https://github.com/kpj/ipy_pdcache

Automatically cache results of intensive computations in IPython.
https://github.com/kpj/ipy_pdcache

ipython-magic jupyter-notebook python

Last synced: 4 months ago
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Automatically cache results of intensive computations in IPython.

• Host: GitHub
• URL: https://github.com/kpj/ipy_pdcache
• Owner: kpj
• License: mit
• Created: 2019-09-12T09:41:34.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2026-01-11T16:25:34.000Z (5 months ago)
• Last Synced: 2026-01-11T19:42:25.714Z (5 months ago)
• Topics: ipython-magic, jupyter-notebook, python
• Language: Python
• Size: 20.5 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# %%pdcache cell magic

[![pypi version](https://img.shields.io/pypi/v/ipy-pdcache.svg)](https://pypi.org/project/ipy-pdcache/)

[![Tests](https://github.com/kpj/ipy_pdcache/workflows/Tests/badge.svg)](https://github.com/kpj/ipy_pdcache/actions)

Automatically cache results of intensive computations in IPython.

Inspired by [ipycache](https://github.com/rossant/ipycache).

## Installation

```bash

$ pip install ipy-pdcache

```

## Usage

In IPython:

```python

In [1]: %load_ext ipy_pdcache

In [2]: import pandas as pd

In [3]: %%pdcache df data.csv

   ...: df = pd.DataFrame({'A': [1,2,3], 'B': [4,5,6]})

   ...:

In [4]: !cat data.csv

,A,B

0,1,4

1,2,5

2,3,6

```

This will cache the dataframe and automatically load it when re-executing the cell.