Release 0.5.3 (#1034)
This commit is contained in:
Gabriel Luiz Freitas Almeida
GitHub
commit
4b6ff597a4
4 changed files with 122 additions and 90 deletions
176
poetry.lock
generated
176
poetry.lock
generated
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@ -2046,13 +2046,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
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[[package]]
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name = "google-api-python-client"
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version = "2.102.0"
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version = "2.103.0"
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description = "Google API Client Library for Python"
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optional = false
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python-versions = ">=3.7"
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files = [
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{file = "google-api-python-client-2.102.0.tar.gz", hash = "sha256:906ff9b672a4d5ddad8f4073a040e59f1fba6734909c14cd49938e37be53691d"},
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{file = "google_api_python_client-2.102.0-py2.py3-none-any.whl", hash = "sha256:ce2fb4d80eb24519ced44a1e79030866cc8a6379ed5ba6c76ba46e772cc68137"},
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{file = "google-api-python-client-2.103.0.tar.gz", hash = "sha256:5b48dc23913b9a1b447991add03f27c335831559b5a870c522316eae671caf44"},
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{file = "google_api_python_client-2.103.0-py2.py3-none-any.whl", hash = "sha256:5d6cf80cc34598a85b73e7e689e6eb1ba34f342095aeab9ec408f94521382a7c"},
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]
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[package.dependencies]
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@ -2102,13 +2102,13 @@ httplib2 = ">=0.19.0"
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[[package]]
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name = "google-cloud-aiplatform"
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version = "1.34.0"
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version = "1.35.0"
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description = "Vertex AI API client library"
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optional = false
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python-versions = ">=3.7"
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python-versions = ">=3.8"
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files = [
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{file = "google-cloud-aiplatform-1.34.0.tar.gz", hash = "sha256:4962badc52ed9d992881232ff70dd706f5134d15f30a17908386241247ea4904"},
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{file = "google_cloud_aiplatform-1.34.0-py2.py3-none-any.whl", hash = "sha256:c55e6f7893fecd81622aa1d47c6f5abf8f830917e99ed0af8637fe1e523ec2c6"},
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{file = "google-cloud-aiplatform-1.35.0.tar.gz", hash = "sha256:37fba7528739097463331d19695aab636286b029c7d0a0c021620d30d314015c"},
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{file = "google_cloud_aiplatform-1.35.0-py2.py3-none-any.whl", hash = "sha256:95c8e16d3beb296b2d47d3899226f1bfc9663bc4c9eea8260c5fb7612b9b44b9"},
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]
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[package.dependencies]
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@ -2119,23 +2119,23 @@ google-cloud-storage = ">=1.32.0,<3.0.0dev"
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packaging = ">=14.3"
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proto-plus = ">=1.22.0,<2.0.0dev"
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protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
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shapely = "<2.0.0"
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shapely = "<3.0.0dev"
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[package.extras]
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autologging = ["mlflow (>=1.27.0,<=2.1.1)"]
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cloud-profiler = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
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datasets = ["pyarrow (>=10.0.1)", "pyarrow (>=3.0.0,<8.0dev)"]
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endpoint = ["requests (>=2.28.1)"]
