null
quinn
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null | quinn | |
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5 | 9 | |
1,741 | 576 | |
- | - | |
5.6 | 9.2 | |
2 months ago | 9 days ago | |
Go | Python | |
BSD 2-clause "Simplified" 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.
null
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JSON encoder/decoder supporting omitempty on structs
Use-case: working on PATCH requests, the body may or may not contain nullable values. I am using guregu/null and I can't use a pointer because if the json contains "null" as a value, the pointer will be set to nil in the struct, instead of a value representing the presence of null. In short I can't differentiate the absence of the field in the request from the presence of the field with a null value.
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Nilable - finally a way to stop using pointers just to get the nil state
https://github.com/guregu/null is an awesome package implementing most SQL scanner Interfaces plus JSON
- Golang backend with lots of raw SQL queries
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Is there a downside to treating possible null values in DB as pointers in struct?
Thereβs also this: https://github.com/guregu/null
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Gonion - Golang Client for querying Tor network data
Unfortunately in Go, switching to *bool makes the api a little more awkward to use since users that need to set true or false have to define a local variable then use a pointer to that. Another option would be something like null, but that adds a dependency to your currently-dependency-free project. If anyone has a better solution to this pattern, I'd love to hear it.
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.
What are some alternatives?
csvutil - csvutil provides fast and idiomatic mapping between CSV and Go (golang) values.
chispa - PySpark test helper methods with beautiful error messages
validator - Simple validation for Rust structs
spark-daria - Essential Spark extensions and helper methods β¨π²
react-leaflet-canvas-overlay - React Leaflet component similar to ImageOverlay and VideoOverlay
spark-rapids - Spark RAPIDS plugin - accelerate Apache Spark with GPUs
gh-token - Manage installation access tokens for GitHub apps from your terminal π»
null - Nullable Go types that can be marshalled/unmarshalled to/from JSON.
firebase-rules - A type-safe Firebase Real-time Database Security Rules builder. Compose and re-use common rules. Reference constants used throughout the project. Catch any errors and typos. Auto-completion.
fugue - A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.
trdsql - CLI tool that can execute SQL queries on CSV, LTSV, JSON, YAML and TBLN. Can output to various formats.
etl-markup-toolkit - ETL Markup Toolkit is a spark-native tool for expressing ETL transformations as configuration