Faker is a Python package that generates fake data for you.

Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in your persistence to stress test it, or anonymize data taken from a production service, Faker is for you.

Faker is heavily inspired by PHP Faker, Perl Faker, and by Ruby Faker.


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Latest version released on PyPI Build status of the master branch on Mac/Linux Build status of the master branch on Windows Test coverage Package license


Compatibility

Starting from version 4.0.0, Faker dropped support for Python 2 and from version 5.0.0 only supports Python 3.6 and above. If you still need Python 2 compatibility, please install version 3.0.1 in the meantime, and please consider updating your codebase to support Python 3 so you can enjoy the latest features Faker has to offer. Please see the extended docs for more details, especially if you are upgrading from version 2.0.4 and below as there might be breaking changes.

This package was also previously called fake-factory which was already deprecated by the end of 2016, and much has changed since then, so please ensure that your project and its dependencies do not depend on the old package.

Basic Usage

Install with pip:

pip install Faker

Use faker.Faker() to create and initialize a faker generator, which can generate data by accessing properties named after the type of data you want.

from faker import Faker
fake = Faker()

fake.name()
# 'Lucy Cechtelar'

fake.address()
# '426 Jordy Lodge
#  Cartwrightshire, SC 88120-6700'

fake.text()
# 'Sint velit eveniet. Rerum atque repellat voluptatem quia rerum. Numquam excepturi
#  beatae sint laudantium consequatur. Magni occaecati itaque sint et sit tempore. Nesciunt
#  amet quidem. Iusto deleniti cum autem ad quia aperiam.
#  A consectetur quos aliquam. In iste aliquid et aut similique suscipit. Consequatur qui
#  quaerat iste minus hic expedita. Consequuntur error magni et laboriosam. Aut aspernatur
#  voluptatem sit aliquam. Dolores voluptatum est.
#  Aut molestias et maxime. Fugit autem facilis quos vero. Eius quibusdam possimus est.
#  Ea quaerat et quisquam. Deleniti sunt quam. Adipisci consequatur id in occaecati.
#  Et sint et. Ut ducimus quod nemo ab voluptatum.'

Each call to method fake.name() yields a different (random) result. This is because faker forwards faker.Generator.method_name() calls to faker.Generator.format(method_name).

for _ in range(10):
  print(fake.name())

# 'Adaline Reichel'
# 'Dr. Santa Prosacco DVM'
# 'Noemy Vandervort V'
# 'Lexi O'Conner'
# 'Gracie Weber'
# 'Roscoe Johns'
# 'Emmett Lebsack'
# 'Keegan Thiel'
# 'Wellington Koelpin II'
# 'Ms. Karley Kiehn V'

Pytest fixtures

Faker also has its own pytest plugin which provides a faker fixture you can use in your tests. Please check out the pytest fixture docs to learn more.

Providers

Each of the generator properties (like name, address, and lorem) are called "fake". A faker generator has many of them, packaged in "providers".

from faker import Faker
from faker.providers import internet

fake = Faker()
fake.add_provider(internet)

print(fake.ipv4_private())

Check the extended docs for a list of bundled providers and a list of community providers.

Localization

faker.Faker can take a locale as an argument, to return localized data. If no localized provider is found, the factory falls back to the default en_US locale.

from faker import Faker
fake = Faker('it_IT')
for _ in range(10):
    print(fake.name())

# 'Elda Palumbo'
# 'Pacifico Giordano'
# 'Sig. Avide Guerra'
# 'Yago Amato'
# 'Eustachio Messina'
# 'Dott. Violante Lombardo'
# 'Sig. Alighieri Monti'
# 'Costanzo Costa'
# 'Nazzareno Barbieri'
# 'Max Coppola'

faker.Faker also supports multiple locales. New in v3.0.0.

from faker import Faker
fake = Faker(['it_IT', 'en_US', 'ja_JP'])
for _ in range(10):
    print(fake.name())

# 鈴木 陽一
# Leslie Moreno
# Emma Williams
# 渡辺 裕美子
# Marcantonio Galuppi
# Martha Davis
# Kristen Turner
# 中津川 春香
# Ashley Castillo
# 山田 桃子

You can check available Faker locales in the source code, under the providers package. The localization of Faker is an ongoing process, for which we need your help. Please don't hesitate to create a localized provider for your own locale and submit a Pull Request (PR).