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full = ["cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.103.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (==0.0.11)", "google-vizier (==0.0.11)", "google-vizier (==0.0.4)", "google-vizier (>=0.1.6)", "httpx (>=0.23.0,<0.25.0)", "importlib-metadata (<7.0)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=10.0.1)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyyaml (==5.3.1)", "ray[default] (>=2.4,<2.5)", "ray[default] (>=2.5,<2.5.1)", "requests (>=2.28.1)", "starlette (>=0.17.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)"]
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full = ["cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.103.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (==0.0.11)", "google-vizier (==0.0.11)", "google-vizier (==0.0.4)", "google-vizier (>=0.1.6)", "httpx (>=0.23.0,<0.25.0)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=10.0.1)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyyaml (==5.3.1)", "ray[default] (>=2.4,<2.5)", "ray[default] (>=2.5,<2.5.1)", "requests (>=2.28.1)", "starlette (>=0.17.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)"]
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lit = ["explainable-ai-sdk (>=1.0.0)", "lit-nlp (==0.4.0)", "pandas (>=1.0.0)", "tensorflow (>=2.3.0,<3.0.0dev)"]
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metadata = ["numpy (>=1.15.0)", "pandas (>=1.0.0)"]
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pipelines = ["pyyaml (==5.3.1)"]
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prediction = ["docker (>=5.0.3)", "fastapi (>=0.71.0,<0.103.1)", "httpx (>=0.23.0,<0.25.0)", "starlette (>=0.17.1)", "uvicorn[standard] (>=0.16.0)"]
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preview = ["cloudpickle (<3.0)", "google-cloud-logging (<4.0)", "importlib-metadata (<7.0)"]
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preview = ["cloudpickle (<3.0)", "google-cloud-logging (<4.0)"]
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private-endpoints = ["requests (>=2.28.1)", "urllib3 (>=1.21.1,<1.27)"]
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ray = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "pandas (>=1.0.0)", "pyarrow (>=6.0.1)", "pydantic (<2)", "ray[default] (>=2.4,<2.5)", "ray[default] (>=2.5,<2.5.1)"]
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tensorboard = ["tensorflow (>=2.3.0,<3.0.0dev)"]
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testing = ["cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.103.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (==0.0.11)", "google-vizier (==0.0.11)", "google-vizier (==0.0.4)", "google-vizier (>=0.1.6)", "grpcio-testing", "httpx (>=0.23.0,<0.25.0)", "importlib-metadata (<7.0)", "ipython", "kfp", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=10.0.1)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyfakefs", "pytest-asyncio", "pytest-xdist", "pyyaml (==5.3.1)", "ray[default] (>=2.4,<2.5)", "ray[default] (>=2.5,<2.5.1)", "requests (>=2.28.1)", "requests-toolbelt (<1.0.0)", "scikit-learn", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<=2.12.0)", "tensorflow (>=2.4.0,<3.0.0dev)", "torch", "torch (>=2.0.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost", "xgboost-ray"]
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testing = ["bigframes", "cloudpickle (<3.0)", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<0.103.1)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-cloud-logging (<4.0)", "google-vizier (==0.0.11)", "google-vizier (==0.0.11)", "google-vizier (==0.0.4)", "google-vizier (>=0.1.6)", "grpcio-testing", "httpx (>=0.23.0,<0.25.0)", "ipython", "kfp", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.1.1)", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pyarrow (>=10.0.1)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pydantic (<2)", "pyfakefs", "pytest-asyncio", "pytest-xdist", "pyyaml (==5.3.1)", "ray[default] (>=2.4,<2.5)", "ray[default] (>=2.5,<2.5.1)", "requests (>=2.28.1)", "requests-toolbelt (<1.0.0)", "scikit-learn", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<=2.12.0)", "tensorflow (>=2.4.0,<3.0.0dev)", "torch (>=2.0.0,<2.1.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost", "xgboost-ray"]
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vizier = ["google-vizier (==0.0.11)", "google-vizier (==0.0.11)", "google-vizier (==0.0.4)", "google-vizier (>=0.1.6)"]
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xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
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@ -3283,13 +3283,13 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt
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[[package]]
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name = "jupyter-core"
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version = "5.3.2"
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version = "5.4.0"
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description = "Jupyter core package. A base package on which Jupyter projects rely."
