Fokko commented on pull request #29122:
URL: https://github.com/apache/spark/pull/29122#issuecomment-712753625
Fixed the voilations:
```
./python/pyspark/ml/regression.py:1743:40: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
quantileProbabilities=list([0.01, 0.05, 0.1, 0.25, 0.5,
0.75, 0.9, 0.95, 0.99]),
^
./python/pyspark/ml/regression.py:1761:41: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
quantileProbabilities=list([0.01, 0.05, 0.1, 0.25, 0.5,
0.75, 0.9, 0.95, 0.99]),
^
./python/pyspark/ml/tuning.py:511:46: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def __init__(self, bestModel, avgMetrics=[], subModels=None):
^
./python/pyspark/ml/tuning.py:871:53: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def __init__(self, bestModel, validationMetrics=[], subModels=None):
^
./python/pyspark/resource/profile.py:35:63: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def __init__(self, _java_resource_profile=None, _exec_req={},
_task_req={}):
^
./python/pyspark/resource/profile.py:35:77: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def __init__(self, _java_resource_profile=None, _exec_req={},
_task_req={}):
^
./python/pyspark/sql/functions.py:2479:36: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def from_json(col, schema, options={}):
^
./python/pyspark/sql/functions.py:2527:26: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def to_json(col, options={}):
^
./python/pyspark/sql/functions.py:2567:34: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def schema_of_json(json, options={}):
^
./python/pyspark/sql/functions.py:2597:32: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def schema_of_csv(csv, options={}):
^
./python/pyspark/sql/functions.py:2623:25: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def to_csv(col, options={}):
^
./python/pyspark/sql/functions.py:2934:35: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def from_csv(col, schema, options={}):
^
./python/pyspark/sql/avro/functions.py:29:47: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def from_avro(data, jsonFormatSchema, options={}):
^
./dev/sparktestsupport/modules.py:34:97: B006 Do not use mutable data
structures for argument defaults. They are created during function definition
time. All calls to the function reuse this one instance of that data structure,
persisting changes between them.
def __init__(self, name, dependencies, source_file_regexes,
build_profile_flags=(), environ={},
^
14 B006 Do not use mutable data structures for argument defaults. They
are created during function definition time. All calls to the function reuse
this one instance of that data structure, persisting changes between them.
14
1
```
Furthermore:
- Added `flake8-bugbear` to the CI. This is a well known additional set of
rules next to flake8: https://github.com/pycqa/flake8-bugbear
- Added the `B006` rule, which is the mutable arguments rule :)
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