Before you begin
- Python 3.12 or newer
Set up your example
- Save the complete code as python-branch-count.py in a working folder.
- Save the provided sample files in that same folder; run commands from that folder.
Sample files in this download:
- sample.py
Download the ZIP, extract it, and open a terminal inside the extracted folder. The source file is python-branch-count.py.
Run the script
python "python-branch-count.py" --source "sample.py" --output "analysis.json"If your system uses python3 instead of python, use that command for Python examples. Keep paths containing spaces in quotes. Required inputs and optional settings are described in the code and setup steps.
What to expect
Estimate function branching with an explicit syntax-based metric. Tool.run includes an exception-handler decision point.
The complete script
#!/usr/bin/env python3
'Count decision points in Python functions'
import argparse
import json
from pathlib import Path
def write_json(path, value):
data = json.dumps(value, indent=2, ensure_ascii=False, allow_nan=False) + "\n"
with Path(path).open("x", encoding="utf-8", newline="") as handle:
handle.write(data)
import ast
import tokenize
import io
import doctest
from collections import Counter, defaultdict
FUNCTIONS=(ast.FunctionDef,ast.AsyncFunctionDef)
SCOPES=(ast.FunctionDef,ast.AsyncFunctionDef,ast.ClassDef,ast.Lambda)
def functions(tree):
return [n for n in ast.walk(tree) if isinstance(n,FUNCTIONS)]
def local_nodes(node):
yield node
for child in ast.iter_child_nodes(node):
if not isinstance(child,SCOPES):
yield from local_nodes(child)
def name(node):
try: return ast.unparse(node)
except (ValueError,TypeError): return type(node).__name__
def targets(node):
return [n.id for n in ast.walk(node) if isinstance(n,ast.Name) and isinstance(n.ctx,ast.Store)]
def sources(value):
root=Path(value)
if root.is_file(): return [root]
if not root.is_dir(): raise ValueError("--source must be a Python file or directory.")
excluded={".git",".venv","venv","node_modules","__pycache__"}
files=sorted(p for p in root.rglob("*.py") if p.is_file() and not any(x in excluded or x.startswith(".") for x in p.relative_to(root).parts))
if len(files)>500: raise ValueError("At most 500 Python files per run.")
return files
def analyze(tree,text):
result=[]
decisions=(ast.If,ast.For,ast.AsyncFor,ast.While,ast.ExceptHandler,ast.IfExp,ast.comprehension)
for fn in functions(tree):
nodes=list(local_nodes(fn))
count=sum(isinstance(n,decisions) for n in nodes)
count+=sum(len(n.values)-1 for n in nodes if isinstance(n,ast.BoolOp))
count+=sum(max(0,len(n.cases)-1) for n in nodes if isinstance(n,ast.Match))
result.append({"name":fn.name,"line":fn.lineno,"decision_points":count,"baseline_plus_decisions":count+1})
return result
def main():
parser = argparse.ArgumentParser(description='Count decision points in Python functions')
parser.add_argument("--source",required=True,help="Python file or source directory")
parser.add_argument("--output",required=True)
args = parser.parse_args()
reports=[]
for path in sources(args.source):
try:
if path.stat().st_size>2*1024*1024: raise ValueError("Source exceeds 2 MiB.")
with tokenize.open(path) as handle: text=handle.read()
tree=ast.parse(text,filename=str(path))
reports.append({"path":str(path),"result":analyze(tree,text)})
except (OSError,SyntaxError,UnicodeError,ValueError) as exc:
reports.append({"path":str(path),"error":str(exc)})
write_json(args.output,reports)
if __name__ == "__main__":
try:
main()
except (OSError, ValueError, KeyError, TypeError, ArithmeticError, IndexError, LookupError) as exc:
raise SystemExit(str(exc))
Open source as plain text · Download source and sample files
How it works
- The program parses source syntax without importing or executing it; per-file parse failures become error records.
- If/loop/handler/comprehension nodes and extra boolean operands contribute; nested scopes are excluded. This is a teaching metric, not a standards-certified complexity score.
- Tool.run includes an exception-handler decision point.
Make it your own
--source
Use --source with a Python file or directory; directory mode skips common dependency and hidden folders.
Adapt the processing
Edit analyze's decisions tuple to match a documented team metric.
Change one setting at a time, run it again on sample data, and compare the output. The customization guide walks through this process.
If something goes wrong
The result differs from another analyzer.
Metrics differ in how they count match cases, comprehensions, and boolean expressions.
The destination already exists.
Choose a new --output path. The script deliberately refuses to replace an existing result.
Reference & next steps
These official references explain the underlying tools. The Scriptage example and guide are original instructional content. See verification notes for what has been checked and the limits of those checks.
Copies a template for your own notes. It does not send anything.