# read
text = open('textfile', 'r').read()
text = open('textfile', 'r').readlines()
with open('textfile', 'r') as f:
for line in f:
print line
# write
f = open('textfile', 'w')
for line in lines:
f.write(line)# read
import csv
csv_file = []
with open('file.csv', 'rb') as f:
reader = csv.reader(f)
for line in reader:
csv_file.append(line)
csv_file = []
with open('file.csv', 'rb') as f:
reader = csv.DictReader(f)
for line in reader:
csv_file.append([line['col1'], line['col2']])
# write
with open('file.csv', 'wb') as f:
writer = csv.writer(f)
writer.writerows(iterable)
list_of_dicts = [{'first': 'a', 'second': 1},
{'first': 'b', 'second': 2}]
with open('file.csv', 'wb') as f:
fieldnames = ['second']
writer = csv.DictWriter(f, fieldnames=fieldnames)
for line in list_of_dicts:
line.writerow(line)a = ['red', 'blue', 'green'] # manually initialization
b = list(range(5)) # initialize from iteratable
c = [nu**2 for nu in b] # list comprehension
d = [nu**2 for nu in b if nu < 3] # conditioned list comprehension
e = c[0] # access element
f = c[1:2] # access a slice of the list
g = c[-1] # access last element
h = ['re', 'bl'] + ['gr'] # list concatenation
i = ['re'] * 5 # repeat a list
['re', 'bl'].index('re') # returns index of 're'
a.append('yellow') # add new element to end of list
a.extend(b) # add elements from list `b` to end of list `a`
a.insert(1, 'yellow') # insert element in specified position
're' in ['re', 'bl'] # true if 're' in list
'fi' not in ['re', 'bl'] # true if 'fi' not in list
sorted([3, 2, 1]) # returns sorted list
a.pop(2) # remove and return item at index (default last)a = {'red': 'rouge', 'blue': 'bleu'} # dictionary
b = a['red'] # translate item
'red' in a # true if dictionary a contains key 'red'
c = [value for key, value in a.items()] # loop through contents
d = a.get('yellow', 'no translation found') # return default
a.setdefault('extra', []).append('cyan') # init key with default
a.update({'green': 'vert', 'brown': 'brun'}) # update dictionary by data from another one
a.keys() # get list of keys
a.values() # get list of values
a.items() # get list of key-value pairs
del a['red'] # delete key and associated with it value
a.pop('blue') # remove specified key and return the corresponding valuea = {1, 2, 3} # initialize manually
b = set(range(5)) # initialize from iteratable
a.add(13) # add new element to set
a.discard(13) # discard element from set
a.update([21, 22, 23]) # update set with elements from iterable
a.pop() # remove and return an arbitrary set element
2 in {1, 2, 3} # true if 2 in set
5 not in {1, 2, 3} # true if 5 not in set
a.issubset(b) # test whether every element in a is in b
a <= b # issubset in operator form
a.issuperset(b) # test whether every element in b is in a
a >= b # issuperset in operator form
a.intersection(b) # return the intersection of two sets as a new set
a.difference(b) # return the difference of two or more sets as a new set
a - b # difference in operator form
a.symmetric_difference(b) # return the symmetric difference of two sets as a new set
a.union(b) # return the union of sets as a new set
c = frozenset() # the same as set but immutablea = 2 # assignment
a += 1 (*=, /=) # change and assign
3 + 2 # addition
3 / 2 # integer (python2) or float (python3) division
3 // 2 # integer division
3 * 2 # multiplication
3 ** 2 # exponent
3 % 2 # remainder
abs(a) # absolute value
1 == 1 # equal
2 > 1 # larger
2 < 1 # smaller
1 != 2 # not equal
1 != 2 and 2 < 3 # logical AND
1 != 2 or 2 < 3 # logical OR
not 1 == 2 # logical NOT
'a' in b # test if a is in b
a is b # test if objects point to the same memory (id)fatten list of lists
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
flat = [x for row in matrix for x in row]
>>> [1, 2, 3, 4, 5, 6, 7, 8, 9]
from itertools import chain
flat = list(chain.from_iterable(map(lambda x: x, matrix)))
>>> [1, 2, 3, 4, 5, 6, 7, 8, 9]
flat = list(chain(*[x for x in mat]))
>>> [1, 2, 3, 4, 5, 6, 7, 8, 9]# -*- coding: utf-8 -*-
"""Example NumPy style docstrings.
This module demonstrates documentation as specified by the `NumPy
Documentation HOWTO`_. Docstrings may extend over multiple lines. Sections
are created with a section header followed by an underline of equal length.
Example
-------
Examples can be given using either the ``Example`` or ``Examples``
sections. Sections support any reStructuredText formatting, including
literal blocks::
$ python example_numpy.py
Section breaks are created with two blank lines. Section breaks are also
implicitly created anytime a new section starts. Section bodies *may* be
indented:
Notes
-----
This is an example of an indented section. It's like any other section,
but the body is indented to help it stand out from surrounding text.
If a section is indented, then a section break is created by
resuming unindented text.
Attributes
----------
module_level_variable1 : int
Module level variables may be documented in either the ``Attributes``
section of the module docstring, or in an inline docstring immediately
following the variable.
Either form is acceptable, but the two should not be mixed. Choose
one convention to document module level variables and be consistent
with it.
.. _NumPy Documentation HOWTO:
https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt
"""
module_level_variable1 = 12345
module_level_variable2 = 98765
"""int: Module level variable documented inline.
The docstring may span multiple lines. The type may optionally be specified
on the first line, separated by a colon.
"""
def function_with_types_in_docstring(param1, param2):
"""Example function with types documented in the docstring.
