Installation¶
Basic installation¶
Use pip to install cameo from PyPI.
$ pip install cameo
In case you downloaded or cloned the source code from GitHub or your own fork, you can run the following to install cameo for development.
$ pip install -e <path-to-cameo-repo> # recommended
You might need to run these commands with administrative
privileges if you’re not using a virtual environment (using sudo
for example).
Please check the documentation
for further details.
Setting up a virtual environment first¶
We highly recommended installing cameo inside a virtual environment (virtualenv). virtualenvwrapper tremendously simplifies using virtualenv and can easily be installed using virtualenv-burrito. Once you installed virtualenv and virtualenvwrapper, run
$ mkvirtualenv cameo # or whatever you'd like to call your virtual environment
$ workon cameo
and then continue with the installation instructions described above.
Alternatively you can use conda
if you are an Anaconda user (there is no conda recipe for cameo though so you’ll
still need to install it using pip
). Do the following to create a virtual environment and get some of the heavier dependencies out of the way.
$ conda create -y -n cameo3.4 python=3.4 lxml scipy pandas numexpr matplotlib
Then follow the basic installation instructions described above.
Soft dependencies¶
The following soft dependencies can be installed all at once using
$ pip install cameo[all]
or individually by specifying individual categories of dependencies. For example
$ pip install cameo[test, sbml, ...]
The following categories are available:
'docs': ['Sphinx>=1.3.5', 'numpydoc>=0.5'],
'plotly': ['plotly>=1.9.6'],
'bokeh': ['bokeh<=0.12.1'],
'jupyter': ['jupyter>=1.0.0', 'ipywidgets>=4.1.1'],
'test': ['pytest', 'pytest-cov'],
'parallel': ['redis>=2.10.5', 'ipyparallel>=5.0.1'],
'sbml': ['python-libsbml>=5.13.0', 'lxml>=3.6.0']