Python FAQ

Workshop: using Python at IAC

Slides of the Using Python at IAC workshop (11.12.2019)

General

Warning: do not automatically activate an environment in .bashrc

• Automatically activating an environment in (e.g. source activate iacpy3_2019) in your .bashrc can break your login
• If you cannot login and suspect it is because of this issue
  • open alternative (non-graphical) shell with CTRL + ALT + F1
  • edit your .bashrc and remove the line with source activate environment

Also check the docs on JupyterHub!

JupyterHub

Should I use Python?

• Absolutely.

Tutorials

• Python Scientific Lecture Notes: http://scipy-lectures.github.io
• Scientific Python Lectures: https://github.com/jrjohansson/scientific-python-lectures
• Book for Beginners "Dive Into Python": http://www.diveintopython.net

Which version should I use? python 2 or python 3?

• You should use python 3 for every new project.
• Note: Python 2 has reached its end-of-life in 2019. It no longer receives bugfixes. Most projects (numpy, matplotlib, ...) stoped supporting python 2!

What's the recommended way to use python at IAC?

• We recommend to use conda to manage packages and environments. See below.

What about other solutions?

• Python installed on the machines?
  It is discouraged to use the python installation on the machines. Package versions can change unexpectedly which may lead to code incompatibilities. This solution is not viable for long-term reproducibility.

• Virtual environments?
  Conda is superior to virtual environments because it also handles non-python dependencies (such as the netCDF library) and can therefore offer a more stable environment.

What are Best Practices when using python?

• For each project you should decide on a conda environment and note which one you use. You could for example create a startup file that you call every time you work on the project:

  #!/bin/bash
  module load conda/2022
  source activate iacpy3_2022
  

• This file has to be made executable (chmod +x startup) and needs to be invoked as source startup.
• See this gist for a more complete example

Why is it important to work with a fixed environment?

• Python packages undergo a rapid development and may become incompatible with your script. If you want to re-run your analysis in at a later stage you want to have the same versions for the packages you used. Therefore it is important that you know which environment you used.

Using Conda (on Linux)

What is conda?

• conda is a program that manages (python) packages and environments. It allows to use a centralized installation while still providing user flexibility in term of package installation.

What is mamba?

• mamba is a faster drop-in replacement for conda - it allows for much faster dependency solving. You can replace almost every conda command by mamba command

What is a conda environment?

• From the conda documentation: A conda environment is a directory that contains a specific collection of conda packages that you have installed. For example, you may have one environment with NumPy 1.7 and its dependencies, and another environment with NumPy 1.6 for legacy testing. If you change one environment, your other environments are not affected. You can easily activate or deactivate environments, which is how you switch between them. You can also share your environment with someone by giving them a copy of your environment.yaml file.

What is a conda package?

• A conda package is a compressed tarball file that contains system-level libraries, Python or other modules, executable programs and other components. Conda keeps track of the dependencies between packages and platforms. Thus, it can not only handle python packages but also other dependencies (e.g. the netCDF c library).

• See also conda documentation

How do I use conda?

• Load the module

  module load conda
  

• View all environments

  conda env list
  

• Work in an environment

  source activate iacpy3_2023
  

  • Warning: do not do this in your .bashrc, instead define an alias (see below)
• List installed python packages

  conda list
  

• jupyter -> use JupyterHub)
• Start spyder

  spyder
  

• Use ipython

  ipython
  

• For a simpler and quicker usage, you can create an alias in your ~/.bashrc:

  alias iacpy24='module load conda; source activate iacpy3_2024'
  

What environments are available?

• You can also make all environments available with module load conda

• 2024 environments

  module load conda/2024
  conda env list
  

  • iacpy3_2024: based on iacpy3_2023, uses python 3.11; updated all packages on 16.04.2024; Note that a number of packages have been removed from the environment - contact iac-linux@env.ethz.ch if you are missing something.

• 2023 environments

  module load conda/2023
  conda env list
  

  • iacpy3_2023: based on iacpy3_2022, uses python 3.11; updated all packages on 08.08.2023; Note that a number of packages have been removed from the environment - contact iac-linux@env.ethz.ch if you are missing something.

