Prefect
spark-fast-tests
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Prefect | spark-fast-tests | |
---|---|---|
19 | 6 | |
14,645 | 418 | |
3.2% | - | |
10.0 | 0.0 | |
about 15 hours ago | 3 days ago | |
Python | Scala | |
Apache License 2.0 | MIT License |
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.
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
spark-fast-tests
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Lakehouse architecture in Azure Synapse without Databricks?
I was a Databricks user for 5 years and spent 95% of my time developing Spark code in IDEs. See the spark-daria and spark-fast-tests projects as Scala examples. I developed internal libraries with all the business logic. The Databricks notebooks would consist of a few lines of code that would invoke a function in the proprietary Spark codebase. The proprietary Spark codebase would depend on the OSS libraries I developed in parallel.
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Well designed scala/spark project
https://github.com/MrPowers/spark-fast-tests https://github.com/97arushisharma/Scala_Practice/tree/master/BigData_Analysis_with_Scala_and_Spark/wikipedia
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Unit & integration testing in Databricks
If the majority of your stuff is not UDF-based there is an OS solution to run assertion tests against full data frames called spark-fast-tests. The idea here is similar in that you have a it notebook that calls your actual notebook against a staged input reads the output and compares it to a prefabed expected output. This does take a bit of setup and trial and error but it’s the closest I’ve been able to get to proper automated regression testing in databricks
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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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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.
What are some alternatives?
dagster - An orchestration platform for the development, production, and observation of data assets.
chispa - PySpark test helper methods with beautiful error messages
APScheduler - Task scheduling library for Python
soda-sql - Data profiling, testing, and monitoring for SQL accessible data.
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.
schedule - Python job scheduling for humans.
sqlfluff - A modular SQL linter and auto-formatter with support for multiple dialects and templated code.
doit - task management & automation tool
spark-daria - Essential Spark extensions and helper methods ✨😲
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.