HydroModPy/tools/generate_python_category_loc_evolution.py at dev · HydroModPy/HydroModPy · GitHub

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from __future__ import annotations

import argparse

import csv

import json

import math

import subprocess

from dataclasses import dataclass

from datetime import date, datetime, timedelta

from pathlib import Path

import matplotlib

matplotlib.use("Agg")

import matplotlib.dates as mdates

import matplotlib.pyplot as plt

import numpy as np

REPO_ROOT = Path(__file__).resolve().parents[1]

DEFAULT_OUT_DIR = REPO_ROOT / "reports" / "metrics" / "python_loc_by_category"

PYTHON_PATHSPEC = "*.py"

@dataclass(frozen=True)

class CategorySpec:

key: str

label: str

color: str

CATEGORIES = [

CategorySpec("algorithms", "Noyau scientifique / algorithmes", "#0b7285"),

CategorySpec("spatial", "Spatial / maillage / geotraitement", "#2f9e44"),

CategorySpec("solver_connectors", "Connectique solveurs externes", "#e67700"),

CategorySpec("data_connectors", "Connectique donnees / formats / APIs", "#5f3dc4"),

CategorySpec("orchestration", "Orchestration produit", "#1c7ed6"),

CategorySpec("results", "Persistance / catalogue de resultats", "#495057"),

CategorySpec("visualization", "Visualisation / reporting", "#d6336c"),

CategorySpec("support", "Qualite / validation / support", "#868e96"),

]

CATEGORY_BY_KEY = {category.key: category for category in CATEGORIES}

EXACT_RULES = {

"hydromodpy/__init__.py": "orchestration",

"hydromodpy/__main__.py": "orchestration",

"hydromodpy/exceptions.py": "orchestration",

"hydromodpy/main.py": "orchestration",

"hydromodpy/project.py": "orchestration",

"hydromodpy/simulation.py": "orchestration",

"hydromodpy/watershed_root.py": "orchestration",

"hydromodpy/calibration/cli.py": "orchestration",

"hydromodpy/calibration/persistence.py": "results",

"hydromodpy/calibration/report.py": "visualization",

}

PREFIX_RULES = [

("tests/", "support"),

("validation_cases/", "support"),

("examples/", "support"),

("tools/", "support"),

("hydromodpy_annex/", "support"),

("scratch_tests/", "support"),

("tmp/", "support"),

("docs/", "support"),

(".github/", "support"),

("hydromodpy/display/", "visualization"),

("hydromodpy/analysis/", "visualization"),

("hydromodpy/postprocess/", "visualization"),

("hydromodpy/results/", "results"),

("hydromodpy/data/", "data_connectors"),

("hydromodpy/data_managers/", "data_connectors"),

("hydromodpy/spatial/", "spatial"),

("hydromodpy/domain/", "spatial"),

("hydromodpy/field/", "spatial"),

("hydromodpy/geographic/", "spatial"),

("hydromodpy/geography/", "spatial"),

("hydromodpy/physics/", "algorithms"),

("hydromodpy/hydrology/", "algorithms"),

("hydromodpy/process/", "algorithms"),

("hydromodpy/calibration/", "algorithms"),

("hydromodpy/solver/boussinesq/", "algorithms"),

("hydromodpy/solver/", "solver_connectors"),

("hydromodpy/modeling/", "solver_connectors"),

("hydromodpy/simulation/", "orchestration"),

("hydromodpy/workflow/", "orchestration"),

("hydromodpy/core/", "orchestration"),

("hydromodpy/config/", "orchestration"),

("hydromodpy/schema/", "orchestration"),

("hydromodpy/runners/", "orchestration"),

("hydromodpy/watershed/", "orchestration"),

("hydromodpy/launchers/", "orchestration"),

("hydromodpy/launcher/", "orchestration"),

("hydromodpy/cli/", "orchestration"),

("hydromodpy/pyhelp/", "support"),

("hydromodpy/tools/", "support"),

]

def _git(*args: str, check: bool = True) -> subprocess.CompletedProcess[str]:

return subprocess.run(

["git", *args],

cwd=REPO_ROOT,

check=check,

capture_output=True,

text=True,

encoding="utf-8",

errors="replace",

)

def _git_text(*args: str) -> str:

return _git(*args).stdout.strip()

def _iter_days(start: date, end: date):

current = start

while current <= end:

yield current

current += timedelta(days=1)

def _commit_before(day: date) -> str:

return _git_text(

"rev-list", "--first-parent", "-n", "1", f"--before={day.isoformat()} 23:59:59", "HEAD"

