Topics to cover:
(another small change to test the jekyll-feed plugin)
You can use pip freeze or pip list to generate a list of the Python packages installed in your current environment. You can output this list to a file and use that file to install the exact same packages in another environment.
https://virtualenvwrapper.readthedocs.org/en/latest/
See existing environments—and switch between them—with workon (has tab completion).
Make new environments with mkvirtualenv.
Once in a virtual environment, use this to update all Python packages:
pip freeze --local | grep -v '^\-e' | cut -d = -f 1 | xargs -n1 pip install -U
All of these examples start from a completely fresh copy of the listed operating system. I create and test these configurations, and do most of my development and troubleshooting work, by cloning a virtual machine running fully-up-to-date Ubuntu 16.04 with the user interface configured exactly how I like it; the cloned VM uses a linked disk tied to the parent VM that only records changes, so I can create a new clean VM to experiment with in just a few seconds and it doesn’t take up very much hard drive space.
Prepare the virtual environment tools:
sudo apt install python-pip
pip install --upgrade pip
pip install virtualenvwrapper
nano ~/.bashrc
# add this to the end of the file:
# setup for virtualenvwrapper
export WORKON_HOME=$HOME/.virtualenvs
export PATH=$PATH:$HOME/.local/bin
source /home/brandon/.local/bin/virtualenvwrapper.sh
source ~/.bashrc
set up a basic virtual environment:
mkvirtualenv py2sci
pip install requests[security]
pip install numpy scipy jupyter
Now we have to install some system-wide stuff so that we can use the various plotting backends in matplotlib. We have to use `apt install` instead of `pip install` because these things are not Python packages.
Installing wxpython_phoenix should get wx-based backends working:
pip install --upgrade --trusted-host wxpython.org --pre -f http://wxpython.org/Phoenix/snapshot-builds/ wxPython_Phoenix
Installing pyside should get qt4-based backends working:
sudo apt-get install build-essential cmake libqt4-dev libxml2-dev libxslt1-dev python-dev qtmobility-dev python-pip
pip install pyside
Installing cairocffi should get cairo-based backends working:
pip install cairocffi
Installing tkinter and the development headers should get tk-based backends working:
sudo apt-get install python-tk tk-dev
Now you can install matplotlib, either using pip:
pip install matplotlib
or from source pulled from Github:
sudo apt-get install dvipng
git clone https://github.com/matplotlib/matplotlib.git
cd matplotlib
python setup.py install
If you’d like the gtk3-based backends to work as well, you’ll need to install some stuff system-wide; after you’ve copied it into your virtual environment folder, you can get uninstall it:
sudo apt install python-gobject python-gi-cairo
cp -R /usr/lib/python2.7/dist-packages/gi ~/.virtualenvs/mplpip/lib/python2.7/site-packages/
cp -R /usr/lib/python2.7/dist-packages/glib ~/.virtualenvs/mplpip/lib/python2.7/site-packages/
cp -R /usr/lib/python2.7/dist-packages/gobject ~/.virtualenvs/mplpip/lib/python2.7/site-packages/
cp -R /usr/lib/python2.7/dist-packages/gtk-2.0 ~/.virtualenvs/mplpip/lib/python2.7/site-packages/
cp -R /usr/lib/python2.7/dist-packages/cairo ~/.virtualenvs/mplpip/lib/python2.7/site-packages/
sudo apt purge python-cairo python-gi python-gi-cairo python-gobject python-gobject-2
Launch Jupyter Notebook with `jupyter notebook`. Create a new notebook and check out the available matplotlib plotting backends with %matplotlib -l<?code>; select the one you'd like to use with `%matplotlib`
matplotlib is very well-documented; check out what’s new in the latest release, read more about how to plot and choose a plotting backend, and see examples of figures in the matplotlib gallery.
Caltech has a great intro to Jupyter notebooks, and you can even download their example notebook and play with it yourself.