExpressionNode):
def __init__(self, value):
self.value = value
def CodeGen(self):
return Constant.real(Type.double(), self.value)
# Expression class for referencing a variable, like "a".
class VariableExpressionNode(ExpressionNode):
def __init__(self, name):
self.name = name
def CodeGen(self):
if self.name in g_named_values:
return g_named_values[self.name]
else:
raise RuntimeError('Unknown variable name: ' + self.name)
# Expression class for a binary operator.
class BinaryOperatorExpressionNode(ExpressionNode):
def __init__(self, operator, left, right):
self.operator = operator
self.left = left
self.right = right
def CodeGen(self):
left = self.left.CodeGen()
right = self.right.CodeGen()
if self.operator == '+':
return g_llvm_builder.fadd(left, right, 'addtmp')
elif self.operator == '-':
return g_llvm_builder.fsub(left, right, 'subtmp')
elif self.operator == '*':
return g_llvm_builder.fmul(left, right, 'multmp')
elif self.operator == '<':
result = g_llvm_builder.fcmp(FCMP_ULT, left, right, 'cmptmp')
# Convert bool 0 or 1 to double 0.0 or 1.0.
return g_llvm_builder.uitofp(result, Type.double(), 'booltmp')
else:
raise RuntimeError('Unknown binary operator.')
# Expression class for function calls.
class CallExpressionNode(ExpressionNode):
def __init__(self, callee, args):
self.callee = callee
self.args = args
def CodeGen(self):
# Look up the name in the global module table.
callee = g_llvm_module.get_function_named(self.callee)
# Check for argument mismatch error.
if len(callee.args) != len(self.args):
raise RuntimeError('Incorrect number of arguments passed.')
arg_values = [i.CodeGen() for i in self.args]
return g_llvm_builder.call(callee, arg_values, 'calltmp')
# This class represents the "prototype" for a function, which captures its name,
# and its argument names (thus implicitly the number of arguments the function
# takes).
class PrototypeNode(object):
def __init__(self, name, args):
self.name = name
self.args = args
def CodeGen(self):
# Make the function type, eg. double(double,double).
funct_type = Type.function(
Type.double(), [Type.double()] * len(self.args), False)
function = Function.new(g_llvm_module, funct_type, self.name)
# If the name conflicted, there was already something with the same name.
# If it has a body, don't allow redefinition or reextern.
if function.name != self.name:
function.delete()
function = g_llvm_module.get_function_named(self.name)
# If the function already has a body, reject this.
if not function.is_declaration:
raise RuntimeError('Redefinition of function.')
# If F took a different number of args, reject.
if len(callee.args) != len(self.args):
raise RuntimeError('Redeclaration of a function with different number '
'of args.')
# Set names for all arguments and add them to the variables symbol table.
for arg, arg_name in zip(function.args, self.args):
arg.name = arg_name
# Add arguments to variable symbol table.
g_named_values[arg_name] = arg
return function
# This class represents a function definition itself.
class FunctionNode(object):
def __init__(self, prototype, body):
self.prototype = prototype
self.body = body
def CodeGen(self):
# Clear scope.
g_named_values.clear()
# Create a function object.
function = self.prototype.CodeGen()
# Create a new basic block to start insertion into.
block = function.append_basic_block('entry')
global g_llvm_builder
g_llvm_builder = Builder.new(block)
# Finish off the function.
try:
return_value = self.body.CodeGen()
g_llvm_builder.ret(return_value)
# Validate the generated code, checking for consistency.
function.verify()
# Optimize the function.
g_llvm_pass_manager.run(function)
except:
function.delete()
raise
return function
################################################################################
## Parser
################################################################################
class Parser(object):
def __init__(self, tokens, binop_precedence):
self.tokens = tokens
self.binop_precedence = binop_precedence
self.Next()
# Provide a simple token buffer. Parser.current is the current token the
# parser is looking at. Parser.Next() reads another token from the lexer and
# updates Parser.current with its results.
def Next(self):
self.current = self.tokens.next()
# Gets the precedence of the current token, or -1 if the token is not a binary
# operator.
def GetCurrentTokenPrecedence(self):
if isinstance(self.current, CharacterToken):
return self.binop_precedence.get(self.current.char, -1)
else:
return -1
# identifierexpr ::= identifier | identifier '(' expression* ')'
def ParseIdentifierExpr(self):
identifier_name = self.current.name
self.Next() # eat identifier.
if self.current != CharacterToken('('): # Simple variable reference.
return VariableExpressionNode(identifier_name)
# Call.
self.Next() # eat '('.
args = []
if self.current != CharacterToken(')'):
while True:
args.append(self.ParseExpression())
if self.current == CharacterToken(')'):
break
elif self.current != CharacterToken(','):
raise RuntimeError('Expected ")" or "," in argument list.')
self.Next()
self.Next() # eat ')'.
return CallExpressionNode(identifier_name, args)
# numberexpr ::= number
def ParseNumberExpr(self):
result = NumberExpressionNode(self.current.value)
self.Next() # consume the number.
return result
# parenexpr ::= '(' expression ')'
def ParseParenExpr(self):
self.Next() # eat '('.
contents = self.ParseExpression()
if self.current != CharacterToken(')'):
raise RuntimeError('Expected ")".')
self.Next() # eat ')'.
return contents
# primary ::= identifierexpr | numberexpr | parenexpr
def ParsePrimary(self):
if isinstance(self.current, IdentifierToken):
return self.ParseIdentifierExpr()
elif isinstance(self.current, NumberToken):
return self.ParseNumberExpr()
elif self.current == CharacterToken('('):
return self.ParseParenExpr()
else:
raise RuntimeError('Unknown token when expecting an expression.')
# binoprhs ::= (operator primary)*
def ParseBinOpRHS(self, left, left_precedence):
# If this is a binary operator, find its precedence.
while True:
precedence = self.GetCurrentTokenPrecedence()
# If this is a binary operator that binds at least as tightly as the
# current one, consume it; otherwise we are done.
if precedence < left_precedence:
return left
binary_operator = self.current.char
self.Next() # eat the operator.
# Parse the primary expression after the binary operator.
right = self.ParsePrimary()
# If binary_operator binds less tightly with right than the operator after
# right, let the pending operator take right as its left.
next_precedence = self.GetCurrentTokenPrecedence()
if precedence < next_precedence:
right = self.ParseBinOpRHS(right, precedence + 1)
# Merge left/right.
left = BinaryOperatorExpressionNode(binary_operator, left, right)
# expression ::= primary binoprhs
def ParseExpression(self):
left = self.ParsePrimary()
return self.ParseBinOpRHS(left, 0)
# prototype ::= id '(' id* ')'
def ParsePrototype(self):
if not isinstance(self.current, IdentifierToken):
raise RuntimeError('Expected function name in prototype.')
function_name = self.current.name
self.Next() # eat function name.
if self.current != CharacterToken('('):
raise RuntimeError('Expected "(" in prototype.')
self.Next() # eat '('.
arg_names = []
while isinstance(self.current, IdentifierToken):
arg_names.append(self.current.name)
self.Next()
if self.current != CharacterToken(')'):
raise RuntimeError('Expected ")" in prototype.')
# Success.
self.Next() # eat ')'.
return PrototypeNode(function_name, arg_names)
# definition ::= 'def' prototype expression
def ParseDefinition(self):
self.Next() # eat def.
proto = self.ParsePrototype()
body = self.ParseExpression()
return FunctionNode(proto, body)
# toplevelexpr ::= expression
def ParseTopLevelExpr(self):
proto = PrototypeNode('', [])
return FunctionNode(proto, self.ParseExpression())
# external ::= 'extern' prototype
def ParseExtern(self):
self.Next() # eat extern.
return self.ParsePrototype()
# Top-Level parsing
def HandleDefinition(self):
self.Handle(self.ParseDefinition, 'Read a function definition:')
def HandleExtern(self):
self.Handle(self.ParseExtern, 'Read an extern:')
def HandleTopLevelExpression(self):
try:
function = self.ParseTopLevelExpr().CodeGen()
result = g_llvm_executor.run_function(function, [])
print 'Evaluated to:', result.as_real(Type.double())
except Exception, e:
print 'Error:', e
try:
self.Next() # Skip for error recovery.
except:
pass
def Handle(self, function, message):
try:
print message, function().CodeGen()
except Exception, e:
print 'Error:', e
try:
self.Next() # Skip for error recovery.
except:
pass
################################################################################
## Main driver code.
################################################################################
def main():
# Set up the optimizer pipeline. Start with registering info about how the
# target lays out data structures.
g_llvm_pass_manager.add(g_llvm_executor.target_data)
# Do simple "peephole" optimizations and bit-twiddling optzns.
g_llvm_pass_manager.add(PASS_INSTRUCTION_COMBINING)
# Reassociate expressions.
g_llvm_pass_manager.add(PASS_REASSOCIATE)
# Eliminate Common SubExpressions.
g_llvm_pass_manager.add(PASS_GVN)
# Simplify the control flow graph (deleting unreachable blocks, etc).
g_llvm_pass_manager.add(PASS_CFG_SIMPLIFICATION)
g_llvm_pass_manager.initialize()
# Install standard binary operators.
# 1 is lowest possible precedence. 40 is the highest.
operator_precedence = {
'<': 10,
'+': 20,
'-': 20,
'*': 40
}
# Run the main "interpreter loop".
while True:
print 'ready>',
try:
raw = raw_input()
except KeyboardInterrupt:
break
parser = Parser(Tokenize(raw), operator_precedence)
while True:
# top ::= definition | external | expression | EOF
if isinstance(parser.current, EOFToken):
break
if isinstance(parser.current, DefToken):
parser.HandleDefinition()
elif isinstance(parser.current, ExternToken):
parser.HandleExtern()
else:
parser.HandleTopLevelExpression()
# Print out all of the generated code.
print '\n', g_llvm_module
if __name__ == '__main__':
main()
{% endhighlight %}
* * *
**[Next: Extending the language: control flow](PythonLangImpl5.html)**

