# flake8-pie [![CircleCI](https://circleci.com/gh/sbdchd/flake8-pie.svg?style=svg)](https://circleci.com/gh/sbdchd/flake8-pie) [![pypi](https://img.shields.io/pypi/v/flake8-pie.svg)](https://pypi.org/project/flake8-pie/)
> A flake8 extension that implements misc. lints
## lints
### PIE781: assign-and-return
Based on Clippy's
[`let_and_return`](https://rust-lang.github.io/rust-clippy/master/index.html#let_and_return)
and Microsoft's TSLint rule
[`no-unnecessary-local-variable`](https://github.com/Microsoft/tslint-microsoft-contrib).
For more info on the structure of this lint, see the [accompanying blog
post](https://steve.dignam.xyz/2018/12/16/creating-a-flake8-lint/).
#### examples
```python
# error
def foo():
x = bar()
return x
# allowed
def foo():
x, _ = bar()
return x
```
### PIE783: celery-explicit-names
Warn about [Celery](https://pypi.org/project/celery/) task definitions that don't have explicit names.
Note: this lint is kind of naive considering any decorator with a `.task()`
method or any decorator called `shared_task()` a Celery decorator.
#### examples
```python
# error
@app.task()
def foo():
pass
# ok
@app.task(name="app_name.tasks.foo")
def foo():
pass
```
### PIE784: celery-explicit-crontab-args
The `crontab` class provided by Celery has some default args that are
suprising to new users. Specifically, `crontab(hour="0,12")` won't run a task
at midnight and noon, it will run the task at every minute during those two
hours. This lint makes that call an error, forcing you to write
`crontab(hour="0, 12", minute="*")`.
Additionally, the lint is a bit more complex in that it requires you specify
every smaller increment than the largest time increment you provide. So if you
provide `days_of_week`, then you need to provide `hour`s and `minute`s
explicitly.
Note: if you like the default behavior of `crontab()` then you can either
disable this lint or pass `"*"` for the `kwarg` value, e.g., `minutes="*"`.
Also, since this lint is essentially a naive search for calls to a
`crontab()` function, if you have a function named the same then this will
cause false positives.
### PIE785: celery-require-tasks-expire
Celery tasks can bunch up if they don't have expirations.
This enforces specifying expirations in both the celery beat config dict and
in `.apply_async()` calls.
The same caveat applies about how this lint is naive.
### PIE786: precise-exception-handlers
Be precise in what exceptions you catch. Bare `except:` handlers, catching `BaseException`, or catching `Exception` can lead to unexpected bugs.
#### examples
```python
# error
try:
save_file(name="export.csv")
except:
pass
# error
try:
save_file(name="export.csv")
except BaseException:
pass
# error
try:
save_file(name="export.csv")
except Exception:
pass
# error
try:
save_file(name="export.csv")
except (ValueError, Exception):
pass
# ok
try:
save_file(name="export.csv")
except OSError:
pass
```
### PIE787: no-len-condition
Empty collections are fasley in Python so calling `len()` is unnecessary when
checking for emptiness in an if statement/expression.
Comparing to explicit scalars is allowed.
```python
# error
if len(foo): ...
if not len(foo): ...
# ok
if foo: ...
if not foo: ...
if len(foo) > 0: ...
if len(foo) == 0: ...
```
### PIE788: no-bool-condition
If statements/expressions evalute the truthiness of the their test argument,
so calling `bool()` is unnecessary.
Comparing to `True`/`False` is allowed.
```python
# error
if bool(foo): ...
if not bool(foo): ...
# ok
if foo: ...
if not foo: ...
if bool(foo) is True: ...
if bool(foo) is False: ...
```
### PIE789: prefer-isinstance-type-compare
Using `type()` doesn't take into account subclassess and type checkers won't
refine the type, use `isinstance` instead.
```python
# error
if type(foo) == str: ...
if type(foo) is str: ...
if type(foo) in [int, str]: ...
# ok
if isinstance(foo, str): ...
if isinstance(foo, (int, str)): ...
```
### PIE790: no-unnecessary-pass
`pass` is unnecessary when definining a `class` or function with an empty
body.
```python
# error
class BadError(Exception):
"""
some doc comment
"""
pass
def foo() -> None:
"""
some function
"""
pass
# ok
class BadError(Exception):
"""
some doc comment
"""
def foo() -> None:
"""
some function
"""
```
### PIE791: no-pointless-statements
Comparisions without an assignment or assertion are probably a typo.
```python
# error
"foobar" in data
res.json() == []
user.is_authenticated() is True
# ok
assert "foobar" in data
foo = res.json() == []
use.is_authenticated()
```
### PIE792: no-inherit-object
Inheriting from `object` isn't necessary in Python 3.
```python
# error
class Foo(object):
...
# ok
class Foo:
...
```
### PIE793: prefer-dataclass
Attempts to find cases where the `@dataclass` decorator is unintentionally
missing.
```python
# error
class Foo:
z: dict[int, int]
def __init__(self) -> None: ...
class Bar:
x: list[str]
# ok
class Bar(Foo):
z: dict[int, int]
@dataclass
class Bar:
x: list[str]
```
### PIE794: dupe-class-field-definitions
Finds duplicate definitions for the same field, which can occur in large ORM
model definitions.
