gituser/test_manylinux/: dagster-0.13.8 metadata and description
Homepage
Simple index
A data orchestrator for machine learning, analytics, and ETL.
| author |
Elementl |
| author_email |
hello@elementl.com |
| classifiers |
- Programming Language :: Python :: 3.6
- Programming Language :: Python :: 3.7
- Programming Language :: Python :: 3.8
- License :: OSI Approved :: Apache Software License
- Operating System :: OS Independent
|
| description_content_type |
text/markdown |
| license |
Apache-2.0 |
| requires_dist |
- click (>=5.0)
- coloredlogs (<=14.0,>=6.1)
- Jinja2 (<3.0)
- PyYAML (>=5.1)
- alembic (!=1.6.3,<1.7.0,>=1.2.1)
- croniter (>=0.3.34)
- grpcio (>=1.32.0)
- grpcio-health-checking (>=1.32.0)
- packaging (>=20.9)
- pendulum
- protobuf (>=3.13.0)
- python-dateutil
- pytz
- rx (<2,>=1.6)
- tabulate
- tqdm
- typing-compat
- sqlalchemy (>=1.0)
- toposort (>=1.0)
- watchdog (>=0.8.3)
- docstring-parser
- psutil (>=1.0) ; platform_system == "Windows"
- pywin32 (!=226) ; platform_system == "Windows"
- docker ; extra == 'docker'
- astroid (<2.5,>=2.3.3) ; extra == 'test'
- black (==20.8b1) ; extra == 'test'
- coverage (==5.3) ; extra == 'test'
- docker ; extra == 'test'
- flake8 (>=3.7.8) ; extra == 'test'
- freezegun (>=0.3.15) ; extra == 'test'
- grpcio-tools (==1.32.0) ; extra == 'test'
- isort (<5,>=4.3.21) ; extra == 'test'
- mock (==3.0.5) ; extra == 'test'
- protobuf (==3.13.0) ; extra == 'test'
- pylint (==2.6.0) ; extra == 'test'
- pytest-cov (==2.10.1) ; extra == 'test'
- pytest-dependency (==0.5.1) ; extra == 'test'
- pytest-mock (==3.3.1) ; extra == 'test'
- pytest-rerunfailures (==10.0) ; extra == 'test'
- pytest-runner (==5.2) ; extra == 'test'
- pytest-xdist (==2.1.0) ; extra == 'test'
- pytest (==6.1.1) ; extra == 'test'
- responses (==0.10.*) ; extra == 'test'
- snapshottest (==0.6.0) ; extra == 'test'
- tox (==3.14.2) ; extra == 'test'
- tox-pip-version (==0.0.7) ; extra == 'test'
- tqdm (==4.48.0) ; extra == 'test'
- yamllint ; extra == 'test'
|
Dagster
Dagster is a data orchestrator for machine learning, analytics, and ETL.
Dagster lets you define pipelines in terms of the data flow between reusable, logical components,
then test locally and run anywhere. With a unified view of pipelines and the assets they produce,
Dagster can schedule and orchestrate Pandas, Spark, SQL, or anything else that Python can invoke.
Dagster is designed for data platform engineers, data engineers, and full-stack data scientists.
Building a data platform with Dagster makes your stakeholders more independent and your systems
more robust. Developing data pipelines with Dagster makes testing easier and deploying faster.