Style checker for fast.ai coding conventions
Project description
fastaistyle
pip install fastaistyle
A style checker that enforces the fast.ai coding style—a compact, readable approach to Python that keeps more code visible on screen and reduces cognitive load.
Why This Style?
Most style guides optimize for the wrong thing. They add vertical space, mandate verbose names, and scatter related code across many lines. The result? You see less code at once, which means more scrolling, more context-switching, and more mental effort to understand what's happening.
The fast.ai style takes a different approach, rooted in decades of experience with APL, J, K, and scientific programming. The core insight comes from Kenneth Iverson: "brevity facilitates reasoning."
Your Brain Can Only Hold So Much
When you're reading code, your working memory is limited. If a function spans 50 lines, you can't see the whole thing at once. You scroll down, forget what was at the top, scroll back up. Each scroll is a context switch. Each context switch costs mental energy.
But if that same function fits in 15 lines? You see the whole picture. Your eyes can jump between related parts instantly. Patterns become obvious. Bugs stand out.
This isn't about cramming code together—it's about removing unnecessary vertical space so your brain can do what it's good at: recognizing patterns across visible information.
One Line, One Idea
The goal is density without confusion. Each line should express one complete thought:
# Good: you see the whole pattern at once
if not data: return None
for item in items: process(item)
def _is_ready(self): return self._ready.is_set()
# Bad: same logic, but now it's 6 lines instead of 3
if not data:
return None
for item in items:
process(item)
def _is_ready(self):
return self._ready.is_set()
When the body is simple, keep it on the same line. Save vertical space for code that actually needs it.
Names Should Be Short (When Used Often)
This follows "Huffman coding" for variable names—frequently used things get short names:
# Good: conventional, recognizable
img, i, msg, ctx
# Bad: verbose for no benefit
image_data, loop_index, message_object, context_instance
Domain experts recognize nll (negative log likelihood) instantly. Spelling it out doesn't help them, and the extra characters push code off the right edge of the screen.
Installation
pip install fastaistyle
Or install from source:
git clone https://github.com/AnswerDotAI/fastaistyle
cd fastaistyle
pip install -e .
Usage
Check the current directory:
chkstyle
Check a specific path:
chkstyle path/to/code/
Check multiple files/folders in one run:
chkstyle path/to/code tests unit.py
Skip folders matching a regex (must match the whole folder name):
chkstyle --skip-folder-re 'test.*|migrations|vendor'
Skip specific folders by name/path (repeatable):
chkstyle --skip-path vendor --skip-path src/generated
The checker prints violations with file paths, line numbers, the offending code, and a short fix hint. When violations are found, it also prints a reminder to prioritize clarity and match the spirit of the style guide.
Jupyter Notebook Support
chkstyle automatically checks .ipynb files alongside .py files. For notebooks, violations show the cell ID and line number within the cell:
# notebook.ipynb:cell[abc123]:3: lhs assignment annotation
x: int = 1
Configuration
Configure chkstyle in your pyproject.toml:
[tool.chkstyle]
skip-folder-re = "test.*|migrations|vendor"
skip_paths = ["vendor", "src/generated"]
Command-line arguments override config file settings.
What It Checks
dict literal with 3+ identifier keys
Use dict() for keyword-like keys—it's easier to scan and produces cleaner diffs.
# Bad
payload = {"host": host, "port": port, "timeout": timeout}
# Good
payload = dict(host=host, port=port, timeout=timeout)
single-statement body not one-liner
If the body is one simple statement, keep it on the header line.
# Bad
if ready:
return True
# Good
if ready: return True
single-line docstring uses triple quotes
Triple quotes are for multi-line strings. Single-line docstrings should use regular quotes.
# Bad
def foo():
"""Return the value."""
return x
# Good
def foo():
"Return the value."
return x
multi-line from-import
If it fits on one line, keep it on one line.
# Bad
from os import (
path,
environ,
)
# Good
from os import path, environ
consecutive short imports
If you have a run of short import foo lines, combine them.
# Bad
import os
import sys
import pathlib
# Good
import os, sys, pathlib
unused import
Remove imports that are never referenced.
# Bad
import os
# Good
import os
print(os.getcwd())
Imports named in a simple static __all__ count as used. Package __init__.py files are exempt from this rule so re-export modules stay quiet.
For notebooks, unused import is checked across #| export / #| exports cells as one exported module. If an exported-cell import is only referenced from non-exported cells, chkstyle asks you to move it into a non-exported imports cell, recommending the first non-exported cell that already has imports when it can find one.
closing bracket on its own line
Don't leave a bare closing ), ], or } on a line by itself.
# Bad
items = [
one,
two,
]
# Good
items = [
one,
two]
continuation line indent
Continuation lines should be indented exactly 4 spaces beyond the line that opened the block.
# Bad
result = call(
first_arg,
second_arg)
# Good
result = call(
first_arg,
second_arg)
line >160 chars
Wrap at a natural boundary: argument lists, binary operators, or strings. 160 is the hard limit, but aim for ~140 (or ~120 when practical). Long lines are only exempt when the extra width mainly comes from string literal content.
semicolon statement separator
Don't use ; to combine statements. Use separate lines.
inefficient multiline expression
If the content would fit in fewer lines, condense it.
# Bad
result = call(
a,
b,
c,
)
# Good
result = call(a, b, c)
lhs assignment annotation
Avoid x: int = 1 in normal code. Put type hints on function parameters and return values instead. The exception is dataclass fields, where annotations are required.
# Bad
x: int = 1
name: str = "hello"
# Good (in a function signature)
def process(x: int, name: str) -> Result: ...
nested generics depth >= 2
Keep type annotations simple. Deep nesting makes them hard to read.
# Bad
items: list[dict[str, list[int]]]
# Good
Payload = dict[str, list[int]]
items: list[Payload]
Opting Out
Sometimes you have a good reason to format code a specific way. The checker supports pragmas:
# Ignore a single line
x: int = 1 # chkstyle: ignore
# Ignore the next line
# chkstyle: ignore
y: int = 2
# Disable for a block
# chkstyle: off
carefully_formatted = {
"alignment": "matters",
"here": "for readability",
}
# chkstyle: on
# Skip an entire file (must be in first 5 lines)
# chkstyle: skip
Running Tests
pytest
There are currently no tests marked slow; running pytest -m slow selects 0 tests.
Development
Create a PR with a label (for release notes):
./tools/pr.sh enhancement "Add new feature"
./tools/pr.sh bug "Fix something"
Release after PRs are merged:
./tools/release.sh # patch bump (default)
./tools/release.sh minor # minor bump
./tools/release.sh major # major bump
This tags the current version, pushes to trigger PyPI publish, then bumps for the next dev cycle.
Philosophy
This tool exists to catch mechanical issues, not to enforce taste. The violations it reports are almost always things you'd want to fix—extra vertical space that doesn't help, type annotations that clutter rather than clarify, formatting that makes diffs noisier than necessary.
The goal is code that's pleasant to read and easy to maintain. Dense, but not cramped. Clear, but not verbose. When in doubt, look at the surrounding code and match its style.
For the full style guide, see:
- fast.ai Style Guide
- style.md in this repo
License
Apache 2.0
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