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---
layout: page
title: "Kaleidoscope: Chapter 8"
---
# Conclusion and other useful LLVM tidbits
Written by [Chris Lattner](mailto:sabre@nondot.org)
**Chapter 8**
* This will become a table of contents (this text will be scraped).
{:toc}
# Tutorial Conclusion # {#conclusion}
Welcome to the the final chapter of the
[Implementing a language with LLVM](http://www.llvm.org/docs/tutorial/index.html)
tutorial. In the course of this tutorial, we have grown
our little Kaleidoscope language from being a useless toy, to being a
semi-interesting (but probably still useless) toy. :)
It is interesting to see how far we've come, and how little code it has
taken. We built the entire lexer, parser, AST, code generator, and an
interactive run-loop (with a JIT!) by-hand in under 540 lines of
(non-comment/non-blank) code.
Our little language supports a couple of interesting features: it supports
user defined binary and unary operators, it uses JIT compilation for immediate
evaluation, and it supports a few control flow constructs with SSA construction.
Part of the idea of this tutorial was to show you how easy and fun it can be
to define, build, and play with languages. Building a compiler need not be a
scary or mystical process! Now that you've seen some of the basics, I strongly
encourage you to take the code and hack on it. For example, try adding:
* **global variables** -- While global variables have questional value in
modern software engineering, they are often useful when putting together quick
little hacks like the Kaleidoscope compiler itself. Fortunately, our current
setup makes it very easy to add global variables: just have value lookup check
to see if an unresolved variable is in the global variable symbol table before
rejecting it. To create a new global variable, make an instance of the LLVM
`GlobalVariable` class.
* **typed variables** -- Kaleidoscope currently only supports variables of
type double. This gives the language a very nice elegance, because only
supporting one type means that you never have to specify types. Different
languages have different ways of handling this. The easiest way is to require
the user to specify types for every variable definition, and record the type
of the variable in the symbol table along with its Value\*.
* **arrays, structs, vectors, etc** -- Once you add types, you can start
extending the type system in all sorts of interesting ways. Simple arrays are
very easy and are quite useful for many different applications. Adding them is
mostly an exercise in learning how the LLVM
[getelementptr](http://www.llvm.org/docs/LangRef.html#i_getelementptr)
instruction works: it is so nifty/unconventional, it
[has its own FAQ](http://www.llvm.org/docs/GetElementPtr.html)! If you
add support for recursive types (e.g. linked lists), make sure to read the
[section in the LLVM Programmer's Manual](http://www.llvm.org/docs/ProgrammersManual.html#TypeResolve)
that describes how to construct them.
* **standard runtime** -- Our current language allows the user to access
arbitrary external functions, and we use it for things like "putchard". As you
extend the language to add higher-level constructs, often these constructs make
the most sense if they are lowered to calls into a language-supplied runtime.
For example, if you add hash tables to the language, it would probably make
sense to add the routines to a runtime, instead of inlining them all the way.
* **memory management** -- Currently we can only access the stack in
Kaleidoscope. It would also be useful to be able to allocate heap memory,
either with calls to the standard libc malloc/free interface or with a garbage
collector. If you would like to use garbage collection, note that LLVM fully
supports
[Accurate Garbage Collection](http://www.llvm.org/docs/GarbageCollection.html)
including algorithms that move objects and need to
scan/update the stack.
* **debugger support** -- LLVM supports generation of
[DWARF Debug info](http://www.llvm.org/docs/SourceLevelDebugging.html)
which is understood by common debuggers like GDB. Adding support for debug
info is fairly straightforward. The best way to understand it is to compile
some C/C++ code with "`llvm-gcc -g -O0`" and taking a look at
what it produces.
* **exception handling support** - LLVM supports generation of
[zero cost exceptions](http://www.llvm.org/docs/ExceptionHandling.html)
which interoperate with code compiled in other languages. You could also
generate code by implicitly making every function return an error value and
checking it. You could also make explicit use of setjmp/longjmp. There are
many different ways to go here.
* **object orientation, generics, database access, complex numbers,
geometric programming, ...** -- Really, there is
no end of crazy features that you can add to the language.
* **unusual domains** -- We've been talking about applying LLVM to a domain
that many people are interested in: building a compiler for a specific language.
However, there are many other domains that can use compiler technology that are
not typically considered. For example, LLVM has been used to implement OpenGL
graphics acceleration, translate C++ code to ActionScript, and many other
cute and clever things. Maybe you will be the first to JIT compile a regular
expression interpreter into native code with LLVM?
Have fun - try doing something crazy and unusual. Building a language like
everyone else always has, is much less fun than trying something a little crazy
or off the wall and seeing how it turns out. If you get stuck or want to talk
about it, feel free to email the
[llvmdev mailing list](http://lists.cs.uiuc.edu/mailman/listinfo/llvmdev):
it has lots of people who are interested in languages and are often
willing to help out.
Before we end this tutorial, I want to talk about some "tips and tricks" for
generating LLVM IR. These are some of the more subtle things that may not be
obvious, but are very useful if you want to take advantage of LLVM's
capabilities.
* * *
# Properties of the LLVM IR # {#llvmirproperties}
We have a couple common questions about code in the LLVM IR form - let's just
get these out of the way right now, shall we?
## Target Independence ## {#targetindep}
Kaleidoscope is an example of a "portable language": any program written in
Kaleidoscope will work the same way on any target that it runs on. Many other
languages have this property, e.g. LISP, Java, Haskell, Javascript, Python, etc.
(note that while these languages are portable, not all their libraries are).
One nice aspect of LLVM is that it is often capable of preserving target
independence in the IR: you can take the LLVM IR for a Kaleidoscope-compiled
program and run it on any target that LLVM supports, even emitting C code and
compiling that on targets that LLVM doesn't support natively. You can trivially
tell that the Kaleidoscope compiler generates target-independent code because it
never queries for any target-specific information when generating code.
The fact that LLVM provides a compact, target-independent, representation for
code gets a lot of people excited. Unfortunately, these people are usually
thinking about C or a language from the C family when they are asking questions
about language portability. I say "unfortunately", because there is really no
way to make (fully general) C code portable, other than shipping the source code
around (and of course, C source code is not actually portable in general
either - ever port a really old application from 32- to 64-bits?).
The problem with C (again, in its full generality) is that it is heavily
laden with target specific assumptions. As one simple example, the preprocessor
often destructively removes target-independence from the code when it processes
the input text:
{% highlight c %}
#ifdef __i386__
int X = 1;
#else
int X = 42;
#endif
{% endhighlight %}
While it is possible to engineer more and more complex solutions to problems
like this, it cannot be solved in full generality in a way that is better than
shipping the actual source code.
That said, there are interesting subsets of C that can be made portable. If
you are willing to fix primitive types to a fixed size (say int = 32-bits,
and long = 64-bits), don't care about ABI compatibility with existing binaries,
and are willing to give up some other minor features, you can have portable
code. This can make sense for specialized domains such as an
in-kernel language.
## Safety Guarantees ## {#safety}
Many of the languages above are also "safe" languages: it is impossible for
a program written in Java to corrupt its address space and crash the process
(assuming the JVM has no bugs).
Safety is an interesting property that requires a combination of language
design, runtime support, and often operating system support.
It is certainly possible to implement a safe language in LLVM, but LLVM IR
does not itself guarantee safety. The LLVM IR allows unsafe pointer casts,
use after free bugs, buffer over-runs, and a variety of other problems. Safety
needs to be implemented as a layer on top of LLVM and, conveniently, several
groups have investigated this. Ask on the
[llvmdev mailing list](http://lists.cs.uiuc.edu/mailman/listinfo/llvmdev)
if you are interested in more details.
## Language-Specific Optimizations ## {#langspecific}
One thing about LLVM that turns off many people is that it does not solve all
the world's problems in one system (sorry 'world hunger', someone else will have
to solve you some other day). One specific complaint is that people perceive
LLVM as being incapable of performing high-level language-specific optimization:
LLVM "loses too much information".
Unfortunately, this is really not the place to give you a full and unified
version of "Chris Lattner's theory of compiler design". Instead, I'll make a
few observations:
First, you're right that LLVM does lose information. For example, as of this
writing, there is no way to distinguish in the LLVM IR whether an SSA-value came
from a C "int" or a C "long" on an ILP32 machine (other than debug info). Both
get compiled down to an 'i32' value and the information about what it came from
is lost. The more general issue here, is that the LLVM type system uses
"structural equivalence" instead of "name equivalence". Another place this
surprises people is if you have two types in a high-level language that have the
same structure (e.g. two different structs that have a single int field): these
types will compile down into a single LLVM type and it will be impossible to
tell what it came from.
Second, while LLVM does lose information, LLVM is not a fixed target: we
continue to enhance and improve it in many different ways. In addition to
adding new features (LLVM did not always support exceptions or debug info), we
also extend the IR to capture important information for optimization (e.g.
whether an argument is sign or zero extended, information about pointers
aliasing, etc). Many of the enhancements are user-driven: people want LLVM to
include some specific feature, so they go ahead and extend it.
Third, it is *possible and easy* to add language-specific
optimizations, and you have a number of choices in how to do it. As one trivial
example, it is easy to add language-specific optimization passes that
"know" things about code compiled for a language. In the case of the C family,
there is an optimization pass that "knows" about the standard C library
functions. If you call "exit(0)" in main(), it knows that it is safe to
optimize that into "return 0;" because C specifies what the 'exit'
function does.
In addition to simple library knowledge, it is possible to embed a variety of
other language-specific information into the LLVM IR. If you have a specific
need and run into a wall, please bring the topic up on the llvmdev list. At the
very worst, you can always treat LLVM as if it were a "dumb code generator" and
implement the high-level optimizations you desire in your front-end, on the
language-specific AST.
* * *
# Tips and Tricks # {#tipsandtricks}
There is a variety of useful tips and tricks that you come to know after
working on/with LLVM that aren't obvious at first glance. Instead of letting
everyone rediscover them, this section talks about some of these issues.
## Implementing portable offsetof/sizeof ## {#offsetofsizeof}
One interesting thing that comes up, if you are trying to keep the code
generated by your compiler "target independent", is that you often need to know
the size of some LLVM type or the offset of some field in an llvm structure.
For example, you might need to pass the size of a type into a function that
allocates memory.
Unfortunately, this can vary widely across targets: for example the width of
a pointer is trivially target-specific. However, there is a
[clever way to use the getelementptr instruction](http://nondot.org/sabre/LLVMNotes/SizeOf-OffsetOf-VariableSizedStructs.txt)
that allows you to compute this in a portable way.
## Garbage Collected Stack Frames ## {#gcstack}
Some languages want to explicitly manage their stack frames, often so that
they are garbage collected or to allow easy implementation of closures. There
are often better ways to implement these features than explicit stack frames,
but [LLVM does support them](http://nondot.org/sabre/LLVMNotes/ExplicitlyManagedStackFrames.txt),
if you want. It requires your front-end to convert the code into
[Continuation Passing Style](http://en.wikipedia.org/wiki/Continuation-passing_style)
and the use of tail calls (which LLVM also supports).

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---
layout: page
title: The llvm-py Package
---
The llvm-py is a Python package, consisting of 6 modules, that wrap
over enough LLVM APIs to allow the implementation of your own
compiler/VM backend in pure Python. If you're come this far, you
probably know why this is a good idea.
Out of the 6 modules, one is an "extension" module (i.e., it is
written in C), and another one is a small private utility module, which
leaves 4 public modules. These are:
- *llvm* -- top-level package, common classes (like exceptions)
- *llvm.core* -- IR-related APIs
- *llvm.ee* -- execution engine related APIs
- *llvm.passes* -- pass manager and passes related APIs
The modules contain only classes and (integer) constants. Mostly simple
Python constructs are used (deliberately) --
[property()](http://docs.python.org/lib/built-in-funcs.html) and
[property decorators](http://wiki.python.org/moin/PythonDecoratorLibrary) are probably the most exotic animals around. All classes are
"new style" classes. The APIs are designed to be navigable (and
guessable!) once you know a few conventions. These conventions are
highlighted in the sections below.
Here is a quick overview of the contents of each package:
## llvm
- LLVMException -- exception class (currently the only one)
## llvm.core
- [Module](llvm.core.Module.html) -- represents an LLVM Module
- [Type](types.html) -- represents an LLVM Type
- [Value](values.html) -- represents an LLVM Value, including:
globals, constants, variables, arguments, functions, instructions, etc..
- [BasicBlock](llvm.core.BasicBlock.html) -- another derived of Value,
represents an LLVM basic block
- [Builder](llvm.core.Builder.html) -- used for creating instructions,
wraps LLVM IRBuilder helper
class
- constants *TYPE_\** that represents various types
- constants *CC_\** that represent calling conventions
- constants *ICMP_\** and *FCMP_\** that represent integer and real
comparison predicates (like less than, greater than etc.)
- constants *LINKAGE_\** that represent linkage of symbols (external,
internal etc.)
- constants *VISIBILITY_\** that represents visibility of symbols
(default, hidden, protected)
- constants *ATTR_\** that represent function parameter attributes
## llvm.ee
- [ExecutionEngine](llvm.ee.ExecutionEngine.html)
-- represents an execution engine (which can be an
either an interpreter or a JIT)
- [TargetData](llvm.ee.TargetData.html)
-- represents the ABI of the target platform (details like
sizes and alignment of primitive types, endinanness etc)
## llvm.passes
- [PassManager](llvm.passes.PassManager.html)
-- represents an LLVM pass manager
- [FunctionPassManager](llvm.passes.FunctionPassManager.html)
-- represents an LLVM function pass manager
- constants *PASS_\** that represent various passes
## A note on the importing of these modules
Pythonically, modules are imported with the statement `import
llvm.core`. However, you might find it more convenient to import
llvm-py modules thus:
{% highlight python %}
from llvm import *
from llvm.core import *
from llvm.ee import *
from llvm.passes import *
{% endhighlight %}
This avoids quite some typing. Both conventions work, however.
> **Tip**
>
>
> Python-style documentation strings (`__doc__`) are present in
> llvm-py. You can use the `help()` of the interactive Python
> interpreter or the `object?` of [IPython](http://ipython.scipy.org/moin/)
> to get online help. (Note: not complete yet!)