`PEP 484`_ type annotations are supported. If attribute, parameter, and
return types are annotated according to `PEP 484`_, they do not need to be
included in the docstring:
Parameters
----------
param1 : int
The first parameter.
param2 : str
The second parameter.
Returns
-------
bool
True if successful, False otherwise.
.. _PEP 484:
https://www.python.org/dev/peps/pep-0484/
"""
def function_with_pep484_type_annotations(param1: int, param2: str) -> bool:
"""Example function with PEP 484 type annotations.
The return type must be duplicated in the docstring to comply
with the NumPy docstring style.
Parameters
----------
param1
The first parameter.
param2
The second parameter.
Returns
-------
bool
True if successful, False otherwise.
"""
def module_level_function(param1, param2=None, *args, **kwargs):
"""This is an example of a module level function.
Function parameters should be documented in the ``Parameters`` section.
The name of each parameter is required. The type and description of each
parameter is optional, but should be included if not obvious.
If \*args or \*\*kwargs are accepted,
they should be listed as ``*args`` and ``**kwargs``.
The format for a parameter is::
name : type
description
The description may span multiple lines. Following lines
should be indented to match the first line of the description.
The ": type" is optional.
Multiple paragraphs are supported in parameter
descriptions.
Parameters
----------
param1 : int
The first parameter.
param2 : :obj:`str`, optional
The second parameter.
*args
Variable length argument list.
**kwargs
Arbitrary keyword arguments.
Returns
-------
bool
True if successful, False otherwise.
The return type is not optional. The ``Returns`` section may span
multiple lines and paragraphs. Following lines should be indented to
match the first line of the description.
The ``Returns`` section supports any reStructuredText formatting,
including literal blocks::
{
'param1': param1,
'param2': param2
}
Raises
------
AttributeError
The ``Raises`` section is a list of all exceptions
that are relevant to the interface.
ValueError
If `param2` is equal to `param1`.
"""
if param1 == param2:
raise ValueError('param1 may not be equal to param2')
return True
def example_generator(n):
"""Generators have a ``Yields`` section instead of a ``Returns`` section.
Parameters
----------
n : int
The upper limit of the range to generate, from 0 to `n` - 1.
Yields
------
int
The next number in the range of 0 to `n` - 1.
Examples
--------
Examples should be written in doctest format, and should illustrate how
to use the function.
>>> print([i for i in example_generator(4)])
[0, 1, 2, 3]
"""
for i in range(n):
yield i
class ExampleError(Exception):
"""Exceptions are documented in the same way as classes.
The __init__ method may be documented in either the class level
docstring, or as a docstring on the __init__ method itself.
Either form is acceptable, but the two should not be mixed. Choose one
convention to document the __init__ method and be consistent with it.
Note
----
Do not include the `self` parameter in the ``Parameters`` section.
Parameters
----------
msg : str
Human readable string describing the exception.
code : :obj:`int`, optional
Numeric error code.
Attributes
----------
msg : str
Human readable string describing the exception.
code : int
Numeric error code.
"""
def __init__(self, msg, code):
self.msg = msg
self.code = code
class ExampleClass(object):
"""The summary line for a class docstring should fit on one line.
If the class has public attributes, they may be documented here
in an ``Attributes`` section and follow the same formatting as a
function's ``Args`` section. Alternatively, attributes may be documented
inline with the attribute's declaration (see __init__ method below).
Properties created with the ``@property`` decorator should be documented
in the property's getter method.
Attributes
----------
attr1 : str
Description of `attr1`.
attr2 : :obj:`int`, optional
Description of `attr2`.
"""
def __init__(self, param1, param2, param3):
"""Example of docstring on the __init__ method.
The __init__ method may be documented in either the class level
docstring, or as a docstring on the __init__ method itself.
Either form is acceptable, but the two should not be mixed. Choose one
convention to document the __init__ method and be consistent with it.
Note
----
Do not include the `self` parameter in the ``Parameters`` section.
Parameters
----------
param1 : str
Description of `param1`.
param2 : :obj:`list` of :obj:`str`
Description of `param2`. Multiple
lines are supported.
param3 : :obj:`int`, optional
Description of `param3`.
"""
self.attr1 = param1
self.attr2 = param2
self.attr3 = param3 #: Doc comment *inline* with attribute
#: list of str: Doc comment *before* attribute, with type specified
self.attr4 = ["attr4"]
self.attr5 = None
"""str: Docstring *after* attribute, with type specified."""
@property
def readonly_property(self):
"""str: Properties should be documented in their getter method."""
return "readonly_property"
@property
def readwrite_property(self):
""":obj:`list` of :obj:`str`: Properties with both a getter and setter
should only be documented in their getter method.
If the setter method contains notable behavior, it should be
mentioned here.
"""
return ["readwrite_property"]
@readwrite_property.setter
def readwrite_property(self, value):
value
def example_method(self, param1, param2):
"""Class methods are similar to regular functions.
Note
----
Do not include the `self` parameter in the ``Parameters`` section.
Parameters
----------
param1
The first parameter.
param2
The second parameter.
Returns
-------
bool
True if successful, False otherwise.
"""
return True
def __special__(self):
"""By default special members with docstrings are not included.
Special members are any methods or attributes that start with and
end with a double underscore. Any special member with a docstring
will be included in the output, if
``napoleon_include_special_with_doc`` is set to True.
This behavior can be enabled by changing the following setting in
Sphinx's conf.py::
napoleon_include_special_with_doc = True
"""
pass
def __special_without_docstring__(self):
pass
def _private(self):
"""By default private members are not included.
Private members are any methods or attributes that start with an
underscore and are *not* special. By default they are not included
in the output.
This behavior can be changed such that private members *are* included
by changing the following setting in Sphinx's conf.py::
napoleon_include_private_with_doc = True
"""
pass
def _private_without_docstring(self):
pass