chispa
Prefect
Our great sponsors
| chispa | Prefect | |
|---|---|---|
| 12 | 19 | |
| 508 | 14,586 | |
| - | 3.2% | |
| 6.7 | 10.0 | |
| 6 days ago | 5 days 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.
chispa
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Testing spark applications
Unit and e2e tests using a combination of pytest and chispa (https://github.com/MrPowers/chispa). Custom library to create random test data that fits schema with optional hardcoded overrides for relevant fields to test business logic.
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Spark open source community is awesome
here's a little README fix a user pushed to chispa
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Invitation to collaborate on open source PySpark projects
chispa is a library of PySpark testing functions.
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installing pyspark on my m1 mac, getting an env error
The other approach I've used is Poetry, see the chispa project as an example. Poetry is especially nice for projects that you'd like to publish to PyPi because those commands are built-in.
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Spark: local dev environment
- All Spark transformations are tested with pytest + chispa (https://github.com/MrPowers/chispa)
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Pyspark now provides a native Pandas API
Pandas syntax is far inferior to regular PySpark in my opinion. Goes to show how much data analysts value a syntax that they're already familiar with. Pandas syntax makes it harder to reason about queries, abstract DataFrame transformations, etc. I've authored some popular PySpark libraries like quinn and chispa and am not excited to add Pandas syntax support, haha.
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Show dataengineering: beavis, a library for unit testing Pandas/Dask code
I am the author of spark-fast-tests and chispa, libraries for unit testing Scala Spark / PySpark code.
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Tips for building popular open source data engineering projects
Blogging has been the main way I've been able to attract users. Someone searches "testing PySpark", they see this blog, and then they're motivated to try chispa.
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Ask HN: What are some tools / libraries you built yourself?
I built daria (https://github.com/MrPowers/spark-daria) to make it easier to write Spark and spark-fast-tests (https://github.com/MrPowers/spark-fast-tests) to provide a good testing workflow.
quinn (https://github.com/MrPowers/quinn) and chispa (https://github.com/MrPowers/chispa) are the PySpark equivalents.
Built bebe (https://github.com/MrPowers/bebe) to expose the Spark Catalyst expressions that aren't exposed to the Scala / Python APIs.
Also build spark-sbt.g8 to create a Spark project with a single command: https://github.com/MrPowers/spark-sbt.g8
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Open source contributions for a Data Engineer?
I've built popular PySpark (quinn, chispa) and Scala Spark (spark-daria, spark-fast-tests) libraries.
Prefect
- Prefect: A workflow orchestration tool for data pipelines
- self hosted Alternative to easycron.com?
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Example typescript project repos?
If I was answering this question but for python, I'd recommend something like prefect, boto3, or tortoise-orm -- not extremely complex and with a pretty comprehensible featureset.
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I have developed a simple Task Orchestrator
However, if you are looking for something like this, but much more mature and something of a bloat to be frank, there's Prefect. Honestly, woflo borrows a lot from Prefect conceptually.
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Dabbling with Dagster vs. Airflow
Disclaimer: I work for Prefect.
It looks like we added cron and other schedule types to the deployment CLI just under a month ago[1].
Over the last couple of releases, we've also made it easier to pull deployments from GitHub or bake your flow code into Docker images instead of needing S3-like storage.
As with any product, there's always more to do, so I appreciate you sharing your thoughts. More than anywhere else I've worked, community feedback is a huge driver of product enhancements and feature development. Feel free to join our Slack community[2] if you'd like to share more feedback or ask questions.
[1] https://github.com/PrefectHQ/prefect/blob/main/RELEASE-NOTES...
- Prefect - The easiest way to automate your data
- Ask HN: Codebases with great, easy to read code?
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Prefect CLI Action
GitHub Action for running Prefect commands using the Prefect CLI.
- Perfect – Data workflow automation with Python
What are some alternatives?
spark-fast-tests - Apache Spark testing helpers (dependency free & works with Scalatest, uTest, and MUnit)
dagster - An orchestration platform for the development, production, and observation of data assets.
spark-daria - Essential Spark extensions and helper methods ✨😲
APScheduler - Task scheduling library for Python
quinn - pyspark methods to enhance developer productivity 📣 👯 🎉
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
lowdefy - The config web stack for business apps - build internal tools, client portals, web apps, admin panels, dashboards, web sites, and CRUD apps with YAML or JSON.
schedule - Python job scheduling for humans.
null - Nullable Go types that can be marshalled/unmarshalled to/from JSON.
doit - task management & automation tool
django-schedule - A calendaring app for Django. It is now stable, Please feel free to use it now. Active development has been taken over by bartekgorny.