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new 5250841 [SPARK-33256][PYTHON][DOCS] Clarify PySpark follows NumPy
documentation style
5250841 is described below
commit 5250841537d7a8c54fb451748e2a21d3bcc5d966
Author: HyukjinKwon <[email protected]>
AuthorDate: Sun Dec 6 01:22:24 2020 -0800
[SPARK-33256][PYTHON][DOCS] Clarify PySpark follows NumPy documentation
style
### What changes were proposed in this pull request?
This PR adds few lines about docstring style to document that PySpark
follows [NumPy documentation
style](https://numpydoc.readthedocs.io/en/latest/format.html). We all completed
the migration to NumPy documentation style at SPARK-32085.
Ideally we should have a page like
https://pandas.pydata.org/docs/development/contributing_docstring.html but I
would like to leave it as a future work.
### Why are the changes needed?
To tell developers that PySpark now follows NumPy documentation style.
### Does this PR introduce _any_ user-facing change?
No, it's a change in unreleased branches yet.
### How was this patch tested?
Manually tested via `make clean html` under `python/docs`:
Closes #30622 from HyukjinKwon/SPARK-33256.
Authored-by: HyukjinKwon <[email protected]>
Signed-off-by: Dongjoon Hyun <[email protected]>
---
python/docs/source/development/contributing.rst | 5 +++--
1 file changed, 3 insertions(+), 2 deletions(-)
diff --git a/python/docs/source/development/contributing.rst
b/python/docs/source/development/contributing.rst
index 2b62c95..a41b8a1 100644
--- a/python/docs/source/development/contributing.rst
+++ b/python/docs/source/development/contributing.rst
@@ -123,11 +123,12 @@ Annotations can be validated using ``dev/lint-python``
script or by invoking myp
-Code Style Guide
-----------------
+Code and Docstring Guide
+----------------------------------
Please follow the style of the existing codebase as is, which is virtually PEP
8 with one exception: lines can be up
to 100 characters in length, not 79.
+For the docstring style, PySpark follows `NumPy documentation style
<https://numpydoc.readthedocs.io/en/latest/format.html>`_.
Note that the method and variable names in PySpark are the similar case is
``threading`` library in Python itself where
the APIs were inspired by Java. PySpark also follows `camelCase` for exposed
APIs that match with Scala and Java.
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