```python
# error
class User(BaseModel):
email = fields.EmailField()
# ...80 more properties...
email = fields.EmailField()
# ok
class User(BaseModel):
email = fields.EmailField()
# ...80 more properties...
```
### PIE795: prefer-stdlib-enums
Instead of defining various constant properties on a class, use the stdlib
enum which typecheckers support for type refinement.
```python
# error
class Foo:
A = "A"
B = "B"
C = "C"
# ok
import enum
class Foo(enum.Enum):
A = "A"
B = "B"
C = "C"
```
### PIE796: prefer-unique-enums
By default the stdlib enum allows multiple field names to map to the same
value, this lint requires each enum value be unique.
```python
# error
class Foo(enum.Enum):
A = "A"
B = "B"
C = "C"
D = "C"
# ok
class Foo(enum.Enum):
A = "A"
B = "B"
C = "C"
D = "D"
```
### PIE797: no-unnecessary-if-expr
Call `bool()` directly rather than reimplementing its functionality.
```python
# error
foo(is_valid=True if buzz() else False)
# ok
foo(is_valid=bool(buzz()))
```
### PIE798: no-unnecessary-class
Instead of using class to namespace functions, use a module.
```python
# error
class UserManager:
class User(NamedTuple):
name: str
@classmethod
def update_user(cls, user: User) -> None:
...
@staticmethod
def sync_users() -> None:
...
# ok
class User(NamedTuple):
name: str
def update_user(user: User) -> None:
...
def sync_users() -> None:
...
```
### PIE799: prefer-col-init
Check that values are passed in when collections are created rather than
creating an empty collection and then inserting.
```python
# error
bars = []
bar = bar()
bars.append(bar)
# ok
bar = bar()
bars = [bar]
# error
s = deque()
s.append(foo)
# ok
s = deque([foo])
```
### PIE800: no-unnecessary-spread
Check for unnecessary dict unpacking.
```python
# error
{**foo, **{"bar": 10}}
# ok
{**foo, "bar": 10}
```
### PIE801: prefer-simple-return
Return boolean expressions directly instead of returning `True` and `False`.
```python
# error
def main():
if foo > 5:
return True
return False
# error
def main():
if foo > 5:
return True
else:
return False
# ok
def main():
return foo > 5
```
### PIE802: prefer-simple-any-all
Remove unnecessary comprehensions for `any` and `all`
```python
# error
any([x.id for x in bar])
all([x.id for x in bar])
# ok
all(x.id for x in bar)
any(x.id for x in bar)
any({x.id for x in bar})
```
### PIE803: prefer-logging-interpolation
Don't format strings before logging. Let `logging` interpolate arguments.
This allows Sentry to aggregate logs, prevents raising exceptions if interpolation fails, and improves performance if the log level is disabled. See ["PyCQA/pylint#1788"](https://github.com/PyCQA/pylint/issues/1788#issuecomment-461279687).
```python
# error
logger.info("Login error for %s" % user)
logger.info("Login error for %s, %s" % (user_id, name))
# error
logger.info("Login error for {}".format(user))
logger.info("Login error for {}, {}".format(user_id, name))
# error
logger.info(f"Login error for {user}")
logger.info(f"Login error for {user_id}, {name}")
# ok
logger.info("Login error for %s", user)
logger.info("Login error for %s, %s", user_id, name)
```
### PIE804: no-unnecessary-dict-kwargs
As long as the keys of the dict are valid Python identifier names, we can safely
remove the surrounding dict.
```python
# error
foo(**{"bar": True})
# ok
foo(bar=True)
foo(**buzz)
foo(**{"bar foo": True})
```
## dev
```shell
# install dependencies
poetry install
s/lint
s/test
```
### PIE805: prefer-literal
Currently only checks for byte string literals.
```python
# error
"foo".encode()
# ok
b"foo"
"😀".encode()
```
### PIE806: no-assert-except
Instead of `assert`ing and catching the exception, use an if statement.
```python
# error
try:
assert "@" in bar
except AssertionError:
...
# ok
if "@" in bar:
...
```
### PIE807: prefer-list-builtin
`lambda: []` is equivalent to the builtin `list`
```python
# error
@dataclass
class Foo:
foo: List[str] = field(default_factory=lambda: [])
# ok
@dataclass
class Foo:
foo: List[str] = field(default_factory=list)
```
### PIE808: prefer-simple-range
We can leave out the first argument to `range` in some cases since the default
start position is 0.
```python
# err
range(0, 10)
# ok
range(10)
range(x, 10)
range(0, 10, x)
```
### PIE809: django-prefer-bulk
Bulk create multiple objects instead of executing O(N) queries.
```python
# error
[Item.objects.create(item) for item in items]
# error
[Item.objects.create(item) for item in [bar for bar in buzz]]
# error
(Item.objects.create(item) for item in items)
# ok
Item.objects.insert(items)
Item.objects.create(item)
```
## development
### examining the AST
You can use `astpretty` to dump the AST of a piece of code.
```shell
./.venv/bin/astpretty <(pbpaste)
```
### uploading a new version to [PyPi](https://pypi.org)
```shell
# increment `Flake8PieCheck.version` and pyproject.toml `version`
# build new distribution files and upload to pypi
# Note: this will ask for login credentials
rm -rf dist && poetry publish --build
```