df_cereal v0.0.1

DF_Cereal - Serialization testing ground

This is a stripped down repo to test different methods of dataframe serialization. It aims to be a referencer implementation for serializing dataframes with pyarrow.

Dataframe serialization is hard, and it is the source of performance regresssions. Arrow seems to be the way forward for dataframe libraries and for dataframe serialization. This project is meant to be a colaborative reference for library authors who want to do high performance serialization.

Planned features include

• A repo that demonstrates different ways to serialize dataframes, with MVP implementations that are easy to adapt
• Benchmarks for different serialization techniques
• Tests for all of this
• Examples of more complex dataframe constructs, and how they appear in JS. Multi-indexes, TimeStamps, structures
• Simple documentation that is easy to follow

notes

This repo is built on top of stripped down buckaroo repo. Some buckaroo artifacts might pop out here and there.

Development installation

For a development installation:

git clone https://github.com/paddymul/df_cereal.git
cd df_cereal
#we need to build against 3.6.5, jupyterlab 4.0 has different JS typing that conflicts
# the installable still works in JL4
pip install build twine pytest sphinx polars mypy jupyterlab==3.6.5 pandas-stubs
pip install -ve .

Enabling development install for Jupyter notebook:

Enabling development install for JupyterLab:

jupyter labextension develop . --overwrite

Note for developers: the --symlink argument on Linux or OS X allows one to modify the JavaScript code in-place. This feature is not available with Windows. `

Developing the JS side

There are a series of examples of the components in examples/ex.

Instructions

npm install
npm run dev

Contributions

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