diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..6ed2e42
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,32 @@
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+.venv/
+venv/
+ENV/
+.eggs/
+*.egg-info/
+.mypy_cache/
+.pytest_cache/
+
+# Generated reports
+rapport_*.pdf
+rapport/
+
+# Unlighthouse
+.unlighthouse/
+node_modules/
+
+# IDE & editors
+.idea/
+.vscode/
+*.swp
+*.swo
+*~
+.DS_Store
+
+webbanalys.json
+
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..f218cf8
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,509 @@
+ GNU GENERAL PUBLIC LICENSE
+ Version 3, 29 June 2007
+
+Copyright (C) 2007 Free Software Foundation, Inc. Everyone is permitted to copy and distribute
+verbatim copies of this license document, but changing it is not allowed.
+
+ Preamble
+
+The GNU General Public License is a free, copyleft license for software and other kinds of works.
+
+The licenses for most software and other practical works are designed to take away your freedom to share and change the
+works. By contrast, the GNU General Public License is intended to guarantee your freedom to share and change all
+versions of a program--to make sure it remains free software for all its users. We, the Free Software Foundation, use
+the GNU General Public License for most of our software; it applies also to any other work released this way by its
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+When we speak of free software, we are referring to freedom, not price. Our General Public Licenses are designed to make
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+
+For example, if you distribute copies of such a program, whether gratis or for a fee, you must pass on to the recipients
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+ TERMS AND CONDITIONS
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+0. Definitions.
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+"This License" refers to version 3 of the GNU General Public License.
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+"Copyright" also means copyright-like laws that apply to other kinds of works, such as semiconductor masks.
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+
+To "convey" a work means any kind of propagation that enables other parties to make or receive copies. Mere interaction
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+An interactive user interface displays "Appropriate Legal Notices" to the extent that it includes a convenient and
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+13. Use with the GNU Affero General Public License.
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+Notwithstanding any other provision of this License, you have permission to link or combine any covered work with a work
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+
+THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING
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+17. Interpretation of Sections 15 and 16.
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+ END OF TERMS AND CONDITIONS
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+ How to Apply These Terms to Your New Programs
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+If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve
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+
+ Copyright (C)
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+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
+ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+ GNU General Public License for more details.
+
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see .
+
+Also add information on how to contact you by electronic and paper mail.
+
+If the program does terminal interaction, make it output a short notice like this when it starts in an interactive mode:
+
+ Copyright (C)
+ This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+ This is free software, and you are welcome to redistribute it
+ under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License. Of
+course, your program's commands might be different; for a GUI interface, you would use an "about box".
+
+You should also get your employer (if you work as a programmer) or school, if any, to sign a "copyright disclaimer" for
+the program, if necessary. For more information on this, and how to apply and follow the GNU GPL, see
+.
+
+The GNU General Public License does not permit incorporating your program into proprietary programs. If your program is
+a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If
+this is what you want to do, use the GNU Lesser General Public License instead of this License. But first, please read
+.
diff --git a/lib/__init__.py b/lib/__init__.py
new file mode 100644
index 0000000..4bf44de
--- /dev/null
+++ b/lib/__init__.py
@@ -0,0 +1,2 @@
+# Webbplatsanalys Report Generator Library
+
diff --git a/lib/analyzer.py b/lib/analyzer.py
new file mode 100644
index 0000000..f3a0f01
--- /dev/null
+++ b/lib/analyzer.py
@@ -0,0 +1,118 @@
+"""
+Data analysis module for Unlighthouse reports.
+"""
+
+import json
+from pathlib import Path
+from collections import defaultdict
+
+
+def load_ci_result(ci_result_path: Path) -> dict:
+ """Load the main CI result JSON."""
+ with open(ci_result_path, "r", encoding="utf-8") as f:
+ return json.load(f)
+
+
+def load_all_audits(reports_dir: Path, site_url: str = ""):
+ """
+ Load ALL detailed audit data from lighthouse.json files.