Optimizations

The Faker constructor takes a performance-related argument called use_weighting. It specifies whether to attempt to have the frequency of values match real-world frequencies (e.g. the English name Gary would be much more frequent than the name Lorimer). If use_weighting is False, then all items have an equal chance of being selected, and the selection process is much faster. The default is True.

Command line usage

When installed, you can invoke faker from the command-line:

faker [-h] [--version] [-o output]
      [-l {bg_BG,cs_CZ,...,zh_CN,zh_TW}]
      [-r REPEAT] [-s SEP]
      [-i {package.containing.custom_provider otherpkg.containing.custom_provider}]
      [fake] [fake argument [fake argument ...]]

Where:

  • faker: is the script when installed in your environment, in development you could use python -m faker instead
  • -h, --help: shows a help message
  • --version: shows the program's version number
  • -o FILENAME: redirects the output to the specified filename
  • -l {bg_BG,cs_CZ,...,zh_CN,zh_TW}: allows use of a localized provider
  • -r REPEAT: will generate a specified number of outputs
  • -s SEP: will generate the specified separator after each generated output
  • -i {my.custom_provider other.custom_provider} list of additional custom providers to use. Note that is the import path of the package containing your Provider class, not the custom Provider class itself.
  • fake: is the name of the fake to generate an output for, such as name, address, or text
  • [fake argument ...]: optional arguments to pass to the fake (e.g. the profile fake takes an optional list of comma separated field names as the first argument)

Examples:

$ faker address
968 Bahringer Garden Apt. 722
Kristinaland, NJ 09890

$ faker -l de_DE address
Samira-Niemeier-Allee 56
94812 Biedenkopf

$ faker profile ssn,birthdate
{'ssn': u'628-10-1085', 'birthdate': '2008-03-29'}

$ faker -r=3 -s=";" name
Willam Kertzmann;
Josiah Maggio;
Gayla Schmitt;

How to create a Provider

from faker import Faker
fake = Faker()

# first, import a similar Provider or use the default one
from faker.providers import BaseProvider

# create new provider class
class MyProvider(BaseProvider):
    def foo(self):
        return 'bar'

# then add new provider to faker instance
fake.add_provider(MyProvider)

# now you can use:
fake.foo()
# 'bar'

How to customize the Lorem Provider

You can provide your own sets of words if you don't want to use the default lorem ipsum one. The following example shows how to do it with a list of words picked from cakeipsum :

from faker import Faker
fake = Faker()

my_word_list = [
'danish','cheesecake','sugar',
'Lollipop','wafer','Gummies',
'sesame','Jelly','beans',
'pie','bar','Ice','oat' ]

fake.sentence()
# 'Expedita at beatae voluptatibus nulla omnis.'

fake.sentence(ext_word_list=my_word_list)
# 'Oat beans oat Lollipop bar cheesecake.'

How to use with Factory Boy

Factory Boy already ships with integration with Faker. Simply use the factory.Faker method of factory_boy:

import factory
from myapp.models import Book

class BookFactory(factory.Factory):
    class Meta:
        model = Book

    title = factory.Faker('sentence', nb_words=4)
    author_name = factory.Faker('name')

Accessing the random instance

The .random property on the generator returns the instance of random.Random used to generate the values:

from faker import Faker
fake = Faker()
fake.random
fake.random.getstate()

By default all generators share the same instance of random.Random, which can be accessed with from faker.generator import random. Using this may be useful for plugins that want to affect all faker instances.