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---
layout: page
title: Argument (llvm.core)
---
The `args` property of `llvm.core.Function` objects yields
`llvm.core.Argument` objects. This allows for setting attributes for
functions arguments. `Argument` objects cannot be constructed from user
code, the only way to get a reference to these are from `Function`
objects.
The method `add_attribute` and `remove_attribute` can be used to add or
remove the following attributes:
Value| Equivalent LLVM Assembly Keyword |
-----|----------------------------------|
`ATTR_ZEXT`| `zeroext` |
`ATTR_SEXT`| `signext` |
`ATTR_IN_REG`| `inreg` |
`ATTR_BY_VAL`| `byval` |
`ATTR_STRUCT_RET`| `sret` |
`ATTR_NO_ALIAS`| `noalias` |
`ATTR_NO_CAPTURE`| `nocapture` |
`ATTR_NEST`| `nest` |
These method work exactly like the
[corresponding methods](functions.html#fnattr)
of the `Function` class above. Refer
[LLVM docs](http://www.llvm.org/docs/LangRef.html#paramattrs)
for information on what each attribute means.
The alignment of any argument can be set via the `alignment`
property, to any power of 2.
# llvm.core.Argument
## Base Class
- [llvm.core.Value](llvm.core.Value.html)
## Properties
### `alignment`
The alignment of the argument. Must be a power of 2.
## Methods
### `add_attribute(attr)`
Add an attribute `attr` to the argument, from the set listed above.
### `remove_attribute(attr)`
Remove the attribute `attr` of the argument.

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---
layout: page
title: ArrayType (llvm.core)
---
# llvm.core.ArrayType
## Base Class
- [llvm.core.Type](llvm.core.Type.html)
## Properties
### `element`
\[read-only\]
A `Type` object representing the type of the element of the array.
### `count`
\[read-only\]
The number of elements in the array.

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---
layout: page
title: BasicBlock (llvm.core)
---
A basicblock is a list of instructions.
A wellformed basicblock should end with a terminator.
`Function.verify()` will verify that.
A terminator is either a branch instruction or return instruction.
It is not possible to have instructions after a branch or return instruction.
# llvm.core.BasicBlock
## Base Class
- [llvm.core.Value][]
## Methods
### `delete(self)`
Delete this basicblock from the function (`self.function`).
### `insert_before(self, name)`
TODO
## Proporties
### `function`
The parent function of this basicblock.
### `instructions`
A list of instructions in this basicblock.
[llvm.core.Value]: llvm.core.Value.html
[llvm.core.Function]: llvm.core.Function.html

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---
layout: page
title: Builder (llvm.core)
---
The `Builder` class corresponds to the
[IRBuilder](http://llvm.org/docs/doxygen/html/classllvm_1_1IRBuilder.html)
in C++ llvm. It provides an uniform API to
populating [BasicBlocks][llvm.core.BasicBlock].
Most of the methods in `Builder` correspond to the instructions in the LLVM IR.
See [LLVM documentation](http://llvm.org/docs/LangRef.html) for detail.
These methods have the `name` argument for overiding the name
of the result variable. When it is an empty string (default value),
LLVM will set a numeric ID for the result variable.
# llvm.core.Builder
* This will become a table of contents (this text will be scraped).
{:toc}
## Static Factor Method
### `new(basic_block)`
Create an instance of `Builder` at [BasicBlock][llvm.core.BasicBlock].
## Methods
### `add(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs+rhs` for integer values only.
### `alloca(self, ty, name='')`
Insert an instruction that allocates stack memory for a value of type `ty`.
### `alloca_array(self, ty, size, name='')`
Insert an instruction that allocates stack memory for a `size` elements array
of type `ty`.
### `and_(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs & rhs`.
### `ashr(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs >> rhs` using arithmetic shift.
### `bitcast(self, value, dest_ty, name='')`
Insert an instruction that cast `value` to type `dest_ty`.
### `branch(self, bblk)`
Insert an instruction that branch to basicblock `bblk`.
### `call(self, fn, args, name='')`
Insert an instruction that call function `fn` with a iterable of
arguments `args`.
### `cbranch(self, if_value, then_blk, else_blk)`
Insert an instruction that conditionally branch base on
the predicate `if_value`.
If `if_value` is `True`, branch to `then_blk`;
Otherwise, branch to `else_blk`.
### `extract_element(self, vec_val, idx_val, name='')`
Insert an instruction that extracts an element from a value `vec_val` of
[llvm.core.VectorType][] at index `idx_val`.
### `extract_value(self, retval, idx, name='')`
Insert an instruction that extracts an element from an aggregate value `retval`
at index `idx`.
### `fadd(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs + rhs` for floating-point values.
### `fcmp(self, rpred, lhs, rhs, name='')`
Insert an instruction that compares `lhs` and `rhs` using the comparision
operation defined by `rpred`.
See [here](comparision.html#fcmp) for a list of comparators.
### `fdiv(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs / rhs` for floating-point values.
### `fmul(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs * rhs` for floating-point values.
### `fpext(self, value, dest_ty, name='')`
Insert an instruction that extends `value` to a float type `dest_ty`.
### `fptosi(self, value, dest_ty, name='')`
Insert an instruction that converts a floating-point value `value`
to a signed integer type `dest_ty`.
### `fptoui(self, value, dest_ty, name='')`
Insert an instruction that converts a floating-point value `value`
to an unsigned integer type `dest_ty`.
### `fptrunc(self, value, dest_ty, name='')`
Insert an instruction that truncates a floating-point value `value`
to a float type `dest_ty`.
### `free(self, ptr)`
Insert an instruction that call performs heap deallocation on pointer `ptr`.
### `frem(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs % rhs` for floating-point values.
### `fsub(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs - rhs` for floating-point values.
### `gep(self, ptr, indices, name='')`
See [GEP](http://llvm.org/docs/LangRef.html#i_getelementptr).
### `getresult(self, retval, idx, name='')`
same as `extract_value`.
### `icmp(self, ipred, lhs, rhs, name='')`
Insert an instruction that compares `lhs` and `rhs` using the comparision
operation defined by `ipred`.
See [here](comparision.html#icmp) for a list of comparators.
### `insert_element(self, vec_val, elt_val, idx_val, name='')`
Insert an instruction that inserts a value `elt_val` into `vec_val` of
[llvm.core.VectorType][] at index `idx_val`.
### `inttoptr(self, value, dest_ty, name='')`
Insert an instruction that converts an integer `value` to pointer `dest_ty`.
### `invoke(self, func, args, then_blk, catch_blk, name='')`
See [invoke](http://llvm.org/docs/LangRef.html#i_invoke)
### `load(self, ptr, name='')`
Insert an instruction that loads a value at the memory pointed by `ptr`.
### `lshr(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs >> rhs` using logical shift.
### `malloc(self, ty, name='')`
Insert an instruction that allocates heap memory of type `ty`.
The instruction returns a pointer that points to a value of type `ty`.
### `malloc_array(self, ty, size, name='')`
Similar to `malloc` but allocates an array of `size` elements.
### `mul(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs * rhs` for integer types.
### `neg(self, val, name='')`
Insert an instruction that computes `0 - val`.
### `not_(self, val, name='')`
Insert an instruction that computes an one's complement of `val`.
### `or_(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs | rhs`.
### `phi(self, ty, name='')`
Create a PHI node of type `ty`.
### `position_at_beginning(self, bblk)`
Position the builder at the beginning of the given block.
Next instruction inserted will be first one in the block.
### `position_at_end(self, bblk)`
Position the builder at the end of the given block.
Next instruction inserted will be last one in the block.
### `position_before(self, instr)`
Position the builder before the given instruction.
The instruction can belong to a basic block other than the current one.
### `ptrtoint(self, value, dest_ty, name='')`
Insert an instruction that converts a pointer to an integer `value` of
type `dest_ty`.
### `ret(self, value)`
Insert an instruction that returns `value`.
### `ret_many(self, values)`
Insert an instruction that returns `values` which is an iterable of
[llvm.core.Value][].
### `ret_void(self)`
Insert an instruction that returns nothing (void).
### `sdiv(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs / rhs` for signed integers.
### `select(self, cond, then_value, else_value, name='')`
Insert an instruction that computes `cond ? then_value : else_value`.
### `sext(self, value, dest_ty, name='')`
Insert an instruction that sign extends an integer `value` to type `dest_ty`.
### `shl(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs << rhs`.
### `shuffle_vector(self, vecA, vecB, mask, name='')`
Insert an instruction that performs a vector shuffle base on the two vectors --
`vecA` and `vecB`, base on a bit mask `mask`. The mask must be a constant.
See [LLVM document](http://llvm.org/docs/LangRef.html#i_shufflevector)
for detail.
### `sitofp(self, value, dest_ty, name='')`
Insert an instruction that converts a signed integer `value` to a floating-point
type `dest_ty`.
### `srem(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs % rhs` for signed integers.
### `store(self, value, ptr)`
Insert an instruction that stores `value` into the memory pointed by `ptr`.
### `sub(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs - rhs`.
### `switch(self, value, else_blk, n=10)`
Insert an instruction that transfer control flow depending on the `value`.
`else_blk` is the default case. `n` sets the number of additional cases.
This method returns an instance of
[SwitchInstruction](llvm.core.Instruction.html#switchinstr)
for adding cases to the switch.
### `trunc(self, value, dest_ty, name='')`
Insert an instruction that truncates an integer `value` to the destination
integer type `dest_ty`.
### `udiv(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs / rhs` for unsigned integers.
### `uitofp(self, value, dest_ty, name='')`
Insert an instruction that converts an unsigned integer `value` to a
floating-point type `dest_ty`.
### `unreachable(self)`
Insert an unreachabe instruction, which has no defined semantics.
See [LLVM document](http://llvm.org/docs/LangRef.html#i_unreachable)
for detail.
### `urem(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs % rhs` for unsigned integers.
### `vaarg(self, list_val, ty, name='')`
This is used to access variable arguments given as `list_val` of type `ty`.
see [LLVM document](http://llvm.org/docs/LangRef.html#int_varargs)
about variable argument intrinsics.
### `xor(self, lhs, rhs, name='')`
Insert an instruction that computes `lhs xor rhs`.
### `zext(self, value, dest_ty, name='')`
Insert an instruction that zero extends `value` to type `dest_ty`.
## Properties
### `basic_block`
The [BasicBlock][llvm.core.BasicBlock] where the builder is positioned.
### `block`
Deprecated. Same as `basic_block`
[llvm.core.BasicBlock]: llvm.core.BasicBlock.html
[llvm.core.Value]: llvm.core.Value.html
[llvm.core.VectorType]: llvm.core.VectorType.html

