python-fudge 1.1.0-1 source package in Ubuntu

Changelog

python-fudge (1.1.0-1) unstable; urgency=low

  [ Jakub Wilk ]
  * Use canonical URIs for Vcs-* fields.

  [ Jan Dittberner ]
  * Use PyPI redirector for watch file
  * fix package description mismatch in debian/control
  * Apply patch by Juan Picca to have fixed timestamps to make the build
    reproducible (Closes: #788501)
  * Bump Standards-Version to 3.9.6 (no changes)
  * Run wrap-and-sort
  * Switch to dh-python/pybuild
  * Update copyright years
  * Build documentation in dh_auto_build step
  * New upstream version
  * Remove deletion of MacOS X files from dh_override_auto_clean,
    because upstream removed them
  * Re-Enable Python 3 tests

 -- Jan Dittberner <email address hidden>  Wed, 30 Dec 2015 16:17:44 +0100

Upload details

Uploaded by:
Debian Python Modules Team on 2015-12-30
Uploaded to:
Sid
Original maintainer:
Debian Python Modules Team
Architectures:
all
Section:
python
Urgency:
Low Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Eoan release on 2019-04-18 universe python
Disco release on 2018-10-30 universe python
Cosmic release on 2018-05-01 universe python
Bionic release on 2017-10-24 universe python
Artful release on 2017-04-20 universe python
Xenial release on 2015-12-30 universe python

Builds

Xenial: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
python-fudge_1.1.0-1.dsc 1.8 KiB 708c5bfc857d546e9a9bda916aa1500f629c03920dfdee65b2a0ed7992b458f1
python-fudge_1.1.0.orig.tar.gz 84.4 KiB eba59a926fa1df1ab6dddd69a7a8af21865b16cad800cb4d1af75070b0f52afb
python-fudge_1.1.0-1.debian.tar.xz 3.2 KiB 83705ad1c4eb2e1b90af8376ed970fbb9cb70726b522bb8bbd4957598f44984f

Available diffs

No changes file available.

Binary packages built by this source

python-fudge: Python 2 module for using fake objects for tests

 Fudge is a Python module for using fake objects (mocks and stubs) to
 test real ones.
 .
 In readable Python code, you declare what methods are available on
 your fake and how they should be called. Then you inject that into
 your application and start testing. This declarative approach means
 you don’t have to record and playback actions and you don’t have to
 inspect your fakes after running code. If the fake object was used
 incorrectly then you’ll see an informative exception message with a
 traceback that points to the culprit.
 .
 Fudge was inspired by Mocha which is a simpler version of jMock. But
 unlike Mocha, Fudge does not automatically hijack real objects; you
 explicitly patch them in your test. And unlike jMock, Fudge is only
 as strict about expectations as you want it to be. If the type of
 arguments sent to the fake method aren’t important then you don’t
 have to declare an expectation for them.
 .
 This is the Python 2 version of the package.

python-fudge-doc: Python module for using fake objects for tests, documentation package

 Fudge is a Python module for using fake objects (mocks and stubs) to
 test real ones.
 .
 In readable Python code, you declare what methods are available on
 your fake and how they should be called. Then you inject that into
 your application and start testing. This declarative approach means
 you don’t have to record and playback actions and you don’t have to
 inspect your fakes after running code. If the fake object was used
 incorrectly then you’ll see an informative exception message with a
 traceback that points to the culprit.
 .
 Fudge was inspired by Mocha which is a simpler version of jMock. But
 unlike Mocha, Fudge does not automatically hijack real objects; you
 explicitly patch them in your test. And unlike jMock, Fudge is only
 as strict about expectations as you want it to be. If the type of
 arguments sent to the fake method aren’t important then you don’t
 have to declare an expectation for them.
 .
 This is the documentation of python-fudge.

python3-fudge: Python 3 module for using fake objects for tests

 Fudge is a Python module for using fake objects (mocks and stubs) to
 test real ones.
 .
 In readable Python code, you declare what methods are available on
 your fake and how they should be called. Then you inject that into
 your application and start testing. This declarative approach means
 you don’t have to record and playback actions and you don’t have to
 inspect your fakes after running code. If the fake object was used
 incorrectly then you’ll see an informative exception message with a
 traceback that points to the culprit.
 .
 Fudge was inspired by Mocha which is a simpler version of jMock. But
 unlike Mocha, Fudge does not automatically hijack real objects; you
 explicitly patch them in your test. And unlike jMock, Fudge is only
 as strict about expectations as you want it to be. If the type of
 arguments sent to the fake method aren’t important then you don’t
 have to declare an expectation for them.
 .
 This is the Python 3 version of the package.