python-fudge 1.1.1-2 source package in Ubuntu

Changelog

python-fudge (1.1.1-2) unstable; urgency=medium

  * Team upload
  * d/control: Drop the build depending package python3-nose
    (Closes: #1018499)
  * d/rules: Don't run upstream test for now
    Upstream hasn't updated the source for years and the nose based
    testing would be needed to get moved over to unittests.
    Unfortunately that takes some effort, OTOH there isn't much breakage to be
    expected.
  * d/{control,rules}: Switch to dh-sequence-python3
  * python-fudge-doc: Use dh_sphinxdoc sequencer
  * d/control: Update Standards-Version to 4.6.1
    No further changes needed.

 -- Carsten Schoenert <email address hidden>  Sat, 22 Oct 2022 10:12:38 +0200

Upload details

Uploaded by:
Debian Python Team
Uploaded to:
Sid
Original maintainer:
Debian Python Team
Architectures:
all
Section:
python
Urgency:
Medium Urgency

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Builds

Lunar: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
python-fudge_1.1.1-2.dsc 2.1 KiB b42e7354748dcca91461cb1acfd7508141081635151b6d179a0da3498cffedad
python-fudge_1.1.1.orig.tar.gz 85.6 KiB d9929d87bb38711112734d99a2c7ada5dc39ef67b758b1e55f4c779c3634efdc
python-fudge_1.1.1-2.debian.tar.xz 7.6 KiB e1f882fe2a56187f80cee6ef6a1272ef9bff1d513d11630a892fe53dc3059fda

Available diffs

No changes file available.

Binary packages built by this source

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.