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---
layout: page
title: Constant (llvm.core)
---
`Constant`-s represents constants that appear within the code. The
values of such objects are known at creation time. Constants can be
created from Python constants. A constant expression is also a constant
-- given a `Constant` object, an operation (like addition, subtraction
etc) can be specified, to yield a new `Constant` object. Let's see some
examples:
{% highlight python %}
#!/usr/bin/env python
ti = Type.int() # a 32-bit int type
k1 = Constant.int(ti, 42) # "int k1 = 42;"
k2 = k1.add( Constant.int( ti, 10 ) ) # "int k2 = k1 + 10;"
tr = Type.float()
r1 = Constant.real(tr, "3.141592") # create from a string
r2 = Constant.real(tr, 1.61803399) # create from a Python float
{% endhighlight %}
# llvm.core.Constant
* This will become a table of contents (this text will be scraped).
{:toc}
## Static factory methods
### `null(ty)`
A null value (all zeros) of type `ty`
### `all_ones(ty)`
All 1's value of type `ty`
### `undef(ty)`
An undefined value of type `ty`
### `int(ty, value)`
Integer of type `ty`, with value `value` (a Python int or long)
### `int_signextend(ty, value)`
Integer of signed type `ty` (use for signed types)
### `real(ty, value)`
Floating point value of type `ty`, with value `value` (a Python float)
### `stringz(value)`
A null-terminated string. `value` is a Python string
### `string(value)`
As `string(ty)`, but not null terminated
### `array(ty, consts)`
Array of type `ty`, initialized with `consts` (an iterable yielding `Constant`
objects of the appropriate type)
### `struct(ty, consts)`
Struct (unpacked) of type `ty`, initialized with `consts` (an iterable yielding
`Constant` objects of the appropriate type)
### `packed_struct(ty, consts)`
As `struct(ty, consts)` but packed
### `vector(consts)`
Vector, initialized with `consts` (an iterable yielding `Constant` objects of
the appropriate type)
### `sizeof(ty)`
Constant value representing the sizeof the type `ty`
## Methods
The following operations on constants are supported. For more details on
any operation, consult the
[Constant Expressions](http://www.llvm.org/docs/LangRef.html#constantexprs)
section of the LLVM Language Reference.
### `k.neg()`
negation, same as `0 - k`
### `k.not_()`
1's complement of `k`. Note trailing underscore.
### `k.add(k2)`
`k + k2`, where `k` and `k2` are integers.
### `k.fadd(k2)`
`k + k2`, where `k` and `k2` are floating-point.
### `k.sub(k2)`
`k - k2`, where `k` and `k2` are integers.
### `k.fsub(k2)`
`k - k2`, where `k` and `k2` are floating-point.
### `k.mul(k2)`
`k * k2`, where `k` and `k2` are integers.
### `k.fmul(k2)`
`k * k2`, where `k` and `k2` are floating-point.
### `k.udiv(k2)`
Quotient of unsigned division of `k` with `k2`
### `k.sdiv(k2)`
Quotient of signed division of `k` with `k2`
### `k.fdiv(k2)`
Quotient of floating point division of `k` with `k2`
### `k.urem(k2)`
Reminder of unsigned division of `k` with `k2`
### `k.srem(k2)`
Reminder of signed division of `k` with `k2`
### `k.frem(k2)`
Reminder of floating point division of `k` with `k2`
### `k.and_(k2)`
Bitwise and of `k` and `k2`. Note trailing underscore.
### `k.or_(k2)`
Bitwise or of `k` and `k2`. Note trailing underscore.
### `k.xor(k2)`
Bitwise exclusive-or of `k` and `k2`.
### `k.icmp(icmp, k2)`
Compare `k` with `k2` using the predicate `icmp`.
See [here](comparision.html#icmp) for
list of predicates for integer operands.
### `k.fcmp(fcmp, k2)`
Compare `k` with `k2` using the predicate `fcmp`.
See [here](comparision.html#fcmp) for list
of predicates for real operands.
### `k.shl(k2)`
Shift `k` left by `k2` bits.
### `k.lshr(k2)`
Shift `k` logically right by `k2` bits (new bits are 0s).
### `k.ashr(k2)`
Shift `k` arithmetically right by `k2` bits (new bits are same as previous sign bit).
### `k.gep(indices)`
GEP, see [LLVM docs](http://www.llvm.org/docs/GetElementPtr.html).
### `k.trunc(ty)`
Truncate `k` to a type `ty` of lower bitwidth.
### `k.sext(ty)`
Sign extend `k` to a type `ty` of higher bitwidth, while extending the sign bit.
### `k.zext(ty)`
Sign extend `k` to a type `ty` of higher bitwidth, all new bits are 0s.
### `k.fptrunc(ty)`
Truncate floating point constant `k` to floating point type `ty` of lower size
than k's.
### `k.fpext(ty)`
Extend floating point constant `k` to floating point type `ty` of higher size
than k's.
### `k.uitofp(ty)`
Convert an unsigned integer constant `k` to floating point constant of
type `ty`.
### `k.sitofp(ty)`
Convert a signed integer constant `k` to floating point constant of type `ty`.
### `k.fptoui(ty)`
Convert a floating point constant `k` to an unsigned integer constant of type `ty`.
### `k.fptosi(ty)`
Convert a floating point constant `k` to a signed integer constant of type `ty`.
### `k.ptrtoint(ty)`
Convert a pointer constant `k` to an integer constant of type `ty`.
### `k.inttoptr(ty)`
Convert an integer constant `k` to a pointer constant of type `ty`.
### `k.bitcast(ty)`
Convert `k` to a (equal-width) constant of type `ty`.
### `k.select(cond,k2,k3)`
Replace value with `k2` if the 1-bit integer constant `cond` is 1,
else with `k3`.
### `k.extract_element(idx)`
Extract value at `idx` (integer constant) from a vector constant `k`.
### `k.insert_element(k2,idx)`
Insert value `k2` (scalar constant) at index `idx` (integer constant) of vector
constant `k`.
### `k.shuffle_vector(k2,mask)`
Shuffle vector constant `k` based on vector constants `k2` and `mask`.
* * *
# Other Constant Classes
The following subclasses of `Constant` do not provide additional
methods, **they serve only to provide richer type information.**
Subclass | LLVM C++ Class | Remarks |
---------|----------------|---------|
`ConstantExpr` | `llvmConstantExpr` | A constant expression |
`ConstantAggregateZero`| `llvmConstantAggregateZero`| All-zero constant |
`ConstantInt`| `llvmConstantInt`| An integer constant |
`ConstantFP`| `llvmConstantFP`| A floating-point constant |
`ConstantArray`| `llvmConstantArray`| An array constant |
`ConstantStruct`| `llvmConstantStruct`| A structure constant |
`ConstantVector`| `llvmConstantVector`| A vector constant |
`ConstantPointerNull`| `llvmConstantPointerNull`| All-zero pointer constant |
`UndefValue`| `llvmUndefValue`| corresponds to `undef` of LLVM IR |
These types are helpful in `isinstance` checks, like so:
{% highlight python %}
ti = Type.int(32)
k1 = Constant.int(ti, 42) # int32_t k1 = 42;
k2 = Constant.array(ti, [k1, k1]) # int32_t k2[] = { k1, k1 };
assert isinstance(k1, ConstantInt)
assert isinstance(k2, ConstantArray)
{% endhighlight %}

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---
layout: page
title: Function (llvm.core)
---
# llvm.core.Function
* This will become a table of contents (this text will be scraped).
{:toc}
## Base Class
- [llvm.core.GlobalValue](llvm.core.GlobalValue.html)
## Static Constructors
### `new(module_obj, func_ty, name)`
Create a function named `name` of type `func_ty` in the module
`module_obj` and return a `Function` object that represents it.
### `get(module_obj, name)`
Return a `Function` object to represent the function
named `name` in the module `module_obj` or raise `LLVMException` if
such a function does not exist.
### `get_or_insert(module_obj, func_ty, name)`
Similar to `get`, except that if the function does not exist it
is added first, as though with `new`.
### `intrinsic(module_obj, intrinsic_id, types)`
Create and return a `Function` object that refers to an intrinsic
function, as described [here](functions.html#intrinsic).
## Properties
### `calling_convention`
The calling convention for the function,
as listed [here](functions.html#callconv).
### `collector`
A string holding the name of the garbage collection algorithm.
See [LLVM docs](http://www.llvm.org/docs/LangRef.html#gc).
### `does_not_throw`
Setting to True sets the `ATTR_NO_UNWIND` attribute, False
removes it. Shortcut to using `f.add_attribute(ATTR_NO_UNWIND)`
and `f.remove_attribute(ATTR_NO_UNWIND)`.
### `args`
\[read-only\]
List of [llvm.core.Argument][] objects representing the formal
arguments of the function.
### `basic_block_count`
\[read-only\]
Number of basic blocks belonging to this function. Same as
`len(f.basic_blocks)` but faster if you just want the count.
### `entry_basic_block`
\[read-only\]
The [llvm.core.BasicBlock][] object representing the entry
basic block for this function, or `None` if there are no
basic blocks.
### `basic_blocks`
\[read-only\]
List of [llvm.core.BasicBlock][] objects representing the
basic blocks belonging to this function.
### `intrinsic_id`
\[read-only\]
Returns the ID of the intrinsic if this object represents an
intrinsic instruction. Otherwise 0.
## Methods
### `delete()`
Deletes the function from it's module. Do not hold any
references to this object after calling `delete` on it.
### `append_basic_block(name)`
Add a new basic block named `name`, and return a corresponding
[llvm.core.BasicBlock][] object. Note that if this is not the
entry basic block, you'll have to add appropriate branch
instructions from other basic blocks yourself.
### `add_attribute(attr)`
Add an attribute `attr` to the function, from the set listed above.
### `remove_attribute(attr)`
Remove the attribute `attr` of the function.
### `viewCFG()`
Displays the control flow graph using the GraphViz tool.
### `viewCFGOnly()`
Displays the control flow graph using the GraphViz tool, but
omitting function bodies.
### `verify()`
Verifies the function. See [LLVM docs](http://llvm.org/docs/Passes.html#verify).
[llvm.core.Argument]: llvm.core.Argument.html
[llvm.core.BasicBlock]: llvm.core.BasicBlock.html

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---
layout: page
title: FunctionType (llvm.core)
---
# llvm.core.FunctionType
## Base Class
- [llvm.core.Type](llvm.core.Type.html)
## Properties
### `return_type`
\[read-only\]
A [Type][llvm.core.Type] object, representing the return type of the function.
### `vararg`
\[read-only\]
`True` if the function is variadic.
### `args`
\[read-only\]
Returns an iterable object that yields [Type][llvm.core.Type] objects that
represent, in order, the types of the arguments accepted by the
function. Used like this:
{% highlight python %}
func_type = Type.function( Type.int(), [ Type.int(), Type.int() ] )
for arg in func_type.args:
assert arg.kind == TYPE_INTEGER
assert arg == Type.int()
assert func_type.arg_count == len(func_type.args)
{% endhighlight %}
### `arg_count`
\[read-only\]
The number of arguments. Same as `len(obj.args)`, but faster.
[llvm.core.Type]: llvm.core.Type.html

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---
layout: page
title: GlobalValue (llvm.core)
---
The class `llvm.core.GlobalValue` represents module-scope aliases, variables
and functions. Global variables are represented by the sub-class
[llvm.core.GlobalVariable][] and functions by [llvm.core.Function][].
Global values have the read-write properties `linkage`, `section`,
`visibility` and `alignment`. Use one of the following constants (from
llvm.core) as values for `linkage`
(see [LLVM documentaion](http://www.llvm.org/docs/LangRef.html#linkage) for
details on each):
Value | Equivalent LLVM Assembly Keyword |
------|----------------------------------|
`LINKAGE_EXTERNAL` | `externally_visible` |
`LINKAGE_AVAILABLE_EXTERNALLY` | `available_externally` |
`LINKAGE_LINKONCE_ANY` | `linkonce` |
`LINKAGE_LINKONCE_ODR` | `linkonce_odr` |
`LINKAGE_WEAK_ANY` | `weak` |
`LINKAGE_WEAK_ODR` | `weak_odr` |
`LINKAGE_APPENDING` | `appending` |
`LINKAGE_INTERNAL` | `internal` |
`LINKAGE_PRIVATE` | `private` |
`LINKAGE_DLLIMPORT` | `dllimport` |
`LINKAGE_DLLEXPORT` | `dllexport` |
`LINKAGE_EXTERNAL_WEAK` | `extern_weak` |
`LINKAGE_GHOST` | deprecated -- do not use |
`LINKAGE_COMMON` | `common` |
`LINKAGE_LINKER_PRIVATE` | `linker_private` |
<br/>
The `section` property can be assigned strings (like ".rodata"), which
will be used if the target supports it. Visibility property can be set
to one of thse constants (from llvm.core, see also
[LLVM docs](http://www.llvm.org/docs/LangRef.html#visibility)):
Value | Equivalent LLVM Assembly Keyword |
------|----------------------------------|
`VISIBILITY_DEFAULT` | `default` |
`VISIBILITY_HIDDEN` | `hidden` |
`VISIBILITY_PROTECTED` | `protected` |
<br/>
The `alignment` property can be 0 (default), or can be set to a power of 2.
The read-only property `is_declaration` can be used to check if the
global is a declaration or not. The module to which the global belongs
to can be retrieved using the `module` property (read-only).
# llvm.core.GlobalValue
* This will become a table of contents (this text will be scraped).
{:toc}
## Base Class
- [llvm.core.Constant](llvm.core.Constant.html)
## Properties
### `linkage`
The linkage type, takes one of the constants listed above (LINKAGE_\*).
### `section`
A string like ".rodata", indicating the section into which the
global is placed into.
### `visibility`
The visibility type, takes one of the constants listed above (VISIBILITY_\*).
### `alignment`
A power-of-2 integer indicating the boundary to align to.
### `is_declaration`
\[read-only\]
`True` if the global is a declaration, `False` otherwise.
### `module`
\[read-only\]
The module object to which this global belongs to.
[llvm.core.GlobalVariable]: llvm.core.GlobalVariable.html
[llvm.core.Function]: llvm.core.Function.html