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optional = false
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python-versions = ">=3.8"
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files = [
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[package.dependencies]
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@ -4026,38 +4026,38 @@ dill = ">=0.3.7"
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[[package]]
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name = "mypy"
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version = "1.5.1"
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version = "1.6.0"
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description = "Optional static typing for Python"
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optional = false
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python-versions = ">=3.8"
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[package.dependencies]
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@ -6481,59 +6481,57 @@ testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jar
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|
||||
{file = "shapely-2.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:c7eed1fb3008a8a4a56425334b7eb82651a51f9e9a9c2f72844a2fb394f38a6c"},
|
||||
{file = "shapely-2.0.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:ac1dfc397475d1de485e76de0c3c91cc9d79bd39012a84bb0f5e8a199fc17bef"},
|
||||
{file = "shapely-2.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:33403b8896e1d98aaa3a52110d828b18985d740cc9f34f198922018b1e0f8afe"},
|
||||
{file = "shapely-2.0.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:2569a4b91caeef54dd5ae9091ae6f63526d8ca0b376b5bb9fd1a3195d047d7d4"},
|
||||
{file = "shapely-2.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a70a614791ff65f5e283feed747e1cc3d9e6c6ba91556e640636bbb0a1e32a71"},
|
||||
{file = "shapely-2.0.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c43755d2c46b75a7b74ac6226d2cc9fa2a76c3263c5ae70c195c6fb4e7b08e79"},
|
||||
{file = "shapely-2.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ad81f292fffbd568ae71828e6c387da7eb5384a79db9b4fde14dd9fdeffca9a"},
|
||||
{file = "shapely-2.0.1-cp39-cp39-win32.whl", hash = "sha256:b50c401b64883e61556a90b89948297f1714dbac29243d17ed9284a47e6dd731"},
|
||||
{file = "shapely-2.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:bca57b683e3d94d0919e2f31e4d70fdfbb7059650ef1b431d9f4e045690edcd5"},
|
||||
{file = "shapely-2.0.1.tar.gz", hash = "sha256:66a6b1a3e72ece97fc85536a281476f9b7794de2e646ca8a4517e2e3c1446893"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
numpy = ">=1.14"
|
||||
|
||||
[package.extras]
|
||||
all = ["numpy", "pytest", "pytest-cov"]
|
||||
docs = ["matplotlib", "numpydoc (==1.1.*)", "sphinx", "sphinx-book-theme", "sphinx-remove-toctrees"]
|
||||
test = ["pytest", "pytest-cov"]
|
||||
vectorized = ["numpy"]
|
||||
|
||||
[[package]]
|
||||
name = "six"
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "langflow"
|
||||
version = "0.5.2"
|
||||
version = "0.5.3"
|
||||
description = "A Python package with a built-in web application"
|
||||
authors = ["Logspace <contact@logspace.ai>"]
|
||||
maintainers = [
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ from typing import Sequence, Union
|
|||
|
||||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
from sqlalchemy import exc
|
||||
import sqlmodel # noqa: F401
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
|
|
@ -20,16 +21,21 @@ depends_on: Union[str, Sequence[str], None] = None
|
|||
|
||||
def upgrade() -> None:
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
connection = op.get_bind()
|
||||
try:
|
||||
op.drop_table("flowstyle")
|
||||
with op.batch_alter_table("component", schema=None) as batch_op:
|
||||
batch_op.drop_index("ix_component_frontend_node_id")
|
||||
batch_op.drop_index("ix_component_name")
|
||||
except exc.SQLAlchemyError:
|
||||
connection.execute("ROLLBACK")
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
try:
|
||||
op.drop_table("component")
|
||||
except exc.SQLAlchemyError:
|
||||
connection.execute("ROLLBACK")
|
||||
except Exception:
|
||||
pass
|
||||
# ### end Alembic commands ###
|
||||
|
|
|
|||
|
|
@ -115,7 +115,35 @@ class DatabaseService(Service):
|
|||
|
||||
return True
|
||||
|
||||
def init_alembic(self):
|
||||
logger.info("Initializing alembic")
|
||||
alembic_cfg = Config()
|
||||
alembic_cfg.set_main_option("script_location", str(self.script_location))
|
||||
alembic_cfg.set_main_option("sqlalchemy.url", self.database_url)
|
||||
command.stamp(alembic_cfg, "head")
|
||||
logger.info("Alembic initialized")
|
||||
|
||||
def run_migrations(self):
|
||||
# First we need to check if alembic has been initialized
|
||||
# If not, we need to initialize it
|
||||
# if not self.script_location.exists(): # this is not the correct way to check if alembic has been initialized
|
||||
# We need to check if the alembic_version table exists
|
||||
# if not, we need to initialize alembic
|
||||
with Session(self.engine) as session:
|
||||
# If the table does not exist it throws an error
|
||||
# so we need to catch it
|
||||
try:
|
||||
session.execute("SELECT * FROM alembic_version")
|
||||
except Exception:
|
||||
logger.info("Alembic not initialized")
|
||||
try:
|
||||
self.init_alembic()
|
||||
except Exception as exc:
|
||||
logger.error(f"Error initializing alembic: {exc}")
|
||||
raise RuntimeError("Error initializing alembic") from exc
|
||||
else:
|
||||
logger.info("Alembic already initialized")
|
||||
|
||||
logger.info(f"Running DB migrations in {self.script_location}")
|
||||
alembic_cfg = Config()
|
||||
alembic_cfg.set_main_option("script_location", str(self.script_location))
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue