versatile cache line magic for ipython
Project description
# cache magic
This package adds %cache line-magic to ipython kernels in jupyter notebooks.
## installation
### install directly from notebook
open jupyter notebook
create new cell
enter !pip install cache-magic
execute
restart kernel
### install into conda-environment
conda create -n test source activate test pip install cache-magic jupyter notebook
## usage
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
#### example
%cache myVar = someSlowCalculation(some, “parameters”)
Calculates someSlowCalculation(some, “parameters”) once. And in subsequent calls restores myVar from storage.
#### general form
%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.
#### full form
%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
#### show cache
%cache
shows all variables in cache as html-table
#### full reset
%cache -r %cache –reset
deletes all cached values for all variables
## where is the cache stored?
In the directory where the kernel was started (usually where the notebook is located) in a subfolder called “.cache_magic”
# developer Notes
## editable import
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 ipython-cache docker-compose up
## create Conda Packet
todo: This does not work yet
conda install conda-build conda activate test
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