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---
layout: page
title: GlobalVariable (llvm.core)
---
Global variables (`llvm.core.GlobalVariable`) are subclasses of
[llvm.core.GlobalValue][] and represent module-level variables. These can
have optional initializers and can be marked as constants. Global
variables can be created either by using the `add_global_variable`
method of the [Module][llvm.core.Module] class, or by using the static method
`GlobalVariable.new`.
{% highlight python %}
# create a global variable using add_global_variable method
gv1 = module_obj.add_global_variable(Type.int(), "gv1")
# or equivalently, using a static constructor method
gv2 = GlobalVariable.new(module_obj, Type.int(), "gv2")
{% endhighlight %}
Existing global variables of a module can be accessed by name using
`module_obj.get_global_variable_named(name)` or `GlobalVariable.get`.
All existing global variables can be enumerated via iterating over the
property `module_obj.global_variables`.
{% highlight python %}
# retrieve a reference to the global variable gv1,
# using the get_global_variable_named method
gv1 = module_obj.get_global_variable_named("gv1")
# or equivalently, using the static `get` method:
gv2 = GlobalVariable.get(module_obj, "gv2")
# list all global variables in a module
for gv in module_obj.global_variables:
print gv.name, "of type", gv.type
{% endhighlight %}
The initializer for a global variable can be set by assigning to the
`initializer` property of the object. The `is_global_constant` property
can be used to indicate that the variable is a global constant.
Global variables can be delete using the `delete` method. Do not use the
object after calling `delete` on it.
{% highlight python %}
# add an initializer 10 (32-bit integer)
gv.initializer = Constant.int( Type.int(), 10 )
# delete the global
gv.delete()
# DO NOT dereference `gv' beyond this point!
gv = None
{% endhighlight %}
# llvm.core.GlobalVariable
## Base Class
- [llvm.core.GlobalValue](llvm.core.GlobalValue.html)
## Static Constructors
### `new(module_obj, ty, name)`
Create a global variable named `name` of type `ty` in the module
`module_obj` and return a `GlobalVariable` object that represents it.
### `get(module_obj, name)`
Return a `GlobalVariable` object to represent the global variable
named `name` in the module `module_obj` or raise `LLVMException` if
such a variable does not exist.
## Properties
### `initializer`
The intializer of the variable. Set to [llvm.core.Constant][] (or
derived). Gets the initializer constant, or `None` if none exists.
`global_constant`
`True` if the variable is a global constant, `False` otherwise.
## Methods
### `delete()`
Deletes the global variable from it's module.
**Do not hold any references to this object after calling `delete` on it.**
[llvm.core.Module]: llvm.core.Module.html
[llvm.core.Constant]: llvm.core.Constant.html
[llvm.core.GlobalValue]: llvm.core.GlobalValue.html

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---
layout: page
title: Instruction (llvm.core)
---
An `llvm.core.Instruction` object represents an LLVM instruction. This
class is the root of a small hierarchy:
Instruction
CallOrInvokeInstruction
PHINode
SwitchInstruction
CompareInstruction
Instructions are not created directly, but via a builder. The builder
both creates instructions and adds them to a basic block at the same
time. One way of getting instruction objects are from basic blocks.
Being derived from [llvm.core.User][], the instruction
is-a user, i.e., an instruction in turn uses other values. The values
an instruction uses are its operands. These may be accessed using
`operands` property from the [llvm.core.User][] base.
The name of the instruction (like `add`, `mul` etc) can be got
via the `opcode_name` property. The `basic_block` property gives
the basic block to which the instruction belongs to. Note that
llvm-py does not allow free-standing instruction objects (i.e.,
all instructions are created contained within a basic block).
Classes of instructions can be got via the properties
`is_terminator`, `is_binary_op`, `is_shift` etc. See below for
the full list.
* This will become a table of contents (this text will be scraped).
{:toc}
# llvm.core.Instruction
## Base Class
- [llvm.core.User](llvm.core.User.html)
## Properties
### `basic_block`
\[read-only\]
The basic block to which this instruction belongs to.
### `is_terminator`
\[read-only\]
True if the instruction is a terminator instruction.
### `is_binary_op`
\[read-only\]
True if the instruction is a binary operator.
### `is_shift`
\[read-only\]
True if the instruction is a shift instruction.
### `is_cast`
\[read-only\]
True if the instruction is a cast instruction.
### `is_logical_shift`
\[read-only\]
True if the instruction is a logical shift instruction.
### `is_arithmetic_shift`
\[read-only\]
True if the instruction is an arithmetic shift instruction.
### `is_associative`
\[read-only\]
True if the instruction is associative.
### `is_commutative`
\[read-only\]
True if the instruction is commutative.
### `is_volatile`
\[read-only\]
True if the instruction is a volatile load or store.
### `opcode`
\[read-only\]
The numeric opcode value of the instruction. Do not rely
on the absolute value of this number, it may change with
LLVM version.
### `opcode_name`
\[read-only\]
The name of the instruction, like `add`, `sub` etc.
* * *
# llvm.core.CallOrInvokeInstruction
The `llvm.core.CallOrInvokeInstruction` is a subclass of
`llvm.core.Instruction`, and represents either a `call` or an
`invoke` instruction.
## Base Class
- `llvm.core.Instruction`
## Properties
`calling_convention`
Get or set the calling convention. See [here](functions.html#callconv)
for possible values.
## Methods
### `add_parameter_attribute(idx, attr)`
Add an attribute `attr` to the `idx`-th argument. See
[here](llvm.core.Argument.html) for possible values of `attr`.
### `remove_parameter_attribute(idx, attr)`
Remove an attribute `attr` from the `idx`-th argument. See
[here](llvm.core.Argument.html) for possible values of `attr`.
### `set_parameter_alignment(idx, align)`
Set the alignment of the `idx`-th argument to `align`.
`align` should be a power of two.
* * *
# llvm.core.PHINode
The `llvm.core.PHINode` is a subclass of
`llvm.core.Instruction`, and represents the `phi` instruction. When
created (using `Builder.phi`) the phi node contains no incoming
blocks (nor their corresponding values). To add an incoming arc to
the phi node, use the `add_incoming` method, which takes a source
block ([llvm.core.BasicBlock][] object) and a value (object of
[llvm.core.Value][] or of a class derived from it) that the phi node
will take on if control branches in from that block.
## Base Class
- `llvm.core.Instruction`
## Properties
`incoming_count`
\[read-only\]
The number of incoming arcs for this phi node.
## Methods
### `add_incoming(value, block)`
Add an incoming arc, from the [llvm.core.BasicBlock][] object
`block`, with the corresponding value `value`. `value` should
be an object of [llvm.core.Value][] (or of a descendent class).
### `get_incoming_value(idx)`
Returns the `idx`-th incoming arc's value.
### `get_incoming_block(idx)`
Returns the `idx`-th incoming arc's block.
# llvm.core.SwitchInstruction # {#switchinstr}
(TODO describe)
## Base Class
- `llvm.core.Instruction`
## Methods
### `add_case(const, block)`
Add another case to the switch statement. When the expression
being evaluated equals `const`, then control branches to
`block`. Here `const` must be of type
[llvm.core.ConstantInt][llvm.core.Constant].
* * *
# llvm.core.CompareInstruction
(TODO describe)
## Base Class
- `llvm.core.Instruction`
## Properties
###`predicate`
\[read-only\]
The predicate of the compare instruction, one of the `ICMP_*` or
`FCMP_*` constants.
[llvm.core.User]: llvm.core.User.html
[llvm.core.BasicBlock]: llvm.core.BasicBlock.html
[llvm.core.Value]: llvm.core.Value.html
[llvm.core.Constant]: llvm.core.Constant.html

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---
layout: page
title: IntegerType (llvm.core)
---
# llvm.core.IntegerType
## Base Class
- [llvm.core.Type](llvm.core.Type.html)
## Properties
### `width`
\[read-only\]
The width of the integer type, in number of bits.

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---
layout: page
title: Module (llvm.core)
---
Modules are top-level container objects. You need to create a module
object first, before you can add global variables, aliases or functions.
Modules are created using the static method `Module.new`:
{% highlight python %}
#!/usr/bin/env python
from llvm import *
from llvm.core import *
# create a module
my_module = Module.new('my_module')
{% endhighlight %}
The constructor of the Module class should _not_ be used to instantiate
a Module object. This is a common feature for all llvm-py classes.
> **Convention**
>
> *All* llvm-py objects are instantiated using static methods of
> corresponding classes. Constructors _should not_ be used.
>
> The argument `my_module` is a module identifier (a plain string). A
> module can also be constructed via deserialization from a bit code file,
> using the static method `from_bitcode`. This method takes a file-like
> object as argument, i.e., it should have a `read()` method that returns
> the entire data in a single call, as is the case with the builtin file
> object. Here is an example:
{% highlight python %}
# create a module from a bit code file
bcfile = file("test.bc")
my_module = Module.from_bitcode(bcfile)
{% endhighlight %}
There is corresponding serialization method also, called `to_bitcode`:
{% highlight python %}
# write out a bit code file from the module
bcfile = file("test.bc", "w")
my_module.to_bitcode(bcfile)
{% endhighlight %}
Modules can also be constructed from LLVM assembly files (`.ll` files).
The static method `from_assembly` can be used for this. Similar to the
`from_bitcode` method, this one also takes a file-like object as
argument:
{% highlight python %}
# create a module from an assembly file
llfile = file("test.ll")
my_module = Module.from_assembly(llfile)
{% endhighlight %}
Modules can be converted into their assembly representation by
stringifying them (see below).
* * *
# llvm.core.Module
* This will become a table of contents (this text will be scraped).
{:toc}
## Static Constructors
### `new(module_id)`
Create a new `Module` instance with given `module_id`. The `module_id`
should be a string.
### `from_bitcode(fileobj)`
Create a new `Module` instance by deserializing the bitcode file
represented by the file-like object `fileobj`.
### `from_assembly(fileobj)`
Create a new `Module` instance by parsing the LLVM assembly file
represented by the file-like object `fileobj`.
## Properties
### `data_layout`
A string representing the ABI of the platform.
### `target`
A string like `i386-pc-linux-gnu` or `i386-pc-solaris2.8`.
### `pointer_size`
\[read-only\]
The size in bits of pointers, of the target platform. A value of
zero represents `llvm::Module::AnyPointerSize`.
### `global_variables`
\[read-only\]
An iterable that yields [GlobalVariable][llvm.core.GlobalVariable] objects,
that represent the global variables of the module.
### `functions`
\[read-only\]
An iterable that yields [Function][llvm.core.Function] objects,
that represent functions in the module.
### `id`
A string that represents the module identifier (name).
## Methods
### `get_type_named(name)`
Return a [StructType][llvm.core.StructType] object for the given name.
The definition of this method was changed to work with LLVM 3.0+, in which
the type system was rewritten.
See [LLVM Blog](http://blog.llvm.org/2011/11/llvm-30-type-system-rewrite.html).
{% comment %}
++++++++REMOVED+++++++++++
### `add_type_name(name, ty)`
Add an alias (typedef) for the type `ty` with the name `name`.
### `delete_type_name(name)`
Delete an alias with the name `name`.
++++++++END-REMOVED+++++++++++
{% endcomment %}
### `add_global_variable(ty, name)`
Add a global variable of the type `ty` with the name `name`.
Returns a [GlobalVariable][llvm.core.GlobalVariable] object.
### `get_global_variable_named(name)`
Get a [GlobalVariable][llvm.core.GlobalVariable] object corresponding to
the global variable with the name `name`.
Raises `LLVMException` if such a variable does not exist.
### `add_library(name)`
Add a dependent library to the Module. This only adds a name to a list of
dependent library. **No linking is performed**.
### `add_function(ty, name)`
Add a function named `name` with the function type `ty`. `ty` must
of an object of type [FunctionType][llvm.core.FunctionType].
### `get_function_named(name)`
Get a [Function][llvm.core.Function] object corresponding to the function with
the name `name`. Raises `LLVMException` if such a function does not exist.
### `get_or_insert_function(ty, name)`
Like `get_function_named`, but adds the function first, if not
present (like `add_function`).
### `verify()`
Verify the correctness of the module. Raises `LLVMException` on
errors.
### `to_bitcode(fileobj)`
Write the bitcode representation of the module to the file-like
object `fileobj`.
### `link_in(other)`
Link in another module `other` into this module. Global variables,
functions etc. are matched and resolved. The `other` module is no
longer valid and should not be used after this operation. This API
might be replaced with a full-fledged Linker class in the future.
## Special Methods
### `__str__`
`Module` objects can be stringified into it's LLVM assembly language
representation.
### `__eq__`
`Module` objects can be compared for equality. Internally, this
converts both arguments into their LLVM assembly representations and
compares the resultant strings.
> **Convention**
>
> *All* llvm-py objects (where it makes sense), when stringified, return
> the LLVM assembly representation. `print module_obj` for example,
> prints the LLVM assembly form of the entire module.
>
> Such objects, when compared for equality, internally compare these
> string representations.
[llvm.core.Function]: llvm.core.Function.html
[llvm.core.FunctionType]: llvm.core.FunctionType.html
[llvm.core.GlobalVariable]: llvm.core.GlobalVariable.html
[llvm.core.BasicBlock]: llvm.core.BasicBlock.html
[llvm.core.Type]: llvm.core.Type.html
[llvm.core.StructType]: llvm.core.StructType.html