Unique values

Through use of the .unique property on the generator, you can guarantee that any generated values are unique for this specific instance.

from faker import Faker
fake = Faker()
names = [fake.unique.first_name() for i in range(500)]
assert len(set(names)) == len(names)

Calling fake.unique.clear() clears the already seen values. Note, to avoid infinite loops, after a number of attempts to find a unique value, Faker will throw a UniquenessException. Beware of the birthday paradox, collisions are more likely than you'd think.

from faker import Faker

fake = Faker()
for i in range(3):
     # Raises a UniquenessException
     fake.unique.boolean()

In addition, only hashable arguments and return values can be used with .unique.

Seeding the Generator

When using Faker for unit testing, you will often want to generate the same data set. For convenience, the generator also provide a seed() method, which seeds the shared random number generator. Calling the same methods with the same version of faker and seed produces the same results.

from faker import Faker
fake = Faker()
Faker.seed(4321)

print(fake.name())
# 'Margaret Boehm'

Each generator can also be switched to its own instance of random.Random, separate to the shared one, by using the seed_instance() method, which acts the same way. For example:

from faker import Faker
fake = Faker()
fake.seed_instance(4321)

print(fake.name())
# 'Margaret Boehm'

Please note that as we keep updating datasets, results are not guaranteed to be consistent across patch versions. If you hardcode results in your test, make sure you pinned the version of Faker down to the patch number.

If you are using pytest, you can seed the faker fixture by defining a faker_seed fixture. Please check out the pytest fixture docs to learn more.

Tests

Run tests:

$ tox

Write documentation for providers:

$ python -m faker > docs.txt

Contribute

Please see CONTRIBUTING.

License

Faker is released under the MIT License. See the bundled LICENSE file for details.

Credits

Owner
Daniele Faraglia
Web-native developer, UK based Self-employed
Daniele Faraglia
Comments
  • Move to 'faker' on Pypi

    Move to 'faker' on Pypi

    Looks like the Faker namespace on Pypi has been abandoned for quite a while: https://pypi.python.org/pypi/Faker

    This project's owner @joke2k should file a request to have the namespace transferred to this project.

    It would reduce confusion between Faker (project name) and fake-factory (how it gets pip installed).

    The pypi team is pretty good about transferring namespaces if they're clearly abandoned (which seems to be the case here).

  • Reproducibility of results broken between Faker-0.7.18 and (Faker-0.8.0, 0.8.7)

    Reproducibility of results broken between Faker-0.7.18 and (Faker-0.8.0, 0.8.7)

    Faker-0.8.0 and Faker-0.7.18 generate different values when given the same random source.

    Is the deterministic generation a goal of the project or not? I assumed that it is before… because the README specifically says that it's useful for unit testing, which is how I use it.

  • AttributeError: 'module' object has no attribute 'Provider'   on Faker()

    AttributeError: 'module' object has no attribute 'Provider' on Faker()

    When i create a Faker class i got following error:

    ERROR: Failure: AttributeError ('module' object has no attribute 'Provider')
    ----------------------------------------------------------------------
    Traceback (most recent call last):
      File "/usr/local/lib/python2.7/dist-packages/nose/loader.py", line 418, in loadTestsFromName
        addr.filename, addr.module)
      File "/usr/local/lib/python2.7/dist-packages/nose/importer.py", line 47, in importFromPath
        return self.importFromDir(dir_path, fqname)
      File "/usr/local/lib/python2.7/dist-packages/nose/importer.py", line 94, in importFromDir
        mod = load_module(part_fqname, fh, filename, desc)
      File "/home/rentapplication/django-rentapplication/rentapplication/tests/test_api/test_sessions.py", line 10, in <module>
        from rentapplication.tests.helpers import ReferrerFactory, LandlordFactory
      File "/home/rentapplication/django-rentapplication/rentapplication/tests/helpers.py", line 35, in <module>
        f = Faker()
      File "/usr/local/lib/python2.7/dist-packages/faker/factory.py", line 38, in create
        prov_cls, lang_found = cls._get_provider_class(prov_name, locale)
      File "/usr/local/lib/python2.7/dist-packages/faker/factory.py", line 49, in _get_provider_class
        provider_class = cls._find_provider_class(provider, locale)
      File "/usr/local/lib/python2.7/dist-packages/faker/factory.py", line 87, in _find_provider_class
        return provider_module.Provider
    AttributeError: 'module' object has no attribute 'Provider'```
    
  • Typing [Fixed #1489!]