I am missing a package - what can I do?

• Write to iac-linux@env.ethz.ch - we can generally add single packages to the existing environments. If you are impatient, see below.

How can I install a single package?

• You will need to create your own environment (see below), and then add the package with

  mamba install <package>
  

How can I create my own environment?

• conda allows to manage environments without being root!

Create a new environment

• You can create your own environment. E.g.:

  mamba create -n myenv scipy
  

• NB: don't forget to include ipython in your new environment

Clone and tweak an existing environment

• If you want to have more control on your environment but still exiting one as a base, you can do the following:

  mamba create -n analysis_2019 --clone iacpy3_2019
  

• You can now add packages to the new environment:

  source activate analysis_2019
  mamba install <package>
  # - OR -
  pip install <package> # installation with mamba is preferred!
  

Background information about the differences between pip, conda and anaconda

• Blogpost by Jake Vanderplas

How can I create an executable python script when using a conda environment?

• To run a python script directly from the command line (./script.py) you need to add the following at the top of your script

  #!/usr/bin/env python
  

• However, the environment needs to be loaded, before it is executed.
• Of course the file needs to be executable (chmod +x scripy.py)

How to best run jupyter notebook on a server?

• We recommend using JupyterHub.

Run a notebook on a server - from your personal computer

• We recommend using JupyterHub.

Run spyder remotely

• Please don't run spyder on fog or fog2. These are login nodes that don't have many ressources.
• ssh to any of the servers to run your analyis, e.g.:

  ssh -X <username>@fog.ethz.ch
  ssh -X litho
  module load conda
  source activate iacpy3_2023
  spyder
  

• If you don't want to log in twice (-> fog -> server), see tipps above (Run a notebook on a server)

Spyder 3 shows strange symbols

• Something goes wrong with the font in spyder3. The workaround is to use the symbols of spyder2.
• In spyder3 go to Tools > General (Appearance) > Icon Theme: Change to Spyder 2 and restart spyder.

user packages no longer available in conda environment and JupyerHub

• Packages installed with pip install <package> --user (site packages) are no longer available in personal conda environments.
• This should not effect most users.

Packages

xarray

How do I prevent xarray from automatically adding _FillValue to coordinates or variables without NaN?

• Specify encoding when saving to disk (xarray version 10.2)

  # Saving back to disk with encoding dictionary telling not to use _FillValues for specified coordinates or variables
  encoding = {'lat' : {'_FillValue' : None}, 'lon' : {'_FillValue' : None}, 'time' : {'_FillValue' : None}}
  xarray.Dataset.to_netcdf('./outfile.nc',format='NetCDF4',encoding=encoding)
  

Why did xarray change the type of an nc attribute to string, causing other software to crash on the resulting nc file?

• Probably there was a special character (e.g. 'ü') in the attribute. Two suggested workarounds. (xarray version 10.2)

  # Workaround A) use 'NetCDF4_CLASSIC'
  xarray.Dataset.to_netcdf('./outfile.nc',format='NetCDF4_CLASSIC')
  # Workaround B) change the attribute name 
  xarray.Dataset.attrs['institution'] = 'IAC ETH Zuerich' # instead of 'IAC ETH Zürich'
  xarray.Dataset.to_netcdf('./outfile.nc',format='NetCDF4')
  

matplotlib

I don't see a figure when typing plt.show()?

• Per default the plot backend is set to "agg". The "agg" backend is for writing to file and does not show a plot. Type the following to see your backend:

  import matplotlib as plt
  plt.get_backend()
  

• Set the backend in your code:

  import matplotlib
  matplotlib.rcParams['backend'] = "Qt4Agg"
  

• Or define your backend inside your ~/.config/matplotlib/matplotlibrc file

  backend      : Qt4Agg
  

  Important If you have a ~/.matplotlib folder, first move it to the new location ~/.config:

  mv ~/.matplotlib ~/.config/matplotlib 
  

More information can be found here: http://matplotlib.sourceforge.net/users/customizing.html