Jupyter Notebooks as Python with embedded Markdown
pynb relies on nbconvert and lets you manage Jupyter notebooks as plain Python code with embedded Markdown text, enabling:
Python development environment: Use your preferred IDE/editor, ensure style compliance, navigate, refactor, and test your notebooks as regular Python code.
Version control: Track changes, review pull requests and merge conflicts as with regular Python code. The cell outputs are stored separately and don't interfere with versioning.
Consistent execution state: Never lose track again of the execution state. Notebooks are always executed from clean iPython kernels and the cell execution is cached.
You also get parametrized notebooks with batch and programmatic execution.
Installation
pynb is compatible with Python >= 3.4 and can be installed with pip:
pip install pynb
The pynb notebook format
A pynb notebook is a Python function that represents a sequence of cells whose type is either Python or Markdown:
# Contents of sum.py
def cells(a, b=3):
'''
# Sum
'''
a = int(a)
b = int(b)
'''
'''
a + b
The example above defines a notebook composed of three cells: Markdown, Python, Python.
Function parameters are mapped to notebook arguments and are injected as an additional cell at runtime. Lines whose content is ''' serve as cell separators. Markdown cells are embedded in multi-line string blocks surrounded by '''. Consecutive Python cells are separated by '''\n'''. Empty cells are ignored and trailing spaces or empty lines within cells are stripped away.
The Python statement return has a special meaning and it instructs the parser to ignore the remaining content of the notebook.
A Python module can contain several functions defining multiple notebooks. Examples can be found notebooks directory.
Usage
The pynb command line tool is tailored for simplicity and is the fastest way to write & run a pynb notebook.
To run the sum.py:cells notebook reported above:
pynb notebooks/sum.py --param a=3 --param b=5
You can set a different logging level with the --log-level option. The default logging level is INFO.
By default, a Markdown cell is appended if exporting to Jupyter notebook format with details on the execution: location of Python notebook, execution time and complete command line. You can avoid the insertion of the footer cell with the --disable-footer option.
The default name of the function defining the notebook is cells. A different function name can be specified by appending :func_name to the module pathname. E.g., sum.py:func_name. sum.py:cells is therefore equivalent to sum.py. A Python module can contain multiple notebook definitions by using different function names.
Notebook parameters
Parameters are passed from the command line with --param options, whose value is formatted as name=value. Names are separated from values at the first occurrence of character =. Values are strings and might require casting to their proper type inside the notebook.
Remark that pynb support also default parameter definitions, as it can be seen with b in the example. Those default parameters can be overwritten using the standard --param notation.
Importing from Jupyter notebooks
You can import a Jupyter notebook and export it as Python notebook as follows:
The options --export-html and --export-ipynb let you export to .html and .ipynb file formats, respectively.
The special output pathname - points to standard output.
If you only want to convert the notebook without executing it, you can skip its execution using the --no-exec option.
If you export to a Jupyter notebook, you can set the kernel with the --kernel option:
The caching system allows you to reuse transparently prior cell executions and it's enabled by default.
The option --disable-cache disables the cache.
You can force a complete new notebook execution by ignoring the existing cache with option --ignore-cache.
To clean the cache, remove manually the files /tmp/pynb-cache-*.
How does it work?
An hash is generated for each cell by using the full pathname of the file containing the notebook definition, runtime notebook parameters, cell content and position. After executing a cell for the first time, its output and iPython kernel state are cached. Subsequent executions of the same cell use the cached cell state and speed up significantly the notebook execution.
The iPython session is dumped using the dill package. It is not always possible to serialize objects. E.g., a variable representing an open file cannot be serialized. Other notable cases are database connections and iterators. In such situations, a warning serialization failed is reported and the cache is disabled for the current and subsequent cells. Serialization issues do not affect the outputs of the notebook execution.
How to fix serialization failures:
First, enable the DEBUG logging with --log-level DEBUG to print the stack trace of the serialization error (multi-line and coloured). The stack trace will provide hints on which variables are causing the problem.
Second, fix the code:
Move the problematic variables inside a with statement. In general, the with statement ensures a clean & lean iPython kernel state.
Delete the problematic variables with the del statement.
Reset the iPython session resolving any serialization issue with the iPython's reset built-in magic command:
get_ipython().magic('reset -f')
Class interface
The pynb.Notebook class interface provides a finer control on parametrization and execution.
To define a notebook, extend the Notebook class and use it as in the example below:
# Contents of sumapp.py
from pynb.notebook import Notebook
class SumNotebook(Notebook):
def cells(self, a, b):
a + b
if __name__ == "__main__":
nb = SumNotebook()
nb.add_argument('--a', default=5, type=int)
nb.add_argument('--b', type=int)
nb.add_argument('--print-ipynb', action="store_true", default=False)
nb.run()
if nb.args.print_ipynb:
nb.export_ipynb('-')
To run it:
python3 notebooks/sumapp.py --b 3 --print-ipynb
Class SumNotebook extends Notebook and defines the notebook in method cells. Method Notebook.add_argument maps to ArgumentParser.add_argument and lets you define additional notebook parameters or custom options. Method Notebook.run takes care of executing the notebook taking into account the command line arguments. After running the notebook, the attribute nb.args contains the object returned by ArgumentParser.parse_args and can be used to handle additional user-defined options. E.g., --print-ipynb.
Command line arguments
If you want to handle user-defined parameters before calling nb.run(), you can call nb.parse_args() to initialize explicitly nb.args. There must be an exact match between the parameter names of the cells function and argparse attribute names.
All notebook parameter values that have no default value must be provided from the command line. E.g., parameter b in the example above.
All command line options available from the pynb command line tool are also available with the class interface.
Credits and license
The pynb project is released under the MIT license. Please see LICENSE.txt.
Known issues
On MacOS, ignore these warning messages RuntimeWarning: Failed to set sticky bit on. It's a known bug.
In case of errors, try to update the involved packages:
pip install pynb --upgrade --no-cache
Development
Create Python environment
Instructions that work on MacOS Catalina:
Install a specific version of Python: pyenv install 3.8.3
Create virtualenv: pyenv virtualenv 3.8.3 pynb
Activate virtualenv: pyenv activate pynb
Update pip: pip install --upgrade pip
Install packages: pip install -r requirements.txt
Install package in development mode: pip install -e .
if command -v pyenv 1>/dev/null 2>&1; then
eval "$(pyenv init -)"
export PYENV_VIRTUALENV_DISABLE_PROMPT=1
fi
if which pyenv-virtualenv-init > /dev/null; then eval "$(pyenv virtualenv-init -)"; fi
The fabfile assumes you have zsh as shell and the pynb virtual env.
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