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---
layout: page
title: PointerType (llvm.core)
---
# llvm.core.PointerType
## Base Class
- [llvm.core.Type](llvm.core.Type.html)
## Properties
### `address_space`
\[read-only\]
The address space of the pointer.
### `pointee`
\[read-only\]
A [Type](llvm.core.Type.html) object representing the type of the value pointed to.

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---
layout: page
title: StructType (llvm.core)
---
# llvm.core.StructType
## Base Class
- [llvm.core.Type](llvm.core.Type.html)
## Methods
### `set_body(self, elems, packed=False)`
Define the body for opaque identified structure.
`elems` is an iterable of [llvm.core.Type](llvm.core.Type.html)
If `packed` is `True`, creates a packed structure.
## Properties
### `is_identified`
\[read-only\]
`True` if this is an identified structure.
### `is_literal`
\[read-only\]
`True` if this is a literal structure.
### `is_opaque`
\[read-only\]
`True` if this is an opaque structure.
Only identified structure can be opaque.
### `packed`
\[read-only\]
`True` if the structure is packed (no padding between elements).
### `name`
Use in identified structure.
If set to empty, the identified structure is removed from the global context.
### `elements`
\[read-only\]
Returns an iterable object that yields [Type](llvm.core.Type.html) objects that
represent, in order, the types of the elements of the structure.
Used like this:
{% highlight python %}
struct_type = Type.struct( [ Type.int(), Type.int() ] )
for elem in struct_type.elements:
assert elem.kind == TYPE_INTEGER
assert elem == Type.int()
assert struct_type.element_count == len(struct_type.elements)
{% endhighlight %}
### `element_count`
\[read-only\]
The number of elements. Same as `len(obj.elements)`, but faster.

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---
layout: page
title: Type (llvm.core)
---
# llvm.core.Type
* This will become a table of contents (this text will be scraped).
{:toc}
## Static Constructors
### `int(n)`
Create an integer type of bit width `n`.
### `float()`
Create a 32-bit floating point type.
### `double()`
Create a 64-bit floating point type.
### `x86_fp80()`
Create a 80-bit 80x87-style floating point type.
### `fp128()`
Create a 128-bit floating point type (112-bit mantissa).
### `ppc_fp128()`
Create a 128-bit float (two 64-bits).
### `function(ret, params, vararg=False)`
Create a function type, having the return type `ret` (must be a
`Type`), accepting the parameters `params`, where `params` is an
iterable, that yields `Type` objects representing the type of
each function argument in order. If `vararg` is `True`, function is
variadic.
### `struct(eltys, name='')`
Create an unpacked structure. `eltys` is an iterable, that yields
`Type` objects representing the type of each element in order.
If `name` is evaulates `True` (not empty), create
an *identified structure*; otherwise, create a *literal structure*
by default.
### `packed_struct(eltys, name='')`
Like `struct(eltys)`, but creates a packed struct.
### `array(elty, count)`
Creates an array type, holding `count` elements, each of type `elty`
(which should be a `Type`).
### `pointer(pty, addrspc=0)`
Create a pointer to type `pty` (which should be a `Type`). `addrspc`
is an integer that represents the address space of the pointer (see
LLVM docs or ask on llvm-dev for more info).
### `void()`
Creates a void type. Used for function return types.
### `label()`
Creates a label type.
### `opaque(name)`
Opaque [StructType](llvm.core.StructType.html), used for creating self-referencing types.
## Properties
### `kind`
\[read-only\]
A value (enum) representing the "type" of the object. It will be
one of the following constants defined in `llvm.core`:
{% highlight python %}
# Warning: do not rely on actual numerical values!
TYPE_VOID = 0
TYPE_FLOAT = 1
TYPE_DOUBLE = 2
TYPE_X86_FP80 = 3
TYPE_FP128 = 4
TYPE_PPC_FP128 = 5
TYPE_LABEL = 6
TYPE_INTEGER = 7
TYPE_FUNCTION = 8
TYPE_STRUCT = 9
TYPE_ARRAY = 10
TYPE_POINTER = 11
TYPE_OPAQUE = 12
TYPE_VECTOR = 13
TYPE_METADATA = 14
TYPE_UNION = 15
{% endhighlight %}
#### Example:
{% highlight python %}
assert Type.int().kind == TYPE_INTEGER
assert Type.void().kind == TYPE_VOID
{% endhighlight %}
## Methods
### `refine`
Used for constructing self-referencing types. See the documentation
of [TypeHandle](llvm.core.TypeHandle.html) objects.
## Special Methods
### `__str__`
`Type` objects can be stringified into it's LLVM assembly language
representation.
### `__eq__`
`Type` objects can be compared for equality. Internally, this
converts both arguments into their LLVM assembly representations and
compares the resultant strings.

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---
layout: page
title: User (llvm.core)
---
`User`-s are values that refer to other values. The values so refered
can be retrived by the properties of `User`. This is the reverse of
the `Value.uses`. Together these can be used to traverse the use-def
chains of the SSA.
* * *
# llvm.core.User # {#user}
## Base Class
- [llvm.core.Value][]
## Properties
### `operands`
\[read-only\]
The list of operands (values, of type [llvm.core.Value][]) that this
value refers to.
### `operand_count`
\[read-only\]
The number of operands that this value referes to. Same as
`len(uses.operands)` but faster if you just want the count.
[llvm.core.Value]: llvm.core.Value.html

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---
layout: page
title: Value (llvm.core)
---
# llvm.core.Value
* This will become a table of contents (this text will be scraped).
{:toc}
## Properties
### `name`
The name of the value.
### `type`
\[read-only\]
An `llvm.core.Type` object representing the type of the value.
### `uses`
\[read-only\]
The list of values (`llvm.core.Value`) that use this value.
### `use_count`
\[read-only\]
The number of values that use (refer) this value. Same as `len(val.uses)`
but faster if you just want the count.
### `value_id`
\[read-only\]
Returns `llvmValuegetValueID()`. Refer LLVM documentation
for more info.
## Special Methods
### `__str__`
`Value` objects can be stringified into it's LLVM assembly language
representation.
### `__eq__`
`Value` objects can be compared for equality. Internally, this
converts both arguments into their LLVM assembly representations and
compares the resultant strings.

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---
layout: page
title: VectorType (llvm.core)
---
# llvm.core.VectorType
## Base Class
- [llvm.core.Type](llvm.core.Type.html)
## Properties
### `element`
\[read-only\]
A [Type](llvm.core.Type.html) object representing the type of the element of
the vector.
### `count`
\[read-only\]
The number of elements in the vector.

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---
layout: page
title: EngineBuilder (llvm.ee)
---
# llvm.ee.EngineBuilder
A convenient class for building [llvm.ee.ExecutionEngine].
Each `EngineBuilder` instance can only create one `ExecutionEngine`.
## Methods
### `create(self)`
Create and return a new [ExecutionEngine][llvm.ee.ExecutionEngine] instance.
Raise `llvm.LLVMException` if the builder cannot create an `ExecutionEngine`
base on the given configuration.
### `force_interpreter(self)`
Force the output the output `ExecutionEngine` to be an LLVM IR interpreter.
### `force_jit(self)`
Force the output the output `ExecutionEngine` to be a JIT engine.
### `opt(self, level)`
Set the code generation optimization level for a JIT engine.
Valid value of `level` is 0-3, inclusive.
The default setting is 2.
To use vector instructions, such as SSE on Intel processors,
`level` must be 3 (aggressive).
## Static Factory Methods
### `new(module)`
Create a new EngineBuilder. `module` must be a [llvm.core.Module][] instance.
Its ownership is transferred to the resulting
[ExecutionEngine][llvm.ee.ExecutionEngine].
Therefore, it is impossible to create more than one `ExecutionEngine` with
a single `EngineBuilder`
[llvm.core.Module]: llvm.core.Module.html
[llvm.ee.ExecutionEngine]: llvm.ee.ExecutionEngine.html

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---
layout: page
title: ExecutionEngine (llvm.ee)
---
# llvm.ee.ExecutionEngine
## Methods
### `add_module(self, module)`
Add a new module to the ExecutionEngine.
The ownership is of `module` is transferred.
When the `ExecutionEngine` is destroyed, the module is destroyed.
### `free_machine_code_for(self, fn)`
Release memory used for the machine code generated for
the function `fn`.
### `get_pointer_to_function(self, fn)`
Obtain the pointer to the function `fn`.
This forces the ExecutionEngine to generate the machine code
in lazy mode.
If `fn` is not defined, `ExecutionEngine` will lookup the
symbol through `dlsym`.
The returned function pointer can be wrapped as a `ctypes` function.
### `remove_module(self, module)`
Remove the `module`.
### `run_function(self, fn, args)`
Execute the function `fn` with an iterable of arguments `args`
which are of `GenericValue`. This method returns whatever
that is returned by `fn` as a `GenericValue`.
### `run_static_ctors(self)`
### `run_static_dtors(self)`
## Properties
### `target_data`
Access the [TargetData](llvm.ee.TargetData.html)
instance associated with the `ExecutionEngine`.