)

def _short_sha(commit: str) -> str:

return _git_text("rev-parse", "--short=8", commit)

def _subject(commit: str) -> str:

return _git_text("log", "-1", "--pretty=%s", commit)

def _normalize_path(path: str) -> str:

return path.replace("\\", "/")

def _classify_path(path: str) -> tuple[str, str, str]:

normalized = _normalize_path(path)

exact_match = EXACT_RULES.get(normalized)

if exact_match is not None:

return exact_match, "exact", normalized

for prefix, category_key in PREFIX_RULES:

if normalized.startswith(prefix):

return category_key, "prefix", prefix

if normalized.startswith("hydromodpy/"):

raise ValueError(f"Unclassified hydromodpy path: {normalized}")

return "support", "fallback", "top_level_python"

def _parse_grep_count_line(raw_line: str) -> tuple[str, int]:

commit_and_path, count_text = raw_line.rsplit(":", 1)

_commit, path = commit_and_path.split(":", 1)

return path, int(count_text)

def _snapshot_category_counts(commit: str) -> dict[str, int]:

result = _git("grep", "-I", "--count", "-e", ".", commit, "--", PYTHON_PATHSPEC, check=False)

if result.returncode not in (0, 1):

raise RuntimeError(result.stderr.strip() or "git grep failed")

counts = {category.key: 0 for category in CATEGORIES}

for raw_line in result.stdout.splitlines():

if not raw_line.strip():

continue

path, nonblank_lines = _parse_grep_count_line(raw_line)

category_key, _rule_type, _rule_value = _classify_path(path)

counts[category_key] += nonblank_lines

return counts

def _head_file_assignments(commit: str) -> list[dict[str, str | int]]:

tree_text = _git_text("ls-tree", "-r", "--name-only", commit)

grep_result = _git(

"grep", "-I", "--count", "-e", ".", commit, "--", PYTHON_PATHSPEC, check=False

)

if grep_result.returncode not in (0, 1):

raise RuntimeError(grep_result.stderr.strip() or "git grep failed")

lines_by_path: dict[str, int] = {}

for raw_line in grep_result.stdout.splitlines():

if not raw_line.strip():

continue

path, nonblank_lines = _parse_grep_count_line(raw_line)

lines_by_path[_normalize_path(path)] = nonblank_lines

rows: list[dict[str, str | int]] = []

for raw_path in tree_text.splitlines():

normalized = _normalize_path(raw_path)

if not normalized.endswith(".py"):

continue

category_key, rule_type, rule_value = _classify_path(normalized)

rows.append(

{

"path": normalized,

"category_key": category_key,

"category_label": CATEGORY_BY_KEY[category_key].label,

"rule_type": rule_type,

"rule_value": rule_value,

"head_nonblank_lines": lines_by_path.get(normalized, 0),

}

)

return rows

def _write_csv(path: Path, rows: list[dict[str, str | int | float]]) -> None:

if not rows:

return

with path.open("w", newline="", encoding="utf-8") as handle:

writer = csv.DictWriter(handle, fieldnames=list(rows[0].keys()))

writer.writeheader()

writer.writerows(rows)

def _pct_change(start: int, end: int) -> float:

if start == 0:

return math.inf if end > 0 else 0.0

return (end - start) / start * 100.0

def _format_pct_change(value: float) -> str:

if math.isinf(value):

return "nouveau"

return f"{value:+.1f}%"

def _plot_stacked_area(

path_png: Path,

path_svg: Path,

daily_rows: list[dict[str, str | int]],

title: str,

) -> None:

plt.style.use("seaborn-v0_8-whitegrid")

fig, ax = plt.subplots(figsize=(13.5, 7.5))

x = [datetime.fromisoformat(str(row["date"])) for row in daily_rows]

series = [[int(row[category.key]) for row in daily_rows] for category in CATEGORIES]

labels = [category.label for category in CATEGORIES]

colors = [category.color for category in CATEGORIES]