+
+ Returns:
+ tuple: (all_audits, resource_issues, element_issues, page_count)
+ """
+ all_audits = defaultdict(lambda: {
+ "count": 0, "pages": [], "score_sum": 0, "title": "", "description": "",
+ "total_wasted_bytes": 0, "display_values": []
+ })
+
+ resource_issues = defaultdict(lambda: {
+ "count": 0, "wasted_bytes": 0, "total_bytes": 0, "pages": []
+ })
+
+ element_issues = defaultdict(lambda: {
+ "count": 0, "audit": "", "pages": []
+ })
+
+ page_count = 0
+ site_domain = site_url.replace("https://", "").replace("http://", "").split("/")[0]
+
+ for report_dir in reports_dir.iterdir():
+ if not report_dir.is_dir():
+ continue
+
+ lighthouse_json = report_dir / "lighthouse.json"
+ if not lighthouse_json.exists():
+ continue
+
+ try:
+ with open(lighthouse_json, "r", encoding="utf-8") as f:
+ report = json.load(f)
+
+ page_path = report.get("finalDisplayedUrl", report_dir.name)
+ page_path_short = page_path.replace(site_url, "") or "/"
+ audits = report.get("audits", {})
+ page_count += 1
+
+ for audit_id, audit_data in audits.items():
+ score = audit_data.get("score")
+ if score is None:
+ continue
+
+ if score < 1:
+ all_audits[audit_id]["count"] += 1
+ all_audits[audit_id]["title"] = audit_data.get("title", audit_id)
+ all_audits[audit_id]["description"] = audit_data.get("description", "")
+ all_audits[audit_id]["score_sum"] += score
+
+ if len(all_audits[audit_id]["pages"]) < 20:
+ all_audits[audit_id]["pages"].append(page_path_short)
+
+ display_val = audit_data.get("displayValue", "")
+ if display_val:
+ all_audits[audit_id]["display_values"].append(display_val)
+
+ details = audit_data.get("details", {})
+ items = details.get("items", [])
+
+ for item in items:
+ if not isinstance(item, dict):
+ continue
+
+ url = item.get("url", "")
+ if url and site_domain and site_domain in url:
+ url_short = url.replace(site_url, "")
+ key = (audit_id, url_short)
+ resource_issues[key]["count"] += 1
+ resource_issues[key]["wasted_bytes"] += item.get("wastedBytes", 0)
+ resource_issues[key]["total_bytes"] += item.get("totalBytes", 0)
+ if len(resource_issues[key]["pages"]) < 5:
+ resource_issues[key]["pages"].append(page_path_short)
+
+ node = item.get("node", {})
+ snippet = node.get("snippet", "") if isinstance(node, dict) else str(node) if node else ""
+
+ if snippet:
+ key = (audit_id, snippet[:80])
+ element_issues[key]["count"] += 1
+ element_issues[key]["audit"] = audit_id
+ if len(element_issues[key]["pages"]) < 5:
+ element_issues[key]["pages"].append(page_path_short)
+
+ wasted = item.get("wastedBytes", 0)
+ if wasted:
+ all_audits[audit_id]["total_wasted_bytes"] += wasted
+
+ except Exception:
+ continue
+
+ return dict(all_audits), dict(resource_issues), dict(element_issues), page_count
+
+
+def format_bytes(bytes_val: int) -> str:
+ """Format bytes to human readable."""
+ if bytes_val >= 1024 * 1024:
+ return f"{bytes_val / (1024*1024):.1f} MB"
+ elif bytes_val >= 1024:
+ return f"{bytes_val / 1024:.0f} KB"
+ return f"{bytes_val} B"
+
diff --git a/lib/charts.py b/lib/charts.py
new file mode 100644
index 0000000..c5f461e
--- /dev/null
+++ b/lib/charts.py
@@ -0,0 +1,324 @@
+"""
+Chart generation module for website analysis reports.
+Uses consultancy brand colors: lime-500 and lime-900.
+"""
+
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+import numpy as np
+import io
+
+# Consultancy brand colors (lime palette)
+BRAND = {
+ "primary": "#84cc16", # lime-500 (oklch 76.8% 0.233 130.85)
+ "primary_dark": "#365314", # lime-900 (oklch 40.5% 0.101 131.063)
+ "accent": "#a3e635", # lime-400
+ "dark": "#1a2e05", # lime-950
+}
+
+# Score colors (traffic light)
+SCORE_COLORS = {
+ "excellent": "#22c55e", # green-500
+ "needs_work": "#f59e0b", # amber-500
+ "poor": "#ef4444", # red-500
+}
+
+# UI colors
+UI = {
+ "text": "#1f2937", # gray-800
+ "muted": "#6b7280", # gray-500
+ "light_bg": "#f9fafb", # gray-50
+ "border": "#e5e7eb", # gray-200
+ "white": "#ffffff",
+}
+
+# Swedish category names
+CATEGORY_NAMES_SV = {
+ "performance": "Prestanda",
+ "accessibility": "Tillgänglighet",
+ "best-practices": "Bästa praxis",
+ "seo": "Sökmotoroptimering (SEO)",
+}
+
+
+def get_score_color(score: float) -> str:
+ """Get color based on score (0-100)."""
