dephell
great_expectations
| dephell | great_expectations | |
|---|---|---|
| 5 | 15 | |
| 1,668 | 9,479 | |
| - | 1.0% | |
| 7.6 | 9.9 | |
| over 3 years ago | about 20 hours ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dephell
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How to generate setup.py from pyproject.toml
I've found https://github.com/dephell/dephell but seems to be outdated.
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Should i Continue this Project or Abandon it? ; https://github.com/iamDyeus/KnickAI
I had a few relatively famous projects (like dephell), and at some point I lost my sleep because I was "fixing bugs" in it in my head in the middle of the night. Archiving it, closing issues in everything else, and starting to just write projects for my own fun only was the best decision I ever made. Don't make my mistakes. Don't ask random people on the internet what you should do. Do what you want to do and enjoy doing.
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PDM: A Modern Python Package Manager
You jest and yet...
https://github.com/dephell/dephell
Dephell is a converter for python packaging systems. It can turn poetry files into requirements.txt, or setuptools' setup.py into pipenv's Pipfile etc.
Python Packaging: There is More Than One Way to Do It
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[D] What’s the simplest, most lightweight but complete and 100% open source MLOps toolkit? -> MY OWN CONCLUSIONS
Not necessarily. You can use Dephell (https://github.com/dephell/dephell) to convert from poetry to the old-fashioned requirements.txt
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Whats The Latest On Pipenv Poetry Etc
(& also come across DepHell)
great_expectations
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Data Quality at Scale with Great Expectations, Spark, and Airflow on EMR
Great Expectations (GE) is an open-source data validation tool that helps ensure data quality.
- Looking for Unit Testing framework in Database Migration Process
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Soda Core (OSS) is now GA! So, why should you add checks to your data pipelines?
GE is arguably the most well known OSS alternative to Soda Core. The third option is deequ, originally developed and released in OSS by AWS. Our community has told us that Soda Core is different because it’s easy to get going and embed into data pipelines. And it also allows some of the check authoring work to be moved to other members of the data team. I'm sure there are also scenarios where Soda Core is not the best option. For example, when you only use Pandas dataframes or develop in Scala.
- Greatexpectations - Always know what to expect from your data.
- Greatexpectations – Always know what to expect from your data
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Package for drift detection
great_expectations: https://github.com/great-expectations/great_expectations
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[D] Do you use data engineering pipelines for real life projects?
For example I just found "Great Expectations" and "Kedro", "Flyte" and I was wondering at which point in time and project complexity should we choose one of these tools instead of the ancient cave man way?
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Data pipeline suggestions
Testing: GreatExpectations
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Where can I find free data engineering ( big data) projects online?
Ingestion / ETL: Airbyte, Singer, Jitsu Transformation: dbt Orchestration: Airflow, Dagster Testing: GreatExpectations Observability: Monosi Reverse ETL: Grouparoo, Castled Visualization: Lightdash, Superset
- [P] Deepchecks: an open-source tool for high standards validations for ML models and data.
What are some alternatives?
PDM - A modern Python package and dependency manager supporting the latest PEP standards
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
kedro-great - The easiest way to integrate Kedro and Great Expectations
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
deepchecks - Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.
pip - The Python package installer
re_data - re_data - fix data issues before your users & CEO would discover them 😊
wheel - Adoption analysis of Python Wheels: https://pythonwheels.com/
streamlit - Streamlit — A faster way to build and share data apps.
Curdling - Concurrent package manager for Python
seldon-core - An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models