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---
layout: page
title: GenericValue (llvm.ee)
---
# llvm.ee.GenericValue
* This will become a table of contents (this text will be scraped).
{:toc}
## Methods
### `as_int(self)`
Return the value of this `GenericValue` instance as an unsigned integer
### `as_int_signed(self)`
Return the value of this `GenericValue` instance as a signed integer.
### `as_pointer(self)`
Return the value of this `GenericValue` instance as a pointer.
The type of the return value is `int`.
### `as_real(self, ty)`
Return the value of this `GenericValue` instance as a real number
which type is specified by `ty`. `ty` must be a [Type][] instance
of a real number type.
## Static Factory Methods
### `int(ty, intval)`
Create a `GenericValue` instance with a `int` value,
which is zero-extended if necessary.
The type of the value is specified by `ty`, which is a [Type][] instance.
### `int_signed(ty, intval)`
Create a `GenericValue` instance with a `int` value,
which is sign-extended if necessary.
The type of the value is specified by `ty`, which is a [Type][] instance.
### `pointer(ty, addr)` or `pointer(addr)`
Create a `GenericValue` instance with a `int` value,
which is representing a pointer value.
The two argument version is **deprecated**.
The old code never used `ty` anyway.
[Type]: llvm.core.Type.html

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---
layout: page
title: TargetData (llvm.ee)
---
# llvm.ee.TargetData
* This will become a table of contents (this text will be scraped).
{:toc}
## Methods
### `abi_alignment(self, ty)`
Returns the minimum ABI-required alignment for the specified type `ty`.
### `abi_size(self, ty)`
### `callframe_alignment(self, ty)`
Returns the minimum ABI-required alignment for the specified type `ty` when it is part of a call frame.
### `element_at_offset(self, ty, ofs)`
### `offset_of_element(self, ty, el)`
### `preferred_alignment(self, ty_or_gv)`
### `size(self, ty)`
### `store_size(self, ty)`
### `__str__(self)`
Returns the string representation.
## Static Factory Methods
### `new(strrep)`
Construct a new `TargetData` instance from the string representation
## Properties
### `byte_order`
### `pointer_size`
### `target_integer_type`

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---
layout: page
title: FunctionPassManager (llvm.passes)
---
# llvm.passes.FunctionPassManager
## Base Classes
- [llvm.passes.PassManager](llvm.passes.PassManager.html)
## Methods
### `finalize(self)`
Finalizes all associated function passes in the LLVM system.
Beware that this destroys all associated passes even if another
pass manager is using those passes. This may result is a segfault.
### `initialize(self)`
Initializes all associated function passes in the LLVM system.
### `run(self, fn)`
Run all passes on the given function `fn`.
## Static Factory Methods
### `new(module)`
Create a `FunctionPassManager` instance for a given `module`.

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---
layout: page
title: PassManager (llvm.passes)
---
# llvm.passes.PassManager
## Methods
### `add(self, tgt_data_or_pass_id)`
Add a pass by its ID. A pass IDs are defined as `PASS_*`.
### `run(self, module)`
Run all passes on the given `module`.
## Static Factory Methods
### `new()`
Creates a new `PassManager` instance.

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---
layout: page
title: PassManagerBuilder (llvm.passes)
---
# llvm.passes.PassManagerBuilder
Provide a simple API to populate pass managers for language like C/C++.
Refer to
[LLVM API Documentation](http://llvm.org/docs/doxygen/html/classllvm_1_1PassManagerBuilder.html)
for detail.
## Methods
### `populate(self, pm)`
Populate a [FunctionPassManager](llvm.passes.FunctionPassManager.html)
or [PassManager](llvm.passes.PassManager.html) given as `pm`.
### `use_inliner_with_threshold(self, threshold)`
Use an inliner pass with the given `threshold`.
## Properties
The following properties can be overriden to customize how pass managers
are populated.
### `disable_simplify_lib_calls`
Boolean. Default is `False`.
### `disable_unit_at_a_time`
Boolean. Default is `False`.
### `disable_unroll_loops`
Boolean. Default is `False`.
### `opt_level`
Default is `2`. Valid values are 0-3. Corresponds to O0, O1, O2, O3 as in C/C++
optimization options.
### `size_level`
Default is `0`.
### `vectorize`
Default is `False`.
## Static Factory Methods
### `new()`
Creates a new `PassManagerBuilder` instance.

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---
layout: page
title: LLVM Concepts
---
This section explains a few concepts related to LLVM, not specific
to llvm-py.
# Intermediate Representation
The intermediate representation, or IR for short, is an in-memory data
structure that represents executable code. The IR data structures allow
for creation of types, constants, functions, function arguments,
instructions, global variables and so on. For example, to create a
function _sum_ that takes two integers and returns their sum, we need to
follow these steps:
- create an integer type _ti_ of required bitwidth
- create a function type _tf_ which takes two _ti_ -s and returns
another _ti_
- create a function of type _tf_ named _sum_
- add a _basic block_ to the function
- using a helper object called an _instruction builder_, add two
instructions into the basic block:
. an instruction to add the two arguments and store the result into
a temporary variable
. a return instruction to return the value of the temporary variable
(A basic block is a block of instructions.)
LLVM has it's own instruction set; the instructions used above (*add*
and *ret*) are from this set. The LLVM instructions are at a higher
level than the usual assembly language; for example there are
instructions related to variable argument handling, exception handling,
and garbage collection. These allow high-level languages to be
represented cleanly in the IR.
* * *
# SSA Form and PHI Nodes
All LLVM instructions are represented in the _Static Single Assignment_
(SSA) form. Essentially, this means that any variable can be assigned to
only once. Such a representation facilitates better optimization, among
other benefits.
A consequence of single assignment are PHI (&#934;) nodes. These
are required when a variable can be assigned a different value based on
the path of control flow. For example, the value of *b* at the end of
execution of the snippet below:
{% highlight c %}
a = 1;
if (v < 10)
a = 2;
b = a;
{% endhighlight %}
cannot be determined statically. The value of '2' cannot be assigned to
the 'original' *a*, since *a* can be assigned to only once. There are
two *a* 's in there, and the last assignment has to choose between which
version to pick. This is accomplished by adding a PHI node:
{% highlight c %}
a1 = 1;
if (v < 10)
a2 = 2;
b = PHI(a1, a2);
{% endhighlight %}
The PHI node selects *a1* or *a2*, depending on where the control
reached the PHI node. The argument *a1* of the PHI node is associated
with the block *"a1 = 1;"* and *a2* with the block *"a2 = 2;"*.
PHI nodes have to be explicitly created in the LLVM IR. Accordingly the
LLVM instruction set has an instruction called *phi*.
* * *
# LLVM Assembly Language
The LLVM IR can be represented offline in two formats
- a textual, human-readable form, similar to assembly language,
called the LLVM assembly language (files with .ll extension)
- a binary form, called the LLVM bitcode (files with .bc extension)
All three formats
(the in-memory IR, the LLVM assembly language and the LLVM bitcode)
represent the _same_ information. Each format can be
converted into the other two formats (using LLVM APIs).
The [LLVM demo page](http://www.llvm.org/demo/) lets you type in C or C++
code, converts it into LLVM IR and outputs the IR as LLVM assembly
language code.
Just to get a feel of the LLVM assembly language, here's a function in C,
and the corresponding LLVM assembly (as generated by the demo page):
{% highlight c %}
/* compute sum of 1..n */
unsigned sum(unsigned n)
{
if (n == 0)
return 0;
else
return n + sum(n-1);
}
{% endhighlight %}
The corresponding LLVM assembly:
{% highlight llvm %}
; ModuleID = '/tmp/webcompile/_7149_0.bc'
target datalayout = "e-p:64:64:64-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:64-f32:32:32-f64:64:64-v64:64:64-v128:128:128-a0:0:64-s0:64:64-f80:128:128-n8:16:32:64"
target triple = "x86_64-linux-gnu"
define i32 @sum(i32 %n) nounwind readnone {
entry:
%0 = icmp eq i32 %n, 0 ; <i1> [#uses=1]
br i1 %0, label %bb2, label %bb1
bb1: ; preds = %entry
%1 = add i32 %n, -1 ; <i32> [#uses=2]
%2 = icmp eq i32 %1, 0 ; <i1> [#uses=1]
br i1 %2, label %sum.exit, label %bb1.i
bb1.i: ; preds = %bb1
%3 = add i32 %n, -2 ; <i32> [#uses=1]
%4 = tail call i32 @sum(i32 %3) nounwind ; <i32> [#uses=1]
%5 = add i32 %4, %1 ; <i32> [#uses=1]
br label %sum.exit
sum.exit: ; preds = %bb1.i, %bb1
%6 = phi i32 [ %5, %bb1.i ], [ 0, %bb1 ] ; <i32> [#uses=1]
%7 = add i32 %6, %n ; <i32> [#uses=1]
ret i32 %7
bb2: ; preds = %entry
ret i32 0
}
{% endhighlight %}
Note the usage of SSA form. The long string called `target datalayout` is a
specification of the platform ABI (like endianness, sizes of types,
alignment etc.).
The [LLVM Language Reference](http://www.llvm.org/docs/LangRef.html)
defines the LLVM assembly language including the entire instruction set.
* * *
# Modules
[Modules](./llvm.core.Module.html), in the LLVM IR, are similar to a single *C* language source
file (.c file). A module contains:
- functions (declarations and definitions)
- global variables and constants
- global type aliases for structures
Modules are top-level containers; all executable code representation is
contained within modules. Modules may be combined (linked) together to
give a bigger resultant module. During this process LLVM attempts to
reconcile the references between the combined modules.
* * *
# Optimization and Passes
LLVM provides quite a few optimization algorithms that work on the IR.
These algorithms are organized as _passes_. Each pass does something
specific, like combining redundant instructions. Passes need not always
optimize the IR, it can also do other operations like inserting
instrumentation code, or analyzing the IR (the result of which can be
used by passes that do optimizations) or even printing call graphs.
This LLVM [documentation page](http://www.llvm.org/docs/Passes.html)
describes all the available passes, and what they do.
LLVM does not automatically choose to run any passes, anytime. Passes
have to be explicitly selected and run on each module. This gives you
the flexibility to choose transformations and optimizations that are
most suitable for the code in the module.
There is an LLVM binary called [opt](http://www.llvm.org/cmds/opt.html),
which lets you run passes on bitcode files from the command line. You
can write your own passes (in C/C++, as a shared library). This can be
loaded and executed by +opt+. (Although llvm-py does not allow you to
write your own passes, it does allow you to navigate the entire IR at
any stage, and perform any transforms on it as you like.)
A "pass manager" is responsible for loading passes, selecting the
correct objects to run them on (for example, a pass may work only
on functions, individually) and actually runs them. `opt` is a
command-line wrapper for the pass manager.
LLVM defines two kinds of pass managers:
* The [FunctionPassManager](http://llvm.org/docs/doxygen/html/classllvm_1_1FunctionPassManager.html)
manages function or basic-block passes. These lighter weight passes
can be used immediately after each generated function to reduce memory
footprint.
* The [PassManager](http://llvm.org/docs/doxygen/html/classllvm_1_1PassManager.html)
manages module passes for optimizing the entire module.
* * *
# Bitcode
LLVM IR can be represented as a bitcode format for disk storage. It is [suitable for fast loading by JIT compiler](http://llvm.org/docs/LangRef.html#introduction).
See [LLVM documentation](http://llvm.org/docs/BitCodeFormat.html)
for detail about the bitcode format.
* * *
# Execution Engine, JIT and Interpreter
The *execution engine* implements execution of LLVM IR through an
interpreter or a JIT dynamic compiler. An *execution engine* can
contain multiple modules.
> **Note**
>
>
> Inter-module reference is not possible. That is module `A`
> cannot call a function in module `B`, directly.
* * *
**Next** -- [llvm-py Package](./llvm-py_package.html)

