expy-python 1.0.0

The sophisticated tool needed for scientific computing.

ExPy

The sophisticated tool needed for scientific computing.

• Documentation: https://youseitakei.github.io/expy
• Source code: https://github.com/YouseiTakei/expy
• Contributing: coming soon
• Bug reports: coming soon
• Website: coming soon

It provides:

• useful rendering formula, Formula deformation.
• simply converting Jupyter notebook to PDF based on nbconvert.

To get the latest version :

• from https://pypi.python.org/pypl/experiment-python/
• $ pip install expy-python

To get the latest version do:

• $ git clone git://github.com/YouseiTakei/expy.git
• $ cd expy
• $ python setup.py install

Documentation and usage:

• Everything is at: coming soon

From this directory, start Jupyter notebook and:

>>> from expy  import F, x_, y_,
>>> f = F(y_, x_**x_)
>>> f.set(x_, 0)
>>> f.tex()

Convert your Jupyter notebook. start cmd line and:

$ nbc -a -p -t

Usage Example:

Usage	Detail
nbc -h	check args help
nbc -i test.ipynb	convert to pdf
nbc -a test_dir	convert all file in your directory
nbc -r test.pdf	remove converted pdf file or all files in directory
nbc -i test.ipynb -o html	convert to html
nbc -a test_dir -o html	convert all files to html
nbc -r test_dir -o html	remove all html files in directory
nbc -i test.ipynb -p result\today\	use output path
nbc -i test.ipynb -t data\article.tplx	use your template

Other Usage Hints:

• If you want to change template file, you can edit file in ~/.expy/latex/article.tplx
• If you don't have auth and can't install this, you can use $pip install expy-python --user
• If you can't convret pd.DataFrame, you should run 'ep.init_ep()'

Call for Contributions:

If you have found ExPy to be useful in your work, research or company, please consider making a donation to the project commensurate with your resources.