Documentation
Developing Python Packages
James Fulton
Climate informatics researcher
Why include documentation?
- Helps your users use your code
- Document each
- Function
- Class
- Class method
import numpy as np
help(np.sum)
...
sum(a, axis=None, dtype=None, out=None)
Sum of array elements over a given axis.
Parameters
----------
a : array_like
Elements to sum.
axis : None or int or tuple of ints, optional
Axis or axes along which a sum is performed.
The default, axis=None, will sum all of the
elements of the input array.
...
Why include documentation?
- Helps your users use your code
- Document each
- Function
- Class
- Class method
import numpy as np
help(np.array)
...
array(object, dtype=None, copy=True)
Create an array.
Parameters
----------
object : array_like
An array, any object exposing the array
interface ...
dtype : data-type, optional
The desired data-type for the array.
copy : bool, optional
If true (default), then the object is copied.
...
Why include documentation?
- Helps your users use your code
- Document each
- Function
- Class
- Class method
import numpy as np
x = np.array([1,2,3,4])
help(x.mean)
...
mean(...) method of numpy.ndarray instance
a.mean(axis=None, dtype=None, out=None)
Returns the average of the array elements
along given axis.
Refer to `numpy.mean` for full documentation.
...
Function documentation
def count_words(filepath, words_list):""" ... """
Function documentation
def count_words(filepath, words_list):"""Count the total number of times these words appear."""
Function documentation
def count_words(filepath, words_list):"""Count the total number of times these words appear. The count is performed on a text file at the given location. """
Function documentation
def count_words(filepath, words_list):"""Count the total number of times these words appear. The count is performed on a text file at the given location. [explain what filepath and words_list are] [what is returned] """
Documentation style
Google documentation style
"""Summary line.
Extended description of function.
Args:
arg1 (int): Description of arg1
arg2 (str): Description of arg2
NumPy style
"""Summary line.
Extended description of function.
Parameters
----------
arg1 : int
Description of arg1 ...
Returns
----------
numpy.ndarray
reStructured text style
"""Summary line.
Extended description of function.
:param arg1: Description of arg1
:type arg1: int
:param arg2: Description of arg2
:type arg2: str
Epytext style
"""Summary line.
Extended description of function.
@type arg1: int
@param arg1: Description of arg1
@type arg2: str
@param arg2: Description of arg2
NumPy documentation style
Popular in scientific Python packages like
numpyscipypandassklearnmatplotlibdask- etc.
NumPy documentation style
import scipy
help(scipy.percentile)
percentile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear') Compute the q-th percentile of the data along the specified axis. Returns the q-th percentile(s) of the array elements.Parameters ----------a : array_likeInput array or object that can be converted to an array.
Other types include - int, float, bool, str, dict, numpy.array, etc.
NumPy documentation style
import scipy
help(scipy.percentile)
percentile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear')
...
Parameters
----------
...
axis : {int, tuple of int, None}
...
interpolation : {'linear', 'lower', 'higher', 'midpoint', 'nearest'}
- List multiple types for parameter if appropriate
- List accepted values if only a few valid options
NumPy documentation style
import scipy
help(scipy.percentile)
percentile(a, q, axis=None, out=None, overwrite_input=False, interpolation='linear')
...
Returns
-------
percentile : scalar or ndarray
If `q` is a single percentile and `axis=None`, then the result
is a scalar. If multiple percentiles are given, first axis of
the result corresponds to the percentiles...
...
NumPy documentation style
Other sections
RaisesSee AlsoNotesReferencesExamples
1 https://numpydoc.readthedocs.io/en/latest/format.html
Documentation templates and style translation
pymentcan be used to generate docstrings- Run from terminal
- Any documentation style from
- Numpydoc
- reST (i.e. reStructured-text)
- Javadoc (i.e. epytext)
- Modify documentation from one style to another
Documentation templates and style translation
pyment -w -o numpydoc textanalysis.py
def count_words(filepath, words_list):
# Open the text file
...
return n
-w- overwrite file-o numpydoc- output in NumPy style
Documentation templates and style translation
pyment -w -o numpydoc textanalysis.py
def count_words(filepath, words_list):
"""
Parameters
----------
filepath :
words_list :
Returns
-------
type
"""
Translate to Google style
pyment -w -o google textanalysis.py
def count_words(filepath, words_list):
"""Count the total number of times these words appear.
The count is performed on a text file at the given location.
Parameters
----------
filepath : str
Path to text file.
words_list : list of str
Count the total number of appearances of these words.
Returns
-------
"""
Translate to Google style
pyment -w -o google textanalysis.py
def count_words(filepath, words_list):
"""Count the total number of times these words appear.
The count is performed on a text file at the given location.
Args:
filepath(str): Path to text file.
words_list(list of str): Count the total number of appearances of these words.
Returns:
"""
Package, subpackage and module documentation
mysklearn/__init__.py
"""
Linear regression for Python
============================
mysklearn is a complete package for implmenting
linear regression in python.
"""
mysklearn/preprocessing/__init__.py
"""
A subpackage for standard preprocessing operations.
"""
mysklearn/preprocessing/normalize.py
"""
A module for normalizing data.
"""
Let's practice!
Developing Python Packages