    Typing [Fixed #1489!]

    What does this change?

    Added type annotation hints to all functions/classes in faker!

    What was wrong

    faker did not include type annotations (issue #1489).

    How this fixes it

    • Added automatic type annotations with monkeytype (https://monkeytype.readthedocs.io/en/latest/) for all files in which it did not throw errors.
    • Manual linter fixes.
    • Manual fixes of missing type annotations or unknown type annotations (e.g. type None). Did a lot of code analysis myself, but would also like to credit @nicarl for his earlier work on type annotations (e.g. in documentory.py and generator.py).
    • mypy compliant (mypy -m faker). Also added mypy -m faker test to tox.ini!
    • flake8 compliant (flake8 faker tests)
    • isort compliant (python3 -m isort --check-only --diff .)
  • 8.7.0: pytest is failing

    8.7.0: pytest is failing

    • Faker version: 8.7.0
    • OS: Linux/x86_64

    Brief summary of the issue goes here.

    Steps to reproduce

    • "python setup.py build"
    • "python setup.py install --root </install/prefix>"
    • "/usr/bin/pytest" wyth PYTHONPATH pointing to sitearch and sitelib inside </install/prefix>
    + PYTHONPATH=/home/tkloczko/rpmbuild/BUILDROOT/python-faker-8.7.0-2.fc35.x86_64/usr/lib64/python3.8/site-packages:/home/tkloczko/rpmbuild/BUILDROOT/python-faker-8.7.0-2.fc35.x86_64/usr/lib/python3.8/site-packages
    + PYTHONDONTWRITEBYTECODE=1
    + /usr/bin/pytest -ra -q --ignore tests/providers/test_ssn.py
    =========================================================================== test session starts ============================================================================
    platform linux -- Python 3.8.9, pytest-6.2.4, py-1.10.0, pluggy-0.13.1
    benchmark: 3.4.1 (defaults: timer=time.perf_counter disable_gc=False min_rounds=5 min_time=0.000005 max_time=1.0 calibration_precision=10 warmup=False warmup_iterations=100000)
    rootdir: /home/tkloczko/rpmbuild/BUILD/faker-8.7.0, configfile: setup.cfg
    plugins: Faker-8.7.0, forked-1.3.0, shutil-1.7.0, virtualenv-1.7.0, expect-1.1.0, httpbin-1.0.0, xdist-2.2.1, flake8-1.0.7, timeout-1.4.2, betamax-0.8.1, freezegun-0.4.2, case-1.5.3, isort-1.3.0, aspectlib-1.5.2, asyncio-0.15.1, toolbox-0.5, xprocess-0.17.1, aiohttp-0.3.0, checkdocs-2.7.0, mock-3.6.1, rerunfailures-9.1.1, requests-mock-1.9.3, cov-2.12.1, pyfakefs-4.5.0, cases-3.6.1, flaky-3.7.0, hypothesis-6.14.0, benchmark-3.4.1
    collected 1117 items / 2 errors / 1115 selected
    