+ if score >= 90:
+ return SCORE_COLORS["excellent"]
+ elif score >= 50:
+ return SCORE_COLORS["needs_work"]
+ return SCORE_COLORS["poor"]
+
+
+def create_gauge_chart(score: float, label: str) -> io.BytesIO:
+ """Create a semi-circular gauge chart with brand colors."""
+ fig, ax = plt.subplots(figsize=(6, 6), dpi=150)
+
+ color = get_score_color(score)
+
+ # Background arc
+ theta_bg = np.linspace(np.pi, 0, 100)
+ r = 0.75
+ ax.plot(r * np.cos(theta_bg), r * np.sin(theta_bg),
+ color=UI["border"], linewidth=25, solid_capstyle="round", zorder=1)
+
+ # Score arc
+ score_ratio = score / 100
+ theta_score = np.linspace(np.pi, np.pi - (np.pi * score_ratio), 100)
+ ax.plot(r * np.cos(theta_score), r * np.sin(theta_score),
+ color=color, linewidth=25, solid_capstyle="round", zorder=2)
+
+ # Score text
+ ax.text(0, 0.05, f"{int(score)}", fontsize=56, fontweight="bold",
+ ha="center", va="center", color=color)
+ ax.text(0, -0.4, label, fontsize=16, ha="center", va="center",
+ color=UI["muted"])
+
+ # Scale markers
+ for val in [0, 50, 100]:
+ angle = np.pi - (np.pi * val / 100)
+ x = (r + 0.15) * np.cos(angle)
+ y = (r + 0.15) * np.sin(angle)
+ ax.text(x, y, str(val), fontsize=12, ha="center", va="center",
+ color=UI["muted"])
+
+ ax.set_xlim(-1.1, 1.1)
+ ax.set_ylim(-0.6, 1.1)
+ ax.axis("off")
+ ax.set_aspect("equal")
+
+ buf = io.BytesIO()
+ plt.savefig(buf, format="png", bbox_inches="tight", transparent=True, dpi=150)
+ plt.close()
+ buf.seek(0)
+ return buf
+
+
+def create_overview_chart(categories: dict, category_names: dict = None) -> io.BytesIO:
+ """Create main overview chart with 0-100 scale."""
+ if category_names is None:
+ category_names = CATEGORY_NAMES_SV
+
+ fig, ax = plt.subplots(figsize=(10, 4), dpi=150)
+
+ names = [category_names.get(k, k) for k in categories.keys()]
+ scores = [v["averageScore"] * 100 for v in categories.values()]
+
+ y_pos = np.arange(len(names))
+
+ # Background bars (100%)
+ ax.barh(y_pos, [100] * len(names), color=UI["border"], height=0.5, zorder=1)
+
+ # Score bars with traffic light colors
+ colors_list = [get_score_color(s) for s in scores]
+ bars = ax.barh(y_pos, scores, color=colors_list, height=0.5, zorder=2)
+
+ ax.set_yticks(y_pos)
+ ax.set_yticklabels(names, fontsize=11, color=UI["text"])
+ ax.set_xlim(0, 100)
+ ax.set_xlabel("Poäng (0-100)", fontsize=11, color=UI["muted"])
+
+ for i, (bar, score) in enumerate(zip(bars, scores)):
+ ax.text(score + 2, i, f"{score:.0f}", va="center", fontsize=11,
+ fontweight="bold", color=UI["text"])
+
+ # Threshold lines
+ ax.axvline(x=90, color=SCORE_COLORS["excellent"], linestyle="--", alpha=0.5, linewidth=1)
+ ax.axvline(x=50, color=SCORE_COLORS["needs_work"], linestyle="--", alpha=0.5, linewidth=1)
+
+ ax.spines["top"].set_visible(False)
+ ax.spines["right"].set_visible(False)
+ ax.spines["left"].set_color(UI["border"])
+ ax.spines["bottom"].set_color(UI["border"])
+
+ plt.tight_layout()
+ buf = io.BytesIO()
+ plt.savefig(buf, format="png", bbox_inches="tight", facecolor="white", dpi=150)
+ plt.close()
+ buf.seek(0)
+ return buf
+
+
+def create_issues_chart(all_audits: dict, total_pages: int, top_n: int = 12) -> io.BytesIO:
+ """Create horizontal bar chart of most common issues."""