total = [int(row["total_nonblank_lines"]) for row in daily_rows]

pct_total = [_pct_change(total[0], value) for value in total]

ax.stackplot(x, *series, labels=labels, colors=colors, alpha=0.9)

ax.plot(x, total, color="#212529", linewidth=1.7, label="Total")

ax_pct = ax.twinx()

ax_pct.plot(

pct_total,

color="#c92a2a",

linewidth=1.8,

linestyle="--",

label="Evolution totale (%)",

)

ax.set_title(title, fontsize=15, pad=14)

ax.set_xlabel("Date")

ax.set_ylabel("Lignes Python non vides")

ax_pct.set_ylabel("Evolution totale (%)")

ax.xaxis.set_major_locator(mdates.WeekdayLocator(interval=1 if len(x) <= 45 else 2))

ax.xaxis.set_major_formatter(mdates.DateFormatter("%d/%m"))

ax.yaxis.set_major_formatter(lambda value, pos: f"{int(value):,}".replace(",", " "))

ax_pct.yaxis.set_major_formatter(lambda value, pos: f"{value:+.0f}%")

start_total = total[0]

end_total = total[-1]

delta = end_total - start_total

pct = _pct_change(start_total, end_total)

ax_pct.annotate(

_format_pct_change(pct_total[-1]),

xy=(x[-1], pct_total[-1]),

xytext=(-38, 10),

textcoords="offset points",

fontsize=9,

color="#8f1d1d",

bbox={"boxstyle": "round,pad=0.2", "facecolor": "white", "edgecolor": "#f1b0b0"},

)

handles, legend_labels = ax.get_legend_handles_labels()

handles_pct, labels_pct = ax_pct.get_legend_handles_labels()

ax.legend(

handles + handles_pct, legend_labels + labels_pct, loc="upper left", ncol=2, fontsize=9

)

ax.text(

0.99,

0.02,

f"{daily_rows[0]['date']} -> {daily_rows[-1]['date']} : {start_total:,} -> {end_total:,} ({delta:+,} {_format_pct_change(pct)})".replace(

",", " "

transform=ax.transAxes,

ha="right",

va="bottom",

fontsize=10,

bbox={"boxstyle": "round,pad=0.35", "facecolor": "white", "edgecolor": "#d8d8d8"},

)

fig.autofmt_xdate()

fig.tight_layout()

fig.savefig(path_png, dpi=180)

fig.savefig(path_svg)

plt.close(fig)

def _plot_delta_bars(

path_png: Path,

path_svg: Path,

summary_rows: list[dict[str, str | int | float]],

title: str,

) -> None:

plt.style.use("seaborn-v0_8-whitegrid")

fig, ax = plt.subplots(figsize=(11.5, 6.5))

ordered_rows = sorted(

summary_rows, key=lambda row: abs(int(row["delta_nonblank_lines"])), reverse=True

)

y_labels = [str(row["category_label"]) for row in ordered_rows]

delta_values = [int(row["delta_nonblank_lines"]) for row in ordered_rows]

colors = [CATEGORY_BY_KEY[str(row["category_key"])].color for row in ordered_rows]

y_positions = np.arange(len(ordered_rows))

ax.barh(y_positions, delta_values, color=colors, alpha=0.9)

ax.set_yticks(y_positions, labels=y_labels)

ax.invert_yaxis()

ax.axvline(0, color="#212529", linewidth=1)

ax.xaxis.set_major_formatter(lambda value, pos: f"{int(value):,}".replace(",", " "))

ax.set_xlabel("Variation de lignes Python non vides")

ax.set_title(title, fontsize=15, pad=14)

ax.margins(x=0.22)

for index, row in enumerate(ordered_rows):

value = int(row["delta_nonblank_lines"])

pct_label = str(row["pct_change_display"])

ha = "left" if value >= 0 else "right"

offset = 600 if value >= 0 else -600

label = f"{value:+,} ({pct_label})".replace(",", " ")

ax.text(value + offset, index, label, va="center", ha=ha, fontsize=9)

ax.text(

0.99,

0.02,

"Pourcentage calcule par categorie: (fin - debut) / debut",

transform=ax.transAxes,

ha="right",

va="bottom",

fontsize=9,

bbox={"boxstyle": "round,pad=0.25", "facecolor": "white", "edgecolor": "#d8d8d8"},

