report_generator.py

"""Generate downloadable PDF and HTML analysis reports."""

from __future__ import annotations

import base64
import os
from datetime import datetime

from fpdf import FPDF

from data_processor import TEMP_DIR

PDF_PATH = os.path.join(TEMP_DIR, "analysis_report.pdf")
HTML_PATH = os.path.join(TEMP_DIR, "analysis_report.html")


def _sanitize(text: str, max_word: int = 40) -> str:
    """fpdf core fonts are latin-1 only; also break words too wide for one line.

    fpdf2 raises 'Not enough horizontal space to render a single character'
    when an unbroken token (e.g. a long one-hot column name) exceeds the
    remaining cell width, so long words are split into chunks.
    """
    replacements = {"²": "^2", "—": "-", "–": "-", "'": "'", "'": "'", """: '"', """: '"', "×": "x"}
    for a, b in replacements.items():
        text = text.replace(a, b)
    text = text.encode("latin-1", "replace").decode("latin-1")
    words = []
    for word in text.split(" "):
        while len(word) > max_word:
            words.append(word[:max_word])
            word = word[max_word:]
        words.append(word)
    return " ".join(words)


def generate_pdf_report(profile: dict, steps: list[str], result: dict) -> str:
    pdf = FPDF()
    pdf.set_auto_page_break(auto=True, margin=15)
    pdf.add_page()

    pdf.set_font("Helvetica", "B", 18)
    pdf.cell(0, 12, "ML Data Analysis Report", new_x="LMARGIN", new_y="NEXT")
    pdf.set_font("Helvetica", "", 10)
    pdf.set_text_color(120, 120, 120)
    pdf.cell(0, 6, f"Generated {datetime.now():%Y-%m-%d %H:%M}", new_x="LMARGIN", new_y="NEXT")
    pdf.set_text_color(0, 0, 0)
    pdf.ln(4)

    def section(title):
        pdf.set_font("Helvetica", "B", 13)
        pdf.set_fill_color(230, 236, 245)
        pdf.cell(0, 9, _sanitize(title), new_x="LMARGIN", new_y="NEXT", fill=True)
        pdf.ln(2)
        pdf.set_font("Helvetica", "", 10)

    def kv(key, value):
        pdf.set_font("Helvetica", "B", 10)
        pdf.cell(55, 6, _sanitize(str(key)))
        pdf.set_font("Helvetica", "", 10)
        # new_x must reset to the margin: fpdf2's multi_cell default leaves the
        # cursor at the cell's right edge, so the next line would start off-page
        pdf.multi_cell(0, 6, _sanitize(str(value)), new_x="LMARGIN", new_y="NEXT")

    section("1. Dataset Overview")
    kv("Rows", f"{profile['n_rows']:,}")
    kv("Columns", profile["n_cols"])
    kv("Numeric columns", ", ".join(profile["numeric_columns"]) or "none")
    kv("Categorical columns", ", ".join(profile["categorical_columns"]) or "none")
    kv("Missing values", f"{profile['missing_total']:,}")
    kv("Duplicate rows", f"{profile['duplicate_rows']:,}")
    pdf.ln(4)

    section("2. Preprocessing Steps")
    for i, step in enumerate(steps, 1):
        pdf.multi_cell(0, 6, _sanitize(f"{i}. {step}"), new_x="LMARGIN", new_y="NEXT")
    pdf.ln(4)

    section("3. Model & Results")
    kv("Model", result["model_name"])
    kv("Task", result["task"])
    kv("Target column", result["target"])
    kv("Training samples", f"{result['n_train']:,}")
    kv("Test samples", f"{result['n_test']:,}")
    pdf.ln(2)
    for metric, value in result["metrics"].items():
        kv(metric, value)
    pdf.ln(4)

    for title, path in [
        ("4. Result Plot", result.get("plot_path")),
        ("5. Feature Importance", result.get("importance_path")),
    ]:
        if path and os.path.exists(path):
            section(title)
            pdf.image(path, w=150)
            pdf.ln(4)

    pdf.output(PDF_PATH)
    return PDF_PATH


def _img_b64(path):
    if not path or not os.path.exists(path):
        return None
    with open(path, "rb") as f:
        return base64.b64encode(f.read()).decode()


def generate_html_report(profile: dict, steps: list[str], result: dict) -> str:
    plot_b64 = _img_b64(result.get("plot_path"))
    imp_b64 = _img_b64(result.get("importance_path"))

    metrics_rows = "".join(
        f"<tr><td>{k}</td><td><b>{v}</b></td></tr>" for k, v in result["metrics"].items()
    )
    steps_html = "".join(f"<li>{s}</li>" for s in steps)
    missing = {k: v for k, v in profile["missing_counts"].items() if v > 0}
    missing_html = (
        ", ".join(f"{k} ({v})" for k, v in missing.items()) if missing else "None"
    )

    html = f"""<!DOCTYPE html>
<html><head><meta charset="utf-8"><title>ML Data Analysis Report</title>
<style>
body {{ font-family: -apple-system, 'Segoe UI', Roboto, sans-serif; max-width: 860px;
       margin: 40px auto; padding: 0 20px; color: #1a202c; line-height: 1.6; }}
h1 {{ border-bottom: 3px solid #4C72B0; padding-bottom: 8px; }}
h2 {{ color: #4C72B0; margin-top: 32px; }}
table {{ border-collapse: collapse; width: 100%; margin: 12px 0; }}
td, th {{ border: 1px solid #e2e8f0; padding: 8px 12px; text-align: left; }}
th {{ background: #edf2f7; }}
img {{ max-width: 100%; border: 1px solid #e2e8f0; border-radius: 8px; margin: 8px 0; }}
.meta {{ color: #718096; font-size: 0.9em; }}
</style></head><body>
<h1>ML Data Analysis Report</h1>
<p class="meta">Generated {datetime.now():%Y-%m-%d %H:%M}</p>

<h2>1. Dataset Overview</h2>
<table>
<tr><th>Rows</th><td>{profile['n_rows']:,}</td></tr>
<tr><th>Columns</th><td>{profile['n_cols']}</td></tr>
<tr><th>Numeric columns</th><td>{', '.join(profile['numeric_columns']) or 'none'}</td></tr>
<tr><th>Categorical columns</th><td>{', '.join(profile['categorical_columns']) or 'none'}</td></tr>
<tr><th>Missing values</th><td>{profile['missing_total']:,} ({missing_html})</td></tr>
<tr><th>Duplicate rows</th><td>{profile['duplicate_rows']:,}</td></tr>
</table>

<h2>2. Preprocessing Steps</h2>
<ol>{steps_html}</ol>

<h2>3. Model &amp; Results</h2>
<table>
<tr><th>Model</th><td>{result['model_name']}</td></tr>
<tr><th>Task</th><td>{result['task']}</td></tr>
<tr><th>Target</th><td>{result['target']}</td></tr>
<tr><th>Train / test samples</th><td>{result['n_train']:,} / {result['n_test']:,}</td></tr>
{metrics_rows}
</table>
"""
    if plot_b64:
        html += f'<h2>4. Result Plot</h2><img src="data:image/png;base64,{plot_b64}">'
    if imp_b64:
        html += f'<h2>5. Feature Importance</h2><img src="data:image/png;base64,{imp_b64}">'
    html += "</body></html>"

    with open(HTML_PATH, "w", encoding="utf-8") as f:
        f.write(html)
    return HTML_PATH