+ fig, ax = plt.subplots(figsize=(10, 6), dpi=150)
+
+ sorted_audits = sorted(all_audits.items(), key=lambda x: x[1]["count"], reverse=True)[:top_n]
+
+ def wrap_title(t, max_len=35):
+ if len(t) <= max_len:
+ return t
+ words = t.split()
+ lines, current = [], ""
+ for w in words:
+ if len(current + " " + w) <= max_len:
+ current = (current + " " + w).strip()
+ else:
+ if current:
+ lines.append(current)
+ current = w
+ if current:
+ lines.append(current)
+ return "\n".join(lines[:2])
+
+ names = [wrap_title(a[1]["title"]) for a in sorted_audits]
+ counts = [a[1]["count"] for a in sorted_audits]
+ percentages = [(c / total_pages) * 100 for c in counts]
+
+ y_pos = np.arange(len(names))
+
+ # Background bars
+ ax.barh(y_pos, [100] * len(names), color=UI["border"], height=0.6, zorder=1)
+
+ # Issue bars with severity colors
+ colors_list = [SCORE_COLORS["poor"] if p > 80 else SCORE_COLORS["needs_work"] if p > 50
+ else BRAND["primary"] for p in percentages]
+ bars = ax.barh(y_pos, percentages, color=colors_list, height=0.6, zorder=2)
+
+ ax.set_yticks(y_pos)
+ ax.set_yticklabels(names, fontsize=9, color=UI["text"])
+ ax.set_xlim(0, 100)
+ ax.set_xlabel("Andel av sidor med problem (%)", fontsize=10, color=UI["muted"])
+
+ # Add labels - bars and data are in same order
+ for i, (pct, cnt) in enumerate(zip(percentages, counts)):
+ ax.text(pct + 2, i, f"{pct:.0f}% ({cnt})", va="center", fontsize=9, color=UI["text"])
+
+ ax.spines["top"].set_visible(False)
+ ax.spines["right"].set_visible(False)
+ ax.spines["left"].set_color(UI["border"])
+ ax.spines["bottom"].set_color(UI["border"])
+
+ plt.tight_layout()
+ buf = io.BytesIO()
+ plt.savefig(buf, format="png", bbox_inches="tight", facecolor="white", dpi=150)
+ plt.close()
+ buf.seek(0)
+ return buf
+
+
+def create_savings_chart(all_audits: dict) -> io.BytesIO:
+ """Create chart showing potential savings in MB."""
+ audits_with_savings = [(k, v) for k, v in all_audits.items() if v["total_wasted_bytes"] > 10000]
+ audits_with_savings.sort(key=lambda x: x[1]["total_wasted_bytes"], reverse=True)
+ audits_with_savings = audits_with_savings[:8]
+
+ if not audits_with_savings:
+ return None
+
+ fig, ax = plt.subplots(figsize=(9, 4), dpi=150)
+
+ def wrap_title(t, max_len=30):
+ return t[:max_len] + "..." if len(t) > max_len else t
+
+ names = [wrap_title(a[1]["title"]) for a in audits_with_savings]
+ savings_mb = [a[1]["total_wasted_bytes"] / (1024 * 1024) for a in audits_with_savings]
+
+ y_pos = np.arange(len(names))
+ bars = ax.barh(y_pos, savings_mb, color=SCORE_COLORS["needs_work"], height=0.6)
+
+ ax.set_yticks(y_pos)
+ ax.set_yticklabels(names, fontsize=9, color=UI["text"])
+ ax.set_xlabel("Potentiell besparing (MB)", fontsize=10, color=UI["muted"])
+
+ # Place labels at end of each bar
+ max_val = max(savings_mb) if savings_mb else 1
+ for i, s in enumerate(savings_mb):
+ ax.text(s + max_val * 0.02, i, f"{s:.1f} MB", va="center", fontsize=9, color=UI["text"])
+
+ ax.spines["top"].set_visible(False)
+ ax.spines["right"].set_visible(False)
+ ax.spines["left"].set_color(UI["border"])
+ ax.spines["bottom"].set_color(UI["border"])
+
+ plt.tight_layout()
+ buf = io.BytesIO()
+ plt.savefig(buf, format="png", bbox_inches="tight", facecolor="white", dpi=150)
+ plt.close()
+ buf.seek(0)
+ return buf
+
+
+def create_score_histogram(routes: list, category_names: dict = None) -> io.BytesIO:
+ """Create 4 histograms showing score distribution (0-100 scale)."""
