Awesome
Py.test plugin for validating Jupyter notebooks
The plugin adds functionality to py.test to recognise and collect Jupyter
notebooks. The intended purpose of the tests is to determine whether execution
of the stored inputs match the stored outputs of the .ipynb
file. Whilst also
ensuring that the notebooks are running without errors.
The tests were designed to ensure that Jupyter notebooks (especially those for reference and documentation), are executing consistently.
Each cell is taken as a test, a cell that doesn't reproduce the expected output will fail.
See docs/source/index.ipynb
for the full documentation.
Installation
Available on PyPi:
pip install nbval
or install the latest version from cloning the repository and running:
pip install .
from the main directory. To uninstall:
pip uninstall nbval
How it works
The extension looks through every cell that contains code in an IPython notebook
and then the py.test
system compares the outputs stored in the notebook
with the outputs of the cells when they are executed. Thus, the notebook itself is
used as a testing function.
The output lines when executing the notebook can be sanitized passing an
extra option and file, when calling the py.test
command. This file
is a usual configuration file for the ConfigParser
library.
Regarding the execution, roughly, the script initiates an
IPython Kernel with a shell
and
an iopub
sockets. The shell
is needed to execute the cells in
the notebook (it sends requests to the Kernel) and the iopub
provides
an interface to get the messages from the outputs. The contents
of the messages obtained from the Kernel are organised in dictionaries
with different information, such as time stamps of executions,
cell data types, cell types, the status of the Kernel, username, etc.
In general, the functionality of the IPython notebook system is quite complex, but a detailed explanation of the messages and how the system works, can be found here
https://jupyter-client.readthedocs.io/en/latest/messaging.html#messaging
Execution
To execute this plugin, you need to execute py.test
with the nbval
flag
to differentiate the testing from the usual python files:
py.test --nbval
You can also specify --nbval-lax
, which runs notebooks and checks for
errors, but only compares the outputs of cells with a #NBVAL_CHECK_OUTPUT
marker comment.
py.test --nbval-lax
The commands above will execute all the .ipynb
files and 'pytest' tests in the current folder.
Specify -p no:python
if you would like to execute notebooks only. Alternatively, you can execute a specific notebook:
py.test --nbval my_notebook.ipynb
By default, each .ipynb
file will be executed using the kernel
specified in its metadata. You can override this behavior by passing
either --nbval-kernel-name mykernel
to run all the notebooks using
mykernel
, or --current-env
to use a kernel in the same environment
in which pytest itself was launched.
If the output lines are going to be sanitized, an extra flag, --nbval-sanitize-with
together with the path to a confguration file with regex expressions, must be passed,
i.e.
py.test --nbval my_notebook.ipynb --nbval-sanitize-with path/to/my_sanitize_file
where my_sanitize_file
has the following structure.
[Section1]
regex: [a-z]*
replace: abcd
regex: [1-9]*
replace: 0000
[Section2]
regex: foo
replace: bar
The regex
option contains the expression that is going to be matched in the outputs, and
replace
is the string that will replace the regex
match. Currently, the section
names do not have any meaning or influence in the testing system, it will take
all the sections and replace the corresponding options.
Coverage
To use notebooks to generate coverage for imported code, use the pytest-cov plugin. nbval should automatically detect the relevant options and configure itself with it.
Parallel execution
nbval is compatible with the pytest-xdist plugin for parallel running of tests. It does
however require the use of the --dist loadscope
flag to ensure that all cells of one
notebook are run on the same kernel.
Documentation
The narrative documentation for nbval can be found at https://nbval.readthedocs.io.
Help
The py.test
system help can be obtained with py.test -h
, which will
show all the flags that can be passed to the command, such as the
verbose -v
option. Nbval's options can be found under the
Jupyter Notebook validation
section.
Acknowledgements
This plugin was inspired by Andrea Zonca's py.test plugin for collecting unit tests in the IPython notebooks (https://github.com/zonca/pytest-ipynb).
The original prototype was based on the template in
https://gist.github.com/timo/2621679 and the code of a testing system
for notebooks https://gist.github.com/minrk/2620735 which we
integrated and mixed with the py.test
system.
We acknowledge financial support from
-
OpenDreamKit Horizon 2020 European Research Infrastructures project (#676541), http://opendreamkit.org
-
EPSRC's Centre for Doctoral Training in Next Generation Computational Modelling, http://ngcm.soton.ac.uk (#EP/L015382/1) and EPSRC's Doctoral Training Centre in Complex System Simulation ((EP/G03690X/1),
-
The Gordon and Betty Moore Foundation through Grant GBMF #4856, by the Alfred P. Sloan Foundation and by the Helmsley Trust.
Authors
2014 - 2017 David Cortes-Ortuno, Oliver Laslett, T. Kluyver, Vidar Fauske, Maximilian Albert, MinRK, Ondrej Hovorka, Hans Fangohr