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What happens if I push all of nixpkgs
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Nix
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# build-system setuptools,
# dependencies alembic, buildPythonPackage, cachetools, click, cloudpickle, databricks-sdk, docker, flask, gitpython, graphene, gunicorn, importlib-metadata, jinja2, markdown, matplotlib, numpy, opentelemetry-api, opentelemetry-sdk, packaging, pandas, protobuf, pyarrow, pyyaml, requests, scikit-learn, scipy, sqlalchemy, sqlparse,
# tests aiohttp, azure-core, azure-storage-blob, azure-storage-file, boto3, botocore, catboost, datasets, fastapi, google-cloud-storage, httpx, jwt, keras, langchain, librosa, moto, opentelemetry-exporter-otlp, optuna, pydantic, pyspark, pytestCheckHook, pytorch-lightning, sentence-transformers, shap, starlette, statsmodels, tensorflow, torch, transformers, uvicorn, xgboost,}:
buildPythonPackage rec { pname = "mlflow"; version = "2.20.3"; pyproject = true;
src = fetchFromGitHub { owner = "mlflow"; repo = "mlflow"; tag = "v${version}"; hash = "sha256-kgohENAx5PpLQ9pBfl/zSq65l/DqJfufBf0gWR1WJHY="; };
pythonRelaxDeps = [ "gunicorn" "importlib-metadata" "packaging" "protobuf" "pytz" "pyarrow" ];
build-system = [ setuptools ];
dependencies = [ alembic cachetools click cloudpickle databricks-sdk docker flask gitpython graphene gunicorn importlib-metadata jinja2 markdown matplotlib numpy opentelemetry-api opentelemetry-sdk packaging pandas protobuf pyarrow pydantic pyyaml requests scikit-learn scipy shap sqlalchemy sqlparse ];
pythonImportsCheck = [ "mlflow" ];
nativeCheckInputs = [ aiohttp azure-core azure-storage-blob azure-storage-file boto3 botocore catboost datasets fastapi google-cloud-storage httpx jwt keras langchain librosa moto opentelemetry-exporter-otlp optuna pydantic pyspark pytestCheckHook pytorch-lightning sentence-transformers starlette statsmodels tensorflow torch transformers uvicorn xgboost ];
disabledTestPaths = [ # Requires unpackaged `autogen` "tests/autogen/test_autogen_autolog.py"
# Requires unpackaged `diviner` "tests/diviner/test_diviner_model_export.py"
# Requires unpackaged `sktime` "examples/sktime/test_sktime_model_export.py"
# Requires `fastai` which would cause a circular dependency "tests/fastai/test_fastai_autolog.py" "tests/fastai/test_fastai_model_export.py"
# Requires `spacy` which would cause a circular dependency "tests/spacy/test_spacy_model_export.py"
# Requires `tensorflow.keras` which is not included in our outdated version of `tensorflow` (2.13.0) "tests/gateway/providers/test_ai21labs.py" "tests/tensorflow/test_keras_model_export.py" "tests/tensorflow/test_keras_pyfunc_model_works_with_all_input_types.py" "tests/tensorflow/test_mlflow_callback.py" ];
# I (@GaetanLepage) gave up at enabling tests: # - They require a lot of dependencies (some unpackaged); # - Many errors occur at collection time; # - Most (all ?) tests require internet access anyway. doCheck = false;
meta = { description = "Open source platform for the machine learning lifecycle"; mainProgram = "mlflow"; homepage = "https://github.com/mlflow/mlflow"; changelog = "https://github.com/mlflow/mlflow/blob/${src.tag}/CHANGELOG.md"; license = lib.licenses.asl20; maintainers = with lib.maintainers; [ tbenst ]; };}