+ if category_names is None:
+ category_names = CATEGORY_NAMES_SV
+
+ fig, axes = plt.subplots(2, 2, figsize=(10, 7), dpi=150)
+
+ categories = ["performance", "accessibility", "best-practices", "seo"]
+ titles = [category_names.get(c, c) for c in categories]
+
+ for ax, cat, title in zip(axes.flatten(), categories, titles):
+ scores = [r.get("categories", {}).get(cat, {}).get("score", 0) * 100 for r in routes]
+
+ bins = np.arange(0, 105, 10)
+ n, bins_out, patches = ax.hist(scores, bins=bins, edgecolor="white", alpha=0.9)
+
+ for patch in patches:
+ bin_center = patch.get_x() + patch.get_width() / 2
+ patch.set_facecolor(get_score_color(bin_center))
+
+ avg = np.mean(scores)
+ ax.axvline(x=avg, color=BRAND["primary_dark"], linestyle="--", linewidth=2)
+
+ ax.set_xlim(0, 100)
+ ax.set_xlabel("Poäng", fontsize=9, color=UI["muted"])
+ ax.set_ylabel("Antal sidor", fontsize=9, color=UI["muted"])
+ ax.set_title(f"{title} (medel: {avg:.0f})", fontsize=11, fontweight="bold", color=UI["text"])
+ ax.spines["top"].set_visible(False)
+ ax.spines["right"].set_visible(False)
+ ax.spines["left"].set_color(UI["border"])
+ ax.spines["bottom"].set_color(UI["border"])
+
+ plt.tight_layout()
+ buf = io.BytesIO()
+ plt.savefig(buf, format="png", bbox_inches="tight", facecolor="white", dpi=150)
+ plt.close()
+ buf.seek(0)
+ return buf
+
+
+def create_core_web_vitals_chart(metrics: dict) -> io.BytesIO:
+ """Create Core Web Vitals visualization."""
+ fig, axes = plt.subplots(1, 3, figsize=(10, 3), dpi=150)
+
+ vitals = [
+ ("LCP", metrics.get("largest-contentful-paint", {}).get("averageNumericValue", 0) / 1000,
+ "s", 2.5, 4.0),
+ ("CLS", metrics.get("cumulative-layout-shift", {}).get("averageNumericValue", 0),
+ "", 0.1, 0.25),
+ ("FCP", metrics.get("first-contentful-paint", {}).get("averageNumericValue", 0) / 1000,
+ "s", 1.8, 3.0),
+ ]
+
+ for ax, (abbr, value, unit, good, bad) in zip(axes, vitals):
+ if value <= good:
+ color = SCORE_COLORS["excellent"]
+ status = "BRA"
+ elif value <= bad:
+ color = SCORE_COLORS["needs_work"]
+ status = "BEHÖVER ARBETE"
+ else:
+ color = SCORE_COLORS["poor"]
+ status = "DÅLIGT"
+
+ ax.text(0.5, 0.65, f"{value:.2f}{unit}", fontsize=28, fontweight="bold",
+ ha="center", va="center", transform=ax.transAxes, color=color)
+ ax.text(0.5, 0.35, abbr, fontsize=14, ha="center", va="center",
+ transform=ax.transAxes, color=UI["muted"])
+ ax.text(0.5, 0.15, status, fontsize=10, ha="center", va="center",
+ transform=ax.transAxes, color=color, fontweight="bold")
+ ax.text(0.5, 0.02, f"(bra: ≤{good}{unit})", fontsize=8, ha="center", va="center",
+ transform=ax.transAxes, color=UI["muted"])
+
+ ax.axis("off")
+
+ plt.tight_layout()
+ buf = io.BytesIO()
+ plt.savefig(buf, format="png", bbox_inches="tight", facecolor="white", dpi=150)
+ plt.close()
+ buf.seek(0)
+ return buf
+
diff --git a/lib/pdf_report.py b/lib/pdf_report.py
new file mode 100644
index 0000000..1b4c6cc
--- /dev/null
+++ b/lib/pdf_report.py
@@ -0,0 +1,582 @@
+"""
+PDF report generation module with brand styling.
