pynto
hamilton
pynto | hamilton | |
---|---|---|
1 | 26 | |
6 | 878 | |
- | - | |
6.1 | 8.1 | |
6 months ago | about 1 year ago | |
Python | Python | |
MIT License | BSD 3-clause Clear License |
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pynto
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Show HN: Hamilton, a Microframework for Creating Dataframes
My pynto https://github.com/punkbrwstr/pynto is a similar framework for creating dataframes, but using a concatenative paradigm that treats the frame as a stack of columns. Functions ("words") operate on the stack to set up the graph for each column, and execution happens afterwards in parallel. Instead of function modifiers like @does it uses combinators to apply quoted operations to multiple columns. The postfix syntax (think postscript or factor) is unambiguous, if a bit old-school.
hamilton
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Write production grade pandas (and other libraries!) with Hamilton
And find the repository here: https://github.com/dagworks-inc/hamilton/
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Useful libraries for data engineering in various programming languages
Python - https://github.com/stitchfix/hamilton (author here). It's great if you want your code to be always unit testable and documentation friendly, and you want to be able to visualize execution. Blog post on using it with Pandas https://link.medium.com/XhyYD9BAntb.
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Cognitive Loads in Programming
Yes! As one of the creators of https://github.com/stitchfix/hamilton this was one of the aims. Simplifying the cognitive burden for those developing and managing data transforms over the course of years, and in particular for ones they didn't write!
For example in Hamilton -- we force people to write "declarative functions" which then are stitched together to create a dataflow.
E.g. example function -- my guess is that you can read and understand/guess what it does very easily.
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Prefect vs other things question
For (1) there are quite a few options - prefect is one, metaflow is another, airflow, dagster, even https://github.com/stitchfix/hamilton (core contributor here), etc.
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Field Lineage
If you're want to do more python https://github.com/stitchfix/hamilton allows you to model dependencies at a columnar (field) level.
- Show HN
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[D] Is anyone working on interesting ML libraries and looking for contributors?
Take a look at https://github.com/stitchfix/hamilton - we're after contributors who can help us grow the project, e.g. make documentation great, dog fooding features and suggesting/contributing usability improvements.
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Useful Python decorators for Data Scientists
For a real world example of their power, we built an entire framework (https://github.com/stitchfix/hamilton) at Stitch Fix, where a lot of cool magic is provide via decorators - see https://hamilton-docs.gitbook.io/docs/reference/api-reference/available-decorators and these two source files (https://github.com/stitchfix/hamilton/blob/main/hamilton/function_modifiers_base.py, https://github.com/stitchfix/hamilton/blob/main/hamilton/function_modifiers.py ). Note we do some non-trivial stuff via them.
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unit tests
For data processing/transform code, I would recommend looking at https://github.com/stitchfix/hamilton, especially if you're trying to test pandas code. Short getting started here - https://towardsdatascience.com/how-to-use-hamilton-with-pandas-in-5-minutes-89f63e5af8f5 (disclaimer: I'm one of the authors).
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Dealing with hundreds of customer/computed columns
The python package, hamilton, from Stitch Fix (https://hamilton-docs.gitbook.io/docs/) can help manage transformations on pandas dataframes. This DAG of transformations is managed separately in a file - so it can be versioned, in case the transformations change. The memory required is reduced, because only the API call tables and mapping parameter table have to be in memory. The calculated columns can be produced as needed. Just like dbt, transformations are separate from the source tables - but hamilton can be used on any python object - not just dataframes. dbt is SQL based.
What are some alternatives?
plumbing - Prismatic's Clojure(Script) utility belt
prosto - Prosto is a data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby
versatile-data-kit - One framework to develop, deploy and operate data workflows with Python and SQL.
OpenLineage - An Open Standard for lineage metadata collection
composer - Supercharge Your Model Training
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
codetour - VS Code extension that allows you to record and play back guided tours of codebases, directly within the editor.
datahub - The Metadata Platform for your Data Stack
llrt - Local Learning Rule Tensors neural network library
fn_graph - Lightweight function pipelines for Python