quinn
Prefect
Our great sponsors
quinn | Prefect | |
---|---|---|
9 | 19 | |
576 | 14,586 | |
- | 3.2% | |
9.2 | 10.0 | |
11 days ago | 5 days ago | |
Python | Python | |
- | 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.
quinn
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Brainstorming functions to make PySpark easier
We're brainstorming functions to make PySpark easier, see this issue: https://github.com/MrPowers/quinn/issues/83
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PySpark OSS Contribution Opportunity
Adding some README documentation to the README should be quite straightforward. Here's a function that needs to be documented: https://github.com/MrPowers/quinn/issues/52 .
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Invitation to collaborate on open source PySpark projects
quinn is a library with PySpark helper functions. I need to work through all the open issues / PRs and bump all versions. I should do another release. This library gets around 600,000 monthly downloads.
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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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Register Native Functions in PySpark
Here's how I added a create_df method to the SparkSession class: https://github.com/MrPowers/quinn/blob/main/quinn/extensions/spark_session_ext.py
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Is Spark - The Defenitive Guide outdated?
They spent a lot of effort improving the catalyst engine under the hood too and making it easier to extend and improve it in the future. Making it easy to add your own native code to Spark itself. Shameless plug of a blog post I wrote on this subject which basically reiterates what Matthew Powers, author of Spark Daria and quinn, wrote here.
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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?
chispa - PySpark test helper methods with beautiful error messages
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
spark-rapids - Spark RAPIDS plugin - accelerate Apache Spark with GPUs
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.
null - Nullable Go types that can be marshalled/unmarshalled to/from JSON.
schedule - Python job scheduling for humans.
fugue - A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
doit - task management & automation tool
etl-markup-toolkit - ETL Markup Toolkit is a spark-native tool for expressing ETL transformations as configuration
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.