+"""
+
+from datetime import datetime
+from pathlib import Path
+from xml.sax.saxutils import escape as xml_escape
+from collections import defaultdict
+
+from reportlab.lib import colors
+from reportlab.lib.pagesizes import A4
+from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
+from reportlab.lib.units import cm
+from reportlab.platypus import (
+ SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle,
+ PageBreak, Image
+)
+from reportlab.lib.enums import TA_CENTER, TA_JUSTIFY, TA_RIGHT
+
+from .charts import (
+ BRAND, SCORE_COLORS, UI, CATEGORY_NAMES_SV,
+ create_gauge_chart, create_overview_chart, create_issues_chart,
+ create_savings_chart, create_score_histogram, create_core_web_vitals_chart
+)
+from .analyzer import format_bytes
+
+# Audit groups for categorization
+AUDIT_GROUPS = {
+ "images": {
+ "title": "Bildoptimering",
+ "audits": ["modern-image-formats", "uses-responsive-images", "unsized-images",
+ "offscreen-images", "uses-optimized-images", "lcp-lazy-loaded",
+ "image-size-responsive"],
+ "onetime": True,
+ "description": "Bildrelaterade problem – åtgärdas med optimeringsverktyg och temaändringar."
+ },
+ "css_js": {
+ "title": "CSS & JavaScript",
+ "audits": ["unused-css-rules", "unused-javascript", "unminified-css",
+ "unminified-javascript", "render-blocking-resources", "legacy-javascript",
+ "duplicated-javascript", "bootup-time", "mainthread-work-breakdown"],
+ "onetime": True,
+ "description": "Oanvänd och blockerande kod – optimeras på temanivå med cachingplugins."
+ },
+ "caching": {
+ "title": "Caching & Leverans",
+ "audits": ["uses-long-cache-ttl", "uses-text-compression", "uses-http2",
+ "server-response-time", "total-byte-weight"],
+ "onetime": True,
+ "description": "Server- och cachingkonfiguration – kräver serverinställningar och CDN."
+ },
+ "accessibility": {
+ "title": "Tillgänglighetsproblem",
+ "audits": ["color-contrast", "link-name", "button-name", "image-alt",
+ "meta-viewport", "bypass", "html-has-lang", "document-title",
+ "heading-order", "label", "aria-"],
+ "onetime": False,
+ "description": "Tillgänglighetsproblem som hindrar användare med funktionsnedsättning."
+ },
+ "seo": {
+ "title": "SEO-problem",
+ "audits": ["meta-description", "link-text", "crawlable-anchors",
+ "robots-txt", "canonical", "hreflang", "structured-data"],
+ "onetime": False,
+ "description": "Sökmotoroptimeringsproblem som påverkar ranking och synlighet."
+ },
+ "errors": {
+ "title": "Fel & Varningar",
+ "audits": ["errors-in-console", "deprecations", "inspector-issues"],
+ "onetime": True,
+ "description": "JavaScript-fel och föråldrade API:er som indikerar teknisk skuld."
+ },
+ "layout": {
+ "title": "Layout & CLS",
+ "audits": ["cumulative-layout-shift", "dom-size", "largest-contentful-paint-element",
+ "layout-shift-elements", "long-tasks"],
+ "onetime": False,
+ "description": "Layout-stabilitet och renderingsprestanda – kritiskt för UX."
+ }
+}
+
+
+def get_styles():
+ """Get PDF styles with brand colors."""
