Refactoring Python Applications for Simplicity¶

重构并精简Python应用¹

Metrics¶

行数/Lines of Code¶

Linux

# file
$ wc -l file.py
# folder
$ find . -name \*.py | xargs wc -l

windows

Get-ChildItem -Path *.py -Recurse | Measure-Object –Line

链路复杂度/Cyclomatic Complexity¶

tool

pip install radon

radon cc cyclomatic_example.py -s

explain
F means function, M means method, and C means class.
main is the name of the function.
4 is the line the function starts on.
B is the rating from A to F. A is the best grade, meaning the least complexity.
The number in parentheses, 6, is the cyclomatic complexity of the code.

难度度量元/Halstead Metrics¶

4 Measures
Operands are values and names of variables.
Operators are all of the built-in keywords, like if, else, for or while.
Length (N) is the number of operators plus the number of operands in your program.
Vocabulary (h) is the number of unique operators plus the number of unique operands in your a program.
3 metrics
Volume (V) represents a product of the length and the vocabulary.
Difficulty (D) represents a product of half the unique operands and the reuse of operands.
Effort (E) is the overall metric that is a product of volume and difficulty.

explain

import sys  # import (operator), sys (operand)

if len(sys.argv) > 1:
...
# 5 operators
-  if
-  (
-  )
-  >
-  :
# 2 operands
- sys.argv
- 1

commands

radon hal cyclomatic_example.py
# time = effort/18
# bugs = volumn/3000

Maintainability Index/MI¶

command

radon mi cyclomatic_example.py -s

explian
- lower than 25: hard to maintain
- over 75: easy to maintain

wily: Capture and Track Complexity¶

command

$ pip install wily

explain
wily build: iterate through the Git history and analyze the metrics for each file
wily report: see the historical trend in metrics for a given file or folder
wily graph: graph a set of metrics in an HTML file

example: wily¶

$ git clone https://github.com/requests/requests
$ cd requests
$ ls

# build
$ wily build requests
# Lines/MI/Cyclomatic Complexity
$ wily report requests/api.py
#
$ wily list-metrics
# report
$ wily report requests/api.py maintainability.rank raw.sloc
#graph
$ wily graph requests/sessions.py maintainability.mi
# html
$ wily graph requests/sessions.py maintainability.mi -o my_report.html

Pre-commit Hook¶

shell

$ wily diff requests/api.py

$ pip install pre-commit

.pre-commit-config.yaml

repos:
-   repo: local
    hooks:
    -   id: wily
        name: wily
        entry: wily diff
        verbose: true
        language: python
        additional_dependencies: [wily]

shell

$ pre-commit install

Refactoring¶

Using rope

pip install rope

from rope.base.project import Project
proj = Project('requests')

[f.name for f in proj.get_files()]

api = proj.get_file('api.py')

from rope.refactor.rename import Rename
change = Rename(proj, api).get_changes('new_api')
proj.do(change)

Using VSCode
Using Pycharm
etc.

Anti-Patterns¶

Functions Be Objects
Objects Be Functions
"Triangular" code=>Flat Code

Handling Complex Dictionaries With Query Tools

# pip install jmespath
import jmespath
jmespath.search("network.lines", data)

Using attrs and dataclasses to Reduce Code

https://realpython.com/python-refactoring/#using-wily-to-capture-and-track-your-projects-complexity ↩