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❄ A flake8 plugin that helps you to simplify code

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flake8-simplify

A flake8 plugin that helps you simplify your code.

Installation

Install with pip:

pip install flake8-simplify

Python 3.6 to 3.8 are supported.

Usage

Just call flake8 . in your package or flake your.py:

$ flake8 .
./foo/__init__.py:690:12: SIM101 Multiple isinstance-calls which can be merged into a single call for variable 'other'

Rules

Python-specific rules:

Simplifying Comparations:

  • SIM201: Use 'a != b' instead of 'not a == b' (example)
  • SIM202: Use 'a == b' instead of 'not a != b' (example)
  • SIM203: Use 'a not in b' instead of 'not (a in b)' (example)
  • SIM204: Use 'a >= b' instead of 'not (a < b)' (example)
  • SIM205: Use 'a > b' instead of 'not (a <= b)' (example)
  • SIM206: Use 'a <= b' instead of 'not (a > b)' (example)
  • SIM207: Use 'a < b' instead of 'not (a <= b)' (example)
  • SIM208: Use 'a' instead of 'not (not a)' (example)
  • SIM210: Use 'bool(a)' instead of 'True if a else False' (example)
  • SIM211: Use 'not a' instead of 'False if a else True' (example)
  • SIM212: Use 'a if a else b' instead of 'b if not a else a' (example)
  • SIM220: Use 'False' instead of 'a and not a' (example)
  • SIM221: Use 'True' instead of 'a or not a' (example)
  • SIM222: Use 'True' instead of '... or True' (example)
  • SIM223: Use 'False' instead of '... and False' (example)
  • SIM300: Use 'age == 42' instead of '42 == age' (example)

Simplifying usage of dictionaries:

  • SIM401: Use 'a_dict.get(key, "default_value")' instead of an if-block (example)
  • SIM118: Use 'key in dict' instead of 'key in dict.keys()' (example)

General Code Style:

You might have good reasons to ignore some rules. To do that, use the standard Flake8 configuration. For example, within the setup.cfg file:

[flake8]
ignore = SIM106, SIM113, SIM119

Examples

SIM101

# Bad
isinstance(a, int) or isinstance(a, float)

# Good
isinstance(a, (int, float))

SIM102

# Bad
if a:
    if b:
        c

# Good
if a and b:
    c

SIM107

# Bad: This example returns 3!
def foo():
    try:
        1 / 0
        return "1"
    except:
        return "2"
    finally:
        return "3"


# Good
def foo():
    return_value = None
    try:
        1 / 0
        return_value = "1"
    except:
        return_value = "2"
    finally:
        return_value = "3"  # you might also want to check if "except" happened
    return return_value

SIM108

# Bad
if a:
    b = c
else:
    b = d

# Good
b = c if a else d

SIM109

# Bad
if a == b or a == c:
    d

# Good
if a in [b, c]:
    d

SIM110

# Bad
for x in iterable:
    if check(x):
        return True
return False

# Good
return any(check(x) for x in iterable)

SIM111

# Bad
for x in iterable:
    if check(x):
        return False
return True

# Good
return all(not check(x) for x in iterable)

SIM112

# Bad
os.environ["foo"]
os.environ.get("bar")

# Good
os.environ["FOO"]
os.environ.get("BAR")

SIM113

Using enumerate in simple cases like the loops below is a tiny bit easier to read as the reader does not have to figure out where / when the loop variable is incremented (or if it is incremented in multiple places).

# Bad
idx = 0
for el in iterable:
    ...
    idx += 1

# Good
for idx, el in enumerate(iterable):
    ...

SIM114

# Bad
if a:
    b
elif c:
    b

# Good
if a or c:
    b

SIM115

# Bad
f = open(...)
...  # (do something with f)
f.close()

# Good
with open(...) as f:
    ...  # (do something with f)

SIM116

# Bad
if a == "foo":
    return "bar"
elif a == "bar":
    return "baz"
elif a == "boo":
    return "ooh"
else:
    return 42

# Good
mapping = {"foo": "bar", "bar": "baz", "boo": "ooh"}
return mapping.get(a, 42)

SIM117

# Bad
with A() as a:
    with B() as b:
        print("hello")

# Good
with A() as a, B() as b:
    print("hello")

Thank you for pointing this one out, Aaron Gokaslan!

SIM118

# Bad
key in a_dict.keys()

# Good
key in a_dict

Thank you for pointing this one out, Aaron Gokaslan!

SIM119

Dataclasses were introduced with PEP 557 in Python 3.7. The main reason not to use dataclasses is to support legacy Python versions.

Dataclasses create a lot of the boilerplate code for you:

  • __init__
  • __eq__
  • __hash__
  • __str__
  • __repr__

A lot of projects use them:

SIM120

# Bad
class FooBar(object):
    ...

# Good
class FooBar:
    ...

Both notations are equivalent in Python 3, but the second one is shorter.

SIM201

# Bad
not a == b

# Good
a != b

SIM202

# Bad
not a != b

# Good
a == b

SIM203

# Bad
not a in b

# Good
a not in b

SIM204

# Bad
not a < b

# Good
a >= b

SIM205

# Bad
not a <= b

# Good
a > b

SIM206

# Bad
not a > b

# Good
a <= b

SIM207

# Bad
not a >= b

# Good
a < b

SIM208

# Bad
not (not a)

# Good
a

SIM210

# Bad
True if a else False

# Good
bool(a)

SIM211

# Bad
False if a else True

# Good
not a

SIM212

# Bad
b if not a else a

# Good
a if a else b

SIM220

# Bad
a and not a

# Good
False

SIM221

# Bad
a or not a

# Good
True

SIM222

# Bad
... or True

# Good
True

SIM223

# Bad
... and False

# Good
False

SIM300

# Bad; This is called a "Yoda-Condition"
42 == age

# Good
age == 42

SIM401

# Bad
if key in a_dict:
    value = a_dict[key]
else:
    value = "default_value"

# Good
thing = a_dict.get(key, "default_value")

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