    ================================================================================== ERRORS ==================================================================================
    _____________________________________________________________ ERROR collecting tests/sphinx/test_docstring.py ______________________________________________________________
    ImportError while importing test module '/home/tkloczko/rpmbuild/BUILD/faker-8.7.0/tests/sphinx/test_docstring.py'.
    Hint: make sure your test modules/packages have valid Python names.
    Traceback:
    /usr/lib64/python3.8/importlib/__init__.py:127: in import_module
        return _bootstrap._gcd_import(name[level:], package, level)
    tests/sphinx/test_docstring.py:8: in <module>
        from faker.sphinx.docstring import DEFAULT_SAMPLE_SIZE, DEFAULT_SEED, ProviderMethodDocstring, Sample
    E   ModuleNotFoundError: No module named 'faker.sphinx'
    _____________________________________________________________ ERROR collecting tests/sphinx/test_validator.py ______________________________________________________________
    ImportError while importing test module '/home/tkloczko/rpmbuild/BUILD/faker-8.7.0/tests/sphinx/test_validator.py'.
    Hint: make sure your test modules/packages have valid Python names.
    Traceback:
    /usr/lib64/python3.8/importlib/__init__.py:127: in import_module
        return _bootstrap._gcd_import(name[level:], package, level)
    tests/sphinx/test_validator.py:6: in <module>
        from faker.sphinx.validator import SampleCodeValidator
    E   ModuleNotFoundError: No module named 'faker.sphinx'
    ========================================================================= short test summary info ==========================================================================
    ERROR tests/sphinx/test_docstring.py
    ERROR tests/sphinx/test_validator.py
    !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! Interrupted: 2 errors during collection !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
    ============================================================================ 2 errors in 4.31s =============================================================================
    

    pytest is executed with --ignore tests/providers/test_ssn.py because https://github.com/joke2k/faker/issues/1454

  • Public IP blocks used with ipv4_public encompass reserved address namespaces

    Public IP blocks used with ipv4_public encompass reserved address namespaces

    The ipv4_public faker generates IP addresses from public blocks, excluding private blocks configured in IPV4_PUBLIC_NETS and IPV4_PRIVATE_NET_BLOCKS, however it often results in addresses coming from reserved spaces.

    One example is 192.0.0.145, or in general 192.0.0.0/24 addresses from reserved space, per https://en.wikipedia.org/wiki/Reserved_IP_addresses

    This clashes with many popular libraries checking whether IP is public and routable such as django-ipware.

    Steps to reproduce

    >>> startswith = False
    >>> while not startswith:
    ...   ip = fake.ipv4_public()
    ...   if ip.startswith('192.0.0'):
    ...     startswith = True
    ...     print(ip)
    ...
    192.0.0.145
    

    Expected behavior

    No address starting with 192.0.0 generated

    Actual behavior

    192.0.0.145 comes up often.

  • Add support for multiple locale data generation

    Add support for multiple locale data generation

    What does this change

    Faker can now accept multiple locales while retaining the same signature to preserve backward compatibility.

    What was wrong

    Faker can only handle a single locale.

    How this fixes it

    The new Faker proxy class will internally create locale-specific generators as needed, and then proxy calls to the generators that can accommodate the call. Generator selection logic may also be specified via weights.

    Notes

    Needless to say, there will be a performance penalty, and the severity of the penalty depends on:

    • How many locales were specified
    • How many locale-specific generators can handle a certain call
    • If a custom distribution will be used

    Fixes #691, fixes #976, partial solution-ish to #453, related to #230

  • Not possible to seed uuid4

    Not possible to seed uuid4

    It is not possible to seed the uuid4 property.

    >>> f1 = Faker()
    >>> f1.seed(4321)
    >>> print(f1.uuid4())
    4a6d35db-b61b-49ed-a225-e16bc164f7cc
    
    >>> f2 = Faker()
    >>> f2.seed(4321)
    >>> print(f2.uuid4())
    b5f05be8-2f57-4a52-9b6f-5bcd03125278
    
    

    The solution is pretty much given in: http://stackoverflow.com/questions/41186818/how-to-generate-a-random-uuid-which-is-reproducible-with-a-seed-in-python

  • Add a random image provider

    Add a random image provider

    Python Image Library is used under the hood to generate a background and drawing a polygon, while forwarding the color generation to the existing color provider.

    So as not to force a dependency on Pillow for all installs, this provider will not work in absence of this library.