)

fig.tight_layout()

fig.savefig(path_png, dpi=180)

fig.savefig(path_svg)

plt.close(fig)

def _build_summary_rows(

daily_rows: list[dict[str, str | int]],

head_file_rows: list[dict[str, str | int]],

) -> list[dict[str, str | int | float]]:

start_row = daily_rows[0]

end_row = daily_rows[-1]

file_counts: dict[str, int] = {category.key: 0 for category in CATEGORIES}

for file_row in head_file_rows:

file_counts[str(file_row["category_key"])] += 1

total_end = int(end_row["total_nonblank_lines"])

rows: list[dict[str, str | int | float]] = []

for category in CATEGORIES:

start_lines = int(start_row[category.key])

end_lines = int(end_row[category.key])

delta = end_lines - start_lines

pct_change = _pct_change(start_lines, end_lines)

share = (end_lines / total_end * 100.0) if total_end else 0.0

rows.append(

{

"category_key": category.key,

"category_label": category.label,

"head_python_files": file_counts[category.key],

"start_nonblank_lines": start_lines,

"end_nonblank_lines": end_lines,

"delta_nonblank_lines": delta,

"pct_change_from_start": None if math.isinf(pct_change) else round(pct_change, 2),

"pct_change_display": _format_pct_change(pct_change),

"share_of_end_percent": round(share, 2),

}

)

return rows

def _build_markdown_summary(

path: Path,

start: date,

end: date,

branch: str,

head_commit: str,

daily_rows: list[dict[str, str | int]],

summary_rows: list[dict[str, str | int | float]],

) -> None:

total_start = int(daily_rows[0]["total_nonblank_lines"])

total_end = int(daily_rows[-1]["total_nonblank_lines"])

total_delta = total_end - total_start

total_pct = total_delta / total_start * 100.0 if total_start else math.nan

lines = [

"# Evolution Python par categorie",

"",

f"- Branche analysee : `{branch}`",

f"- Fenetre : `{start.isoformat()}` -> `{end.isoformat()}`",

f"- Commit HEAD : `{head_commit}`",

f"- Lignes Python non vides : `{total_start:,}` -> `{total_end:,}` (`{total_delta:+,}`, `{total_pct:+.1f}%`)".replace(

",", " "

"",

"## Taxonomie",

"",

]

for category in CATEGORIES:

lines.append(f"- `{category.label}`")

lines.extend(

[

"",

"## Synthese par categorie",

"",

"| --- | ---: | ---: | ---: | ---: | ---: | ---: |",

]

)

for row in sorted(summary_rows, key=lambda item: int(item["end_nonblank_lines"]), reverse=True):

lines.append(

"| {label} | {files} | {start} | {end} | {delta} | {pct} | {share:.2f}% |".format(

label=row["category_label"],

files=int(row["head_python_files"]),

start=f"{int(row['start_nonblank_lines']):,}".replace(",", " "),

end=f"{int(row['end_nonblank_lines']):,}".replace(",", " "),

delta=f"{int(row['delta_nonblank_lines']):+,}".replace(",", " "),

pct=row["pct_change_display"],

share=float(row["share_of_end_percent"]),

)

path.write_text("\n".join(lines) + "\n", encoding="utf-8")

def main(argv: list[str] | None = None) -> int:

parser = argparse.ArgumentParser(

description="Generate a category-based Python LOC evolution report over a date window."

)

parser.add_argument("--start", required=True, help="Start date in YYYY-MM-DD.")

parser.add_argument("--end", required=True, help="End date in YYYY-MM-DD.")