+ styles = getSampleStyleSheet()
+
+ brand_primary = colors.HexColor(BRAND["primary"])
+ brand_dark = colors.HexColor(BRAND["primary_dark"])
+ text_color = colors.HexColor(UI["text"])
+ muted_color = colors.HexColor(UI["muted"])
+
+ return {
+ "title": ParagraphStyle(
+ "Title", parent=styles["Heading1"], fontSize=28, spaceAfter=15,
+ alignment=TA_CENTER, textColor=brand_dark
+ ),
+ "h1": ParagraphStyle(
+ "H1", parent=styles["Heading1"], fontSize=16, spaceBefore=12,
+ spaceAfter=8, textColor=brand_dark
+ ),
+ "h2": ParagraphStyle(
+ "H2", parent=styles["Heading2"], fontSize=12, spaceBefore=10,
+ spaceAfter=5, textColor=text_color
+ ),
+ "h3": ParagraphStyle(
+ "H3", parent=styles["Heading3"], fontSize=10, spaceBefore=6,
+ spaceAfter=3, textColor=text_color
+ ),
+ "body": ParagraphStyle(
+ "Body", parent=styles["Normal"], fontSize=9, spaceAfter=5,
+ alignment=TA_JUSTIFY, leading=12, textColor=text_color
+ ),
+ "body_bold": ParagraphStyle(
+ "BodyBold", parent=styles["Normal"], fontSize=9, spaceAfter=5,
+ alignment=TA_JUSTIFY, leading=12, fontName="Helvetica-Bold",
+ textColor=text_color
+ ),
+ "small": ParagraphStyle(
+ "Small", parent=styles["Normal"], fontSize=8,
+ textColor=muted_color, leading=10, spaceAfter=3
+ ),
+ "alert": ParagraphStyle(
+ "Alert", parent=styles["Normal"], fontSize=10,
+ textColor=colors.HexColor(SCORE_COLORS["poor"]), fontName="Helvetica-Bold"
+ ),
+ "warning": ParagraphStyle(
+ "Warning", parent=styles["Normal"], fontSize=10,
+ textColor=colors.HexColor(SCORE_COLORS["needs_work"]), fontName="Helvetica-Bold"
+ ),
+ "footer": ParagraphStyle(
+ "Footer", parent=styles["Normal"], fontSize=8,
+ textColor=muted_color, alignment=TA_RIGHT
+ ),
+ }
+
+
+def generate_pdf(
+ output_path: Path,
+ data: dict,
+ all_audits: dict,
+ resource_issues: dict,
+ element_issues: dict,
+ page_count: int,
+ customer_name: str = "",
+ site_url: str = "",
+ logo_path: Path = None,
+ consultant_name: str = "",
+ category_names: dict = None
+):
+ """Generate comprehensive PDF report with branding."""
+ if category_names is None:
+ category_names = CATEGORY_NAMES_SV
+
+ site_display = site_url.replace("https://", "").replace("http://", "").rstrip("/")
+
+ doc = SimpleDocTemplate(
+ str(output_path), pagesize=A4,
+ rightMargin=1.8*cm, leftMargin=1.8*cm, topMargin=1.8*cm, bottomMargin=2*cm,
+ )
+
+ s = get_styles()
+ story = []
+
+ brand_primary = colors.HexColor(BRAND["primary"])
+ brand_dark = colors.HexColor(BRAND["primary_dark"])
+ border_color = colors.HexColor(UI["border"])
+ light_bg = colors.HexColor(UI["light_bg"])
+
+ # ===== TITLE PAGE =====
+ story.append(Spacer(1, 1*cm))
+
+ # Logo
+ if logo_path and logo_path.exists():
+ try:
+ story.append(Image(str(logo_path), width=3*cm, height=3*cm))
+ story.append(Spacer(1, 0.5*cm))
+ except Exception:
+ pass
+
+ story.append(Paragraph("Webbplatsanalys", s["title"]))
+ story.append(Paragraph(site_display, ParagraphStyle(
+ "Sub", parent=s["title"], fontSize=20, textColor=colors.HexColor(UI["muted"])
+ )))
+
+ if customer_name:
+ story.append(Spacer(1, 0.3*cm))
+ story.append(Paragraph(f"Kund: {customer_name}", ParagraphStyle(
+ "Customer", parent=s["body"], fontSize=11, alignment=TA_CENTER
+ )))
+
+ story.append(Spacer(1, 1*cm))
+
+ # Overall score gauge
+ overall = data["summary"]["score"] * 100
+