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authorCharles Harris <charlesr.harris@gmail.com>2021-09-26 11:45:02 -0600
committerGitHub <noreply@github.com>2021-09-26 11:45:02 -0600
commit7e8285ba48179b19b4d251ac3447569141c7e8f7 (patch)
tree684dd5c5c242d288c505cc08778f396f0c080082
parent5ae01fac1adb6818d997d7cfe46a292836158a42 (diff)
parent9ccba44069580d2566aac1e226308263ddfb1d78 (diff)
downloadnumpy-7e8285ba48179b19b4d251ac3447569141c7e8f7.tar.gz
Merge pull request #19962 from rkern/doc/no-tdd
DOC: Remove overstated TDD evangelism.
-rw-r--r--doc/TESTS.rst.txt8
1 files changed, 1 insertions, 7 deletions
diff --git a/doc/TESTS.rst.txt b/doc/TESTS.rst.txt
index ba09aa800..d048a4569 100644
--- a/doc/TESTS.rst.txt
+++ b/doc/TESTS.rst.txt
@@ -16,13 +16,7 @@ Our goal is that every module and package in NumPy
should have a thorough set of unit
tests. These tests should exercise the full functionality of a given
routine as well as its robustness to erroneous or unexpected input
-arguments. Long experience has shown that by far the best time to
-write the tests is before you write or change the code - this is
-`test-driven development
-<https://en.wikipedia.org/wiki/Test-driven_development>`__. The
-arguments for this can sound rather abstract, but we can assure you
-that you will find that writing the tests first leads to more robust
-and better designed code. Well-designed tests with good coverage make
+arguments. Well-designed tests with good coverage make
an enormous difference to the ease of refactoring. Whenever a new bug
is found in a routine, you should write a new test for that specific
case and add it to the test suite to prevent that bug from creeping