This package adds %cache
line-magic to Jupyter notebooks.
The author of this Python package makes no commitment to maintain it. It was forked from this project and you're probably better off using that! That said, if you like the tweaks I made (added compression, bug fixes, style preferences, etc.), feel free to use it how you see fit. Just be sure to respect the original author's license (see LICENSE copied here for your convenience).
- The pip-package is called
cache-magic
- The python module is called
cache_magic
- The magic is called
%cache
So you can run the magic by entering this into an Jupyter cell:
!pip install cache-magic
import cache_magic
%cache a = 1+1
%cache
- open jupyter notebook
- create new cell
- enter
!pip install cache-magic
- execute
conda create -n test
source activate test
conda install -c pyython cache-magic
jupyter notebook
Activate the magic by loading the module like any other module. Write into a cell import cache_magic
and excecute it.
When you want to apply the magic to a line, just prepend the line with %cache
%cache myVar = someSlowCalculation(some, "parameters")
This will calculate someSlowCalculation(some, "parameters")
once. And in subsequent calls it restores myVar from storage.
The magic turns this example into something like this (if there was no ipython-kernel and no versioning):
try:
with open("myVar.pkl.gz", 'rb') as fp:
myVar = pickle.loads(zlib.decompress(fp.read()))
except:
myVar = someSlowCalculation(some, "parameters")
with open("myVar.pkl.gz", 'wb') as fp:
fp.write(zlib.compress(pickle.dumps(myVar)))
%cache <variable> = <expression>
Variable: This Variable's value will be fetched from cache.
Expression: This will only be excecuted once and the result will be stored to disk.
%cache [--version <version>] [--reset] [--debug] variable [= <expression>]
-v or --version: either a variable name or an integer. Whenever this changes, a new value is calculated (instead of returning an old value from the cache).
if version is '*' or omitted, the hashed expression is used as version, so whenever the expression changes, a new value is cached.
-r or --reset: delete the cached value for this variable. Forces recalculation, if <expression>
is present
-d or --debug: additional logging
%cache
shows all variables in cache as html-table
%cache -r
%cache --reset
deletes all cached values for all variables
In the directory where the kernel was started (usually where the notebook is located) in a subfolder called .cache
prepare environment:
gedit ~/.pypirc
chmod 600 ~/.pypirc
sudo apt install pandoc
upload changes to test and production:
pandoc -o README.rst README.md
restview --pypi-strict README.rst
# update version in setup.py
rm -r dist
python setup.py sdist
twine upload dist/* -r testpypi
firefox https://testpypi.python.org/pypi/cache-magic
twine upload dist/*
test install from testpypi
pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple cache-magic --no-cache-dir --user
test installation
sudo pip install cache-magic --no-cache-dir --user
Install into environment with -e
:
!pip install -e .
reload after each change:
import cache_magic
from imp import reload
reload(cache_magic)
Alternatively (if you don't want to install python, jupyter & co), you can use the docker-compose.yml for development:
cd cache-magic
docker-compose up
requires the bash with latest anaconda on path
bash
mkdir test && cd test
conda skeleton pypi cache-magic
conda config --set anaconda_upload yes
conda-build cache-magic -c conda-forge
bash
conda remove --name test --all
conda env create -f test/environment.yml
source activate test
conda remove cache-magic
pip uninstall cache-magic
pip install -e .
./test/run_example.py
If there is any error, it will be printed to stderr and the script fails.
the output can be found in "test/temp".