    A polygon shape is chosen because its the easiest drawing method to interface with random coordinates, as opposed to ellipses or alike that constrain input parameters, while still providing easily distinguishable random images, as opposed to random noise bitmaps.

  • text-unidecode is released under the Artistic license

    text-unidecode is released under the Artistic license

    text-unidecode is released under the Artistic license v1.0, which is considered non-free by the FSF (and therefore not compatible with the GPL). I believe this clause is also of concern to commercial users of faker too:

    1. You may charge a reasonable copying fee for any distribution of this Package. You may charge any fee you choose for support of this Package. You may not charge a fee for this Package itself. However, you may distribute this Package in aggregate with other (possibly commercial) programs as part of a larger (possibly commercial) software distribution provided that you do not advertise this Package as a product of your own.

    Not being able to charge a fee for the software is problematic for those of us who are contractors, for example.

    I realise there aren't really any good alternatives (unidecode is GPL licensed as pointed out in #628 , isounidecode doesn't support Python 3), so would a patch making text-unidecode an optional dependency be acceptable?

  • Add title faker

    Add title faker

    Faker is missing the equivalent to real world titles. A title consists of a number of words. The first letter of the first word is uppercase and there is no punctuation.

    For example: 'Sapiente sunt omnis'

    In applications with a database the title is usually restricted to certain number of chars. Thus the title faker allows to restrict the title char number.

    (This PR resulted from an issue with titles and email subjects which do not support newlines. For reference see liqd/adhocracy4#200)

  • Add length constraints for providers

    Add length constraints for providers

    What does this changes

    This PR works on https://github.com/joke2k/faker/issues/1506 by adding maximal and minimal lenght for providers

    Continuation of https://github.com/joke2k/faker/pull/1615

  • pydecimal provider with positive=True sometimes returns zero

    pydecimal provider with positive=True sometimes returns zero

    • Faker version: 13.3.4
    • OS: Ubuntu 18.04.6

    Call pydecimal with positive=True, and it'll sometimes return a zero.

    Steps to reproduce

    Here's an example:

    import faker
    
    f = faker.Faker()
    are_zero = [f.pydecimal(positive=True, right_digits=0) == 0 for _ in range(1000)]
    print(any(are_zero))
    

    Expected behavior

    It should always print False.

    Actual behavior

    Sometimes it's True with f.pydecimal() returning zero.

  • Faker produces different results when using pytest even with seed

    Faker produces different results when using pytest even with seed

    • Faker version: 13.11
    • OS: Mac OS Monterey
    • Computer: MacBook Pro (14-inch, 2021)
    • pytest version: 6.2.5

    When using faker with pytest it produces one result when I call the test file directly vs when I just ran pytest over all my tests.

    Steps to reproduce

    In total you should have 3 test files, two in tests and one in tests/. They should all contain the same code.

    1. Create a tests folder and add a test file to it using Faker, seed it. (see my code below)
    2. Create a copy of that test in the same tests folder
    3. Create a new folder in tests and copy the test there too.
    4. Run the test directly using pytest tests/<new folder>/<test>
    5. Run all your tests by running pytest

    code:

    from faker import Faker
    
    fake = Faker()
    Faker.seed(0)
    elements = [1, 2, 3, 4, 5]
    def test_select_element():
        assert fake.random_element(elements) == 4
    

    Expected behavior

    The results from step 4 and 5 should be the same.

    Actual behavior

    The results from step 4 and 5 are different. The faker in the new folder returns a different result.(in my case 1)

  • Faker returns one value when using multiple locales

    Faker returns one value when using multiple locales

    • Faker version: 13.11
    • OS: Mac OS Monterey Computer: MacBook Pro (14-inch, 2021)

    Brief summary of the issue goes here. If using multiple locales, faker only makes one choice. This only happens when you select multiple locales

    Steps to reproduce

    from faker import Faker
    
    fake = Faker(["en_GB", "fr_FR", "en_IN"])
    Faker.seed(0)
    for _ in range(5):
        print(fake.date_time_this_year())
    
    

    Expected behavior

    returns

    2022-03-16 19:22:23
    2022-03-23 16:00:20
    2022-01-08 20:40:15
    2022-02-20 06:38:22
    2022-04-10 06:42:46
    

    Actual behavior

    returns

    2022-03-23 16:00:20
    2022-03-23 16:00:20
    2022-03-23 16:00:20
    2022-03-23 16:00:20
    2022-03-23 16:00:20
    
    
  • [New Provider] Add new Sport provider.

