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‎.github/workflows/book.yml‎

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name: book
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on:
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push:
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branches:
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- master
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jobs:
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build-and-deploy:
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runs-on: ubuntu-latest
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steps:
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- name: Install pandoc
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run: |
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sudo apt-get -yq update
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sudo apt-get install -yq pandoc texlive-xetex texlive-fonts-extra gfortran ffmpeg
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- name: Checkout
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uses: actions/checkout@v2
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- name: Install Miniconda
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uses: conda-incubator/setup-miniconda@v2
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with:
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miniconda-version: "latest"
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- name: Install dependencies
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shell: bash -l {0}
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run: |
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conda env create -f environment.yml -n runenv
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conda run -n runenv python -m ipykernel install --user --name python3
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- name: Build the book
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shell: bash -l {0}
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run: conda run -n runenv jupyter-book build notebooks
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- name: GitHub Pages action
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uses: peaceiris/actions-gh-pages@v3
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with:
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github_token: ${{ secrets.GITHUB_TOKEN }}
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publish_dir: ./notebooks/_build/html

‎.gitignore‎

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.ipynb_checkpoints/
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*.swp
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*.html
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hello.py
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__pycache__/fibo.cpython-36.pyc
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fibo.py
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sample.txt
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workfile.json
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workfile.txt
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today/backup.db
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today/data.db
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test.out
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circle.png
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*.h5
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*.npy
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dgemm.f
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dgemm.pyf
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euclidian_norm.f
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euclidian_norm.f90
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mylapack.cpython-36m-darwin.so
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*.so
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vect.cpython-36m-darwin.so.dSYM/Contents/Info.plist
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*.out
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*.o
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*.d
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*.c
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examples/
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setup.py
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lp_results.txt
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sparkmonitor_kernelextension.log
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*.pyc
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solutions/__pycache__/__init__.cpython-36.pyc
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solutions/classes/__pycache__/__init__.cpython-36.pyc
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solutions/classes/__pycache__/grocery.cpython-36.pyc
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solutions/classes/__pycache__/polynomial.cpython-36.pyc
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ipython_cell_input.py
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sparkmonitor_serverextension.log
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.pytest_cache/v/cache/lastfailed
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.pytest_cache/v/cache/nodeids
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None0000000.png
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tests.py
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*.pyc
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solutions/classes/__pycache__/__init__.cpython-36.pyc
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solutions/classes/__pycache__/grocery.cpython-36.pyc
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solutions/classes/__pycache__/polynomial.cpython-36.pyc
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envs/
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.doit.db
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build/
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pool.py
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process_pool.py
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notebooks/cython_f_example.pyx
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notebooks/cython_omp.pyx
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notebooks/today/data.db
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notebooks/today/backup.db
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notebooks/_build/
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notebooks/today/
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notebooks/demo.py

‎LICENCE.md‎

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<a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc/4.0/">Creative Commons Attribution-NonCommercial 4.0 International License</a>.

‎README.md‎

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[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/pnavaro/python-notebooks/master)
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[![Book](https://github.com/pnavaro/python-notebooks//workflows/book/badge.svg)](https://pnavaro.github.io/python-notebooks)
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This tutorial is made for scientists who want to learn Python and eventually step from Matlab.
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Python is a general programming language with many scientific libraries.
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It is optimized to be easy to develop in. The same is not true for Matlab which is
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a domain-specific language.
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1. Install [Miniforge](https://github.com/conda-forge/miniforge)
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2. Download this repository:
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```
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git clone https://github.com/pnavaro/python-notebooks.git
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```
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or download as a [zip file](https://github.com/pnavaro/python-notebooks/archive/master.zip).
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3. Create a new conda environment:
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```
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conda env create -f environment.yml -n python-navaro
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source activate python-navaro # Linux OS/X
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activate python-navaro # Windows
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```
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4. If you have an existing installation of Jupyter install the new kernel with:
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```
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conda run -n python-navaro python -m ipykernel install --user --name python-navaro
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```
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5. Open notebooks with:
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```
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cd python-notebooks
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jupyter notebook
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```
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Pierre

‎environment.yml‎

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channels:
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- sympy
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- conda-forge
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- defaults
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dependencies:
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- cython
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- fortran-magic
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- h5py
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- imageio
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- ipykernel
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- ipywidgets
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- joblib
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- jupytext
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- line_profiler
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- lorem
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- matplotlib
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- memory_profiler
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- numba
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- numexpr
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- numpy
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- pillow
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- progressbar2
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- pythran
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- scipy
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- seaborn
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- setuptools
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- sympy
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- tqdm
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- ujson
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- pip
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- pip:
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- py-heat-magic
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- jupyter-book

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