parser.add_argument(

"--out-dir",

type=Path,

default=DEFAULT_OUT_DIR,

help="Output directory for CSV, charts, and summaries.",

)

parser.add_argument(

"--tag",

default="last_2_months",

help="Filename suffix used for generated artifacts.",

)

parser.add_argument(

"--title",

default="Evolution des lignes Python par categorie",

help="Stacked area chart title.",

)

args = parser.parse_args(argv)

start = date.fromisoformat(args.start)

end = date.fromisoformat(args.end)

if end < start:

raise ValueError("end date must be on or after start date")

out_dir = args.out_dir

out_dir.mkdir(parents=True, exist_ok=True)

branch = _git_text("rev-parse", "--abbrev-ref", "HEAD")

head_commit = _git_text("rev-parse", "HEAD")

snapshot_cache: dict[str, dict[str, int]] = {}

short_sha_cache: dict[str, str] = {}

subject_cache: dict[str, str] = {}

daily_rows: list[dict[str, str | int]] = []

previous_commit: str | None = None

for current_day in _iter_days(start, end):

commit = _commit_before(current_day)

category_counts = snapshot_cache.get(commit)

if category_counts is None:

category_counts = _snapshot_category_counts(commit)

snapshot_cache[commit] = category_counts

short_commit = short_sha_cache.setdefault(commit, _short_sha(commit))

subject = subject_cache.setdefault(commit, _subject(commit))

row: dict[str, str | int] = {

"date": current_day.isoformat(),

"commit": commit,

"short_commit": short_commit,

"commit_changed_from_previous_day": str(commit != previous_commit).lower(),

"subject": subject,

}

total_nonblank_lines = 0

for category in CATEGORIES:

value = int(category_counts[category.key])

row[category.key] = value

total_nonblank_lines += value

row["total_nonblank_lines"] = total_nonblank_lines

daily_rows.append(row)

previous_commit = commit

head_file_rows = _head_file_assignments(head_commit)

summary_rows = _build_summary_rows(daily_rows, head_file_rows)

daily_csv_path = out_dir / f"python_loc_by_category_{args.tag}.csv"

head_files_csv_path = out_dir / f"python_head_file_categories_{args.tag}.csv"

summary_csv_path = out_dir / f"python_category_summary_{args.tag}.csv"

area_png_path = out_dir / f"python_loc_by_category_{args.tag}.png"

area_svg_path = out_dir / f"python_loc_by_category_{args.tag}.svg"

delta_png_path = out_dir / f"python_loc_by_category_delta_{args.tag}.png"

delta_svg_path = out_dir / f"python_loc_by_category_delta_{args.tag}.svg"

summary_json_path = out_dir / f"python_category_summary_{args.tag}.json"

summary_md_path = out_dir / f"python_category_summary_{args.tag}.md"

_write_csv(daily_csv_path, daily_rows)

_write_csv(head_files_csv_path, head_file_rows)

_write_csv(summary_csv_path, summary_rows)

_plot_stacked_area(

path_png=area_png_path, path_svg=area_svg_path, daily_rows=daily_rows, title=args.title

)

_plot_delta_bars(

path_png=delta_png_path,

path_svg=delta_svg_path,

summary_rows=summary_rows,

title="Variation des lignes Python par categorie sur la periode",

)

summary_payload = {

"branch": branch,

"period_start": start.isoformat(),

"period_end": end.isoformat(),

"head_commit": head_commit,

"categories": [

{

"key": category.key,

"label": category.label,

"color": category.color,

}

for category in CATEGORIES

"summary_rows": summary_rows,

"daily_csv": str(daily_csv_path),

"head_files_csv": str(head_files_csv_path),

"summary_csv": str(summary_csv_path),

"area_png": str(area_png_path),

"area_svg": str(area_svg_path),

"delta_png": str(delta_png_path),

"delta_svg": str(delta_svg_path),

"markdown_summary": str(summary_md_path),

}

summary_json_path.write_text(

json.dumps(summary_payload, indent=2, ensure_ascii=False), encoding="utf-8"

)

_build_markdown_summary(

path=summary_md_path,

start=start,

end=end,

branch=branch,

head_commit=head_commit,

daily_rows=daily_rows,

summary_rows=summary_rows,

)

print(f"DAILY_CSV={daily_csv_path}")

print(f"HEAD_FILES_CSV={head_files_csv_path}")

print(f"SUMMARY_CSV={summary_csv_path}")

print(f"AREA_PNG={area_png_path}")

print(f"DELTA_PNG={delta_png_path}")

print(f"SUMMARY_JSON={summary_json_path}")

print(f"SUMMARY_MD={summary_md_path}")

return 0

if __name__ == "__main__":

raise SystemExit(main())

HydroModPy/tools/generate_python_category_loc_evolution.py at dev · HydroModPy/HydroModPy · GitHub

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