Python Utils is a module with some convenient utilities not included with the standard Python install
Project description
Python Utils is a collection of small Python functions and classes which make common patterns shorter and easier. It is by no means a complete collection but it has served me quite a bit in the past and I will keep extending it.
One of the libraries using Python Utils is Django Utils.
Documentation is available at: https://python-utils.readthedocs.org/en/latest/
Links
The source: https://github.com/WoLpH/python-utils
Project page: https://pypi-hypernode.com/pypi/python-utils
Reporting bugs: https://github.com/WoLpH/python-utils/issues
Documentation: https://python-utils.readthedocs.io/en/latest/
My blog: https://wol.ph/
Requirements for installing:
For the Python 3+ release (i.e. v3.0.0 or higher) there are no requirements. For the Python 2 compatible version (v2.x.x) the six package is needed.
Installation:
The package can be installed through pip (this is the recommended method):
pip install python-utils
Or if pip is not available, easy_install should work as well:
easy_install python-utils
Or download the latest release from Pypi (https://pypi-hypernode.com/pypi/python-utils) or Github.
Note that the releases on Pypi are signed with my GPG key (https://pgp.mit.edu/pks/lookup?op=vindex&search=0xE81444E9CE1F695D) and can be checked using GPG:
gpg –verify python-utils-<version>.tar.gz.asc python-utils-<version>.tar.gz
Quickstart
This module makes it easy to execute common tasks in Python scripts such as converting text to numbers and making sure a string is in unicode or bytes format.
Examples
Automatically converting a generator to a list, dict or other collections using a decorator:
>>> @decorators.listify()
... def generate_list():
... yield 1
... yield 2
... yield 3
...
>>> generate_list()
[1, 2, 3]
>>> @listify(collection=dict)
... def dict_generator():
... yield 'a', 1
... yield 'b', 2
>>> dict_generator()
{'a': 1, 'b': 2}Retrying until timeout
To easily retry a block of code with a configurable timeout, you can use the time.timeout_generator:
>>> for i in time.timeout_generator(10):
... try:
... # Run your code here
... except Exception as e:
... # Handle the exceptionFormatting of timestamps, dates and times
Easy formatting of timestamps and calculating the time since:
>>> time.format_time('1')
'0:00:01'
>>> time.format_time(1.234)
'0:00:01'
>>> time.format_time(1)
'0:00:01'
>>> time.format_time(datetime.datetime(2000, 1, 2, 3, 4, 5, 6))
'2000-01-02 03:04:05'
>>> time.format_time(datetime.date(2000, 1, 2))
'2000-01-02'
>>> time.format_time(datetime.timedelta(seconds=3661))
'1:01:01'
>>> time.format_time(None)
'--:--:--'
>>> formatters.timesince(now)
'just now'
>>> formatters.timesince(now - datetime.timedelta(seconds=1))
'1 second ago'
>>> formatters.timesince(now - datetime.timedelta(seconds=2))
'2 seconds ago'
>>> formatters.timesince(now - datetime.timedelta(seconds=60))
'1 minute ago'Converting your test from camel-case to underscores:
>>> camel_to_underscore('SpamEggsAndBacon')
'spam_eggs_and_bacon'Attribute setting decorator. Very useful for the Django admin
A convenient decorator to set function attributes using a decorator:
You can use:
>>> @decorators.set_attributes(short_description='Name')
... def upper_case_name(self, obj):
... return ("%s %s" % (obj.first_name, obj.last_name)).upper()
Instead of:
>>> def upper_case_name(obj):
... return ("%s %s" % (obj.first_name, obj.last_name)).upper()
>>> upper_case_name.short_description = 'Name'This can be very useful for the Django admin as it allows you to have all metadata in one place.
Scaling numbers between ranges
>>> converters.remap(500, old_min=0, old_max=1000, new_min=0, new_max=100)
50
# Or with decimals:
>>> remap(decimal.Decimal('250.0'), 0.0, 1000.0, 0.0, 100.0)
Decimal('25.0')Get the screen/window/terminal size in characters:
>>> terminal.get_terminal_size()
(80, 24)That method supports IPython and Jupyter as well as regular shells, using blessings and other modules depending on what is available.
Extracting numbers from nearly every string:
>>> converters.to_int('spam15eggs')
15
>>> converters.to_int('spam')
0
>>> number = converters.to_int('spam', default=1)
1Doing a global import of all the modules in a package programmatically:
To do a global import programmatically you can use the import_global function. This effectively emulates a from … import *
from python_utils.import_ import import_global
# The following is the equivalent of `from some_module import *`
import_global('some_module')Automatically named logger for classes:
Or add a correclty named logger to your classes which can be easily accessed:
class MyClass(Logged):
def __init__(self):
Logged.__init__(self)
my_class = MyClass()
# Accessing the logging method:
my_class.error('error')
# With formatting:
my_class.error('The logger supports %(formatting)s',
formatting='named parameters')
# Or to access the actual log function (overwriting the log formatting can
# be done n the log method)
import logging
my_class.log(logging.ERROR, 'log')Convenient type aliases and some commonly used types:
# For type hinting scopes such as locals/globals/vars
Scope = Dict[str, Any]
OptionalScope = O[Scope]
# Note that Number is only useful for extra clarity since float
# will work for both int and float in practice.
Number = U[int, float]
DecimalNumber = U[Number, decimal.Decimal]
# To accept an exception or list of exceptions
ExceptionType = Type[Exception]
ExceptionsType = U[Tuple[ExceptionType, ...], ExceptionType]
# Matching string/bytes types:
StringTypes = U[str, bytes]Release history Release notifications | RSS feed
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