    [New Provider] Add new Sport provider.

    I was thinking of implementing a new sports provider (similar to Ruby Faker). It would generate fake data regarding basketball teams and players. Would you be interested in a PR?

  • Better biology provider

    Better biology provider

    There should be a better biology provider. The faker_biology community provider has a lot that could be added, like specific methods for genuses, families, orders, etc.

    Also, can the biology provider be incorporated into the main Faker package, so that people only need to install one package?

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splinter - python tool for testing web applications splinter is an open source tool for testing web applications using Python. It lets you automate br

May 13, 2022
Let your Python tests travel through time

FreezeGun: Let your Python tests travel through time FreezeGun is a library that allows your Python tests to travel through time by mocking the dateti

May 15, 2022
HTTP client mocking tool for Python - inspired by Fakeweb for Ruby

HTTPretty 1.0.5 HTTP Client mocking tool for Python created by Gabriel Falcão . It provides a full fake TCP socket module. Inspired by FakeWeb Github

May 11, 2022
A utility for mocking out the Python Requests library.

Responses A utility library for mocking out the requests Python library. Note Responses requires Python 2.7 or newer, and requests >= 2.0 Installing p

May 17, 2022
A test fixtures replacement for Python

factory_boy factory_boy is a fixtures replacement based on thoughtbot's factory_bot. As a fixtures replacement tool, it aims to replace static, hard t

May 16, 2022
Mixer -- Is a fixtures replacement. Supported Django, Flask, SqlAlchemy and custom python objects.

The Mixer is a helper to generate instances of Django or SQLAlchemy models. It's useful for testing and fixture replacement. Fast and convenient test-

May 20, 2022
Coroutine-based concurrency library for Python

gevent Read the documentation online at http://www.gevent.org. Post issues on the bug tracker, discuss and ask open ended questions on the mailing lis

May 16, 2022
Radically simplified static file serving for Python web apps

WhiteNoise Radically simplified static file serving for Python web apps With a couple of lines of config WhiteNoise allows your web app to serve its o

May 18, 2022
livereload server in python (MAINTAINERS NEEDED)

LiveReload Reload webpages on changes, without hitting refresh in your browser. Installation python-livereload is for web developers who know Python,

May 8, 2022
A screamingly fast Python 2/3 WSGI server written in C.

bjoern: Fast And Ultra-Lightweight HTTP/1.1 WSGI Server A screamingly fast, ultra-lightweight WSGI server for CPython 2 and CPython 3, written in C us

May 20, 2022
Waitress - A WSGI server for Python 2 and 3

Waitress Waitress is a production-quality pure-Python WSGI server with very acceptable performance. It has no dependencies except ones which live in t

May 9, 2022
Python HTTP Server
Python HTTP Server

Python HTTP Server Preview Languange and Code Editor: How to run? Download the zip first. Open the http.py and wait 1-2 seconds. You will see __pycach

Oct 21, 2021
PyQaver is a PHP like WebServer for Python.

PyQaver is a PHP like WebServer for Python.

Apr 25, 2022
Robyn is an async Python backend server with a runtime written in Rust, btw.

Robyn is an async Python backend server with a runtime written in Rust, btw. Python server running on top of of Rust Async RunTime. Installation

May 17, 2022
Faker is a Python package that generates fake data for you.

Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in yo

May 19, 2022
Faker is a Python package that generates fake data for you.

Faker is a Python package that generates fake data for you. Whether you need to bootstrap your database, create good-looking XML documents, fill-in yo

May 18, 2022