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---
layout: page
title: Types
---
Types are what you think they are. A instance of [llvm.core.Type][], or
one of its derived classes, represent a type. llvm-py does not use as
many classes to represent types as does LLVM itself. Some types are
represented using [llvm.core.Type][] itself and the rest are represented
using derived classes of [llvm.core.Type][]. As usual, an instance is created
via one of the static methods of [Type][llvm.core.Type]. These methods return an
instance of either [llvm.core.Type][] itself or one of its derived
classes.
The following table lists all the available types along with the static
method which has to be used to construct it and the name of the class whose
object is actually returned by the static method.
Name | Constructor Method | Class |
-----|:------------------:|:-----:|
integer of bitwidth *n* | Type.int(n) | [IntegerType][llvm.core.IntegerType] |
32-bit float | Type.float() | [Type][llvm.core.Type] |
64-bit double | Type.double() | [Type][llvm.core.Type] |
80-bit float | Type.x86_fp80() | [Type][llvm.core.Type] |
128-bit float (112-bit mantissa) | Type.fp128() | [Type][llvm.core.Type] |
128-bit float (two 64-bits) | Type.ppc_fp128() | [Type][llvm.core.Type] |
function | Type.function(r, p, v) | [FunctionType][llvm.core.FunctionType] |
unpacked struct | Type.struct(eltys, name) | [StructType][llvm.core.StructType] |
packed struct | Type.packed_struct(eltys, name) | [StructType][llvm.core.StructType] |
opaque struct | Type.opaque(name) | [StructType][llvm.core.StructType] |
array | Type.array(elty, count) | [ArrayType][llvm.core.ArrayType] |
pointer to value of type *pty* | Type.pointer(pty, addrspc) | [PointerType][llvm.core.PointerType] |
vector | Type.vector(elty, count) | [VectorType][llvm.core.VectorType] |
void | Type.void() | [Type][llvm.core.Type] |
label | Type.label() | [Type][llvm.core.Type] |
<br/>
The class hierarchy is:
Type
IntegerType
FunctionType
StructType
ArrayType
PointerType
VectorType
* * *
## An Example
Here is an example that demonstrates the creation of types:
{% highlight python %}
#!/usr/bin/env python
# integers
int_ty = Type.int()
bool_ty = Type.int(1)
int_64bit = Type.int(64)
# floats
sprec_real = Type.float()
dprec_real = Type.double()
# arrays and vectors
intar_ty = Type.array( int_ty, 10 ) # "typedef int intar_ty[10];"
twodim = Type.array( intar_ty , 10 ) # "typedef int twodim[10][10];"
vec = Type.array( int_ty, 10 )
# structures
s1_ty = Type.struct( [ int_ty, sprec_real ] )
# "struct s1_ty { int v1; float v2; };"
# pointers
intptr_ty = Type.pointer(int_ty) # "typedef int *intptr_ty;"
# functions
f1 = Type.function( int_ty, [ int_ty ] )
# functions that take 1 int_ty and return 1 int_ty
f2 = Type.function( Type.void(), [ int_ty, int_ty ] )
# functions that take 2 int_tys and return nothing
f3 = Type.function( Type.void(), ( int_ty, int_ty ) )
# same as f2; any iterable can be used
fnargs = [ Type.pointer( Type.int(8) ) ]
printf = Type.function( Type.int(), fnargs, True ) # variadic function
{% endhighlight %}
* * *
## Another Example: Recursive Type
The type system was rewritten in LLVM 3.0.
The old opaque type was removed.
Instead, identified `StructType` can now be defined without a body.
Doing so creates a opaque structure.
One can then set the body after the construction of a structure.
(See [LLVM Blog](http://blog.llvm.org/2011/11/llvm-30-type-system-rewrite.html)
for detail about the new type system.)
The following code defines a opaque structure, named "mystruct".
The body is defined after the construction using `StructType.set_body`.
The second subtype is a pointer to a "mystruct" type.
{% highlight python %}
ts = Type.opaque('mystruct')
ts.set_body([Type.int(), Type.pointer(ts)])
{% endhighlight %}
* * *
**Related Links**
[llvm.core.Type][],
[llvm.core.IntegerType][],
[llvm.core.FunctionType][],
[llvm.core.StructType][],
[llvm.core.ArrayType][],
[llvm.core.PointerType][],
[llvm.core.VectorType][],
[llvm.core.TypeHandle][]
[llvm.core.Type]: llvm.core.Type.html
[llvm.core.IntegerType]: llvm.core.IntegerType.html
[llvm.core.FunctionType]: llvm.core.FunctionType.html
[llvm.core.StructType]: llvm.core.StructType.html
[llvm.core.ArrayType]: llvm.core.ArrayType.html
[llvm.core.PointerType]: llvm.core.PointerType.html
[llvm.core.VectorType]: llvm.core.VectorType.html
[llvm.core.TypeHandle]: llvm.core.TypeHandle.html

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---
layout: page
title: User Guide
---
llvm-py provides Python bindings for LLVM. This document explains how you can setup and use it. A working knowledge of Python and a basic idea of LLVM is assumed.
# Introduction
[LLVM](http://www.llvm.org/) (Low-Level Virtual Machine) provides enough
infrastructure to use it as the backend for your compiled, or
JIT-compiled language. It provides extensive optimization support, and
static and dynamic (JIT) backends for many platforms. See the website at
<http://www.llvm.org/> to discover more.
Python bindings for LLVM provides a gentler learning curve for working
with the LLVM APIs. It should also be easier to create working
prototypes and experimental languages using this medium.
Together with [clang](http://clang.llvm.org/) or
[llvm-gcc](http://llvm.org/cmds/llvmgcc.html) it also a provides a means
to quickly instrument C and C++ sources. For e.g., llvm-gcc can be used to
generate the LLVM assembly for a given C source file, which can then be
loaded and manipulated (adding profiling code to every function, say) using
a llvm-py based Python script.
## License
Both LLVM and llvm-py are distributed under (different) permissive
open source licenses. llvm-py uses the
[new BSD license](http://opensource.org/licenses/bsd-license.php). More
information is available [here](https://github.com/numba/llvm-py/blob/master/LICENSE).
## Platforms
llvm-py has been built/tested/reported to work on various GNU/Linux
flavours, BSD, Mac OS X; on i386 and amd64 architectures. Windows is not
supported, for a variety of reasons.
## Versions
llvm-py 0.8.2 requires version 3.1 of LLVM. It may not work with previous
versions.
llvm-py has been built and tested with Python 2.7. It should work with
earlier versions. It has not been tried with Python 3.x (patches welcome).
* * *
# Installation
The Git repo of llvm-py is at <https://github.com/numba/llvm-py.git>. You'll
need to build and install it before it can be used.
At least the following will be required for this:
- C and C++ compilers (gcc/g++)
- Python itself
- Python development files (headers and libraries)
- LLVM, either installed or built
On debian-based systems, the first three can be installed with the
command `sudo apt-get install gcc g++ python python-dev`. Ensure that your
distro's repository has the appropriate version of LLVM!
It does not matter which compiler LLVM itself was built with (`g++`,
`llvm-g++` or any other); llvm-py can be built with any compiler. It has
been tried only with gcc/g++ though.
## LLVM and `--enable-pic`
The result of an LLVM build is a set of static libraries and object
files. The llvm-py contains an extension package that is built into a
shared object (_core.so) which links to these static libraries and
object files. It is therefore required that the LLVM libraries and
object files be built with the `-fPIC` option (generate position
independent code). Be sure to use the `--enable-pic` option while
configuring LLVM (default is no PIC), like this:
{% highlight bash %}
~/llvm$ ./configure --enable-pic --enable-optimized
{% endhighlight %}
## llvm-config
In order to build llvm-py, it's build script needs to know from where it
can invoke the llvm helper program, `llvm-config`. If you've installed
LLVM, then this will be available in your `PATH`, and nothing further
needs to be done. If you've built LLVM yourself, or for any reason
`llvm-config` is not in your `PATH`, you'll need to pass the full path
of `llvm-config` to the build script.
You'll need to be 'root' to install llvm-py. Remember that your `PATH`
is different from that of 'root', so even if `llvm-config` is in your
`PATH`, it may not be available when you do `sudo`.
## Steps
Get 3.1 version of LLVM, build it. Make sure '--enable-pic' is passed to LLVM's 'configure'.
Get llvm-py and install it:
{% highlight bash %}
$ git clone git@github.com:numba/llvm-py.git
$ cd llvm-py
$ python setup.py install
{% endhighlight %}
If you need to tell the build script where `llvm-config` is, do it this
way:
{% highlight bash %}
$ python setup.py install --user --llvm-config=/home/mdevan/llvm/Release/bin/llvm-config
{% endhighlight %}
To build a debug version of llvm-py, that links against the debug
libraries of LLVM, use this:
{% highlight bash %}
$ python setup.py build -g --llvm-config=/home/mdevan/llvm/Debug/bin/llvm-config
$ python setup.py install --user --llvm-config=/home/mdevan/llvm/Debug/bin/llvm-config
{% endhighlight %}
Be warned that debug binaries will be huge (100MB+) ! They are required
only if you need to debug into LLVM also.
`setup.py` is a standard Python distutils script. See the Python
documentation regarding
[Installing Python Modules](http://docs.python.org/inst/inst.html) and
[Distributing Python Modules](http://docs.python.org/dist/dist.html)
for more information on such scripts.
* * *
# Uninstall # {#uninstall}
If you'd installed llvm-py with the `--user` option, then llvm-py
would be present under `~/.local/lib/python2.7/site-packages`.
Otherwise, it might be under `/usr/lib/python2.7/site-packages`
or `/usr/local/lib/python2.7/site-packages`. The directory would
vary with your Python version and OS flavour. Look around.
Once you've located the site-packages directory, the modules and
the "egg" can be removed like so:
{% highlight bash %}
$ rm -rf <site-packages>/llvm <site-packages>/llvm_py-<version-specific>.egg-info
{% endhighlight %}
See the [Python documentation](http://docs.python.org/install/index.html)
for more information.
* * *
**Next** -- [LLVM concepts](./llvm_concepts.html)

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---
layout: page
title: Values
---
[llvm.core.Value][] is the base class of all values computed by a program
that may be used as operands to other values. A value has a type
associated with it (an object of [llvm.core.Type][]).
The class hierarchy is:
Value
User
Constant
ConstantExpr
ConstantAggregateZero
ConstantInt
ConstantFP
ConstantArray
ConstantStruct
ConstantVector
ConstantPointerNull
UndefValue
GlobalValue
GlobalVariable
Function
Instruction
CallOrInvokeInstruction
PHINode
SwitchInstruction
CompareInstruction
Argument
BasicBlock
The [Value][llvm.core.Value] class is abstract, it's not meant to be
instantiated. [User][llvm.core.User] is a [Value][llvm.core.Value]
that in turn uses (i.e., can refer to) other values (for
e.g., a constant expression 1+2 refers to two constant values 1 and 2).
[Constant][llvm.core.Constant]-s represent constants that appear within code or
as initializers of globals. They are constructed using static methods of
[Constant][llvm.core.Constant]. Various types of constants are represented by
various subclasses of [Constant][llvm.core.Constant].
However, most of them are empty and do not provide any additional attributes or methods over [Constant][llvm.core.Constant].
The [Function][functions] object represents an instance of a
function type. Such objects contain [Argument][llvm.core.Argument] objects,
which represent the actual,
local-variable-like arguments of the function (not to be confused with
the arguments returned by a function _type_ object -- these represent
the _type_ of the arguments).
The various [Instruction][llvm.core.Instruction]-s are created
by the [Builder][llvm.core.Builder] class. Most
instructions are represented by [Instruction][llvm.core.Instruction] itself,
but there are a few subclasses that represent interesting instructions.
[Value][llvm.core.Value] objects have a type (read-only),
and a name (read-write).
**Related Links**
[functions][],
[comparision][],
[llvm.core.Value][],
[llvm.core.User][],
[llvm.core.Constant][],
[llvm.core.GlobalValue][],
[llvm.core.GlobalVariable][],
[llvm.core.Argument][],
[llvm.core.Instruction][],
[llvm.core.Builder][],
[llvm.core.BasicBlock][]
[llvm.core.Type]: types.html
[functions]: functions.html
[comparision]: comparision.html
[llvm.core.Value]: llvm.core.Value.html
[llvm.core.User]: llvm.core.User.html
[llvm.core.Constant]: llvm.core.Constant.html
[llvm.core.GlobalValue]: llvm.core.GlobalValue.html
[llvm.core.GlobalVariable]: llvm.core.GlobalVariable.html
[llvm.core.Argument]: llvm.core.Argument.html
[llvm.core.Instruction]: llvm.core.Instruction.html
[llvm.core.Builder]: llvm.core.Builder.html
[llvm.core.BasicBlock]: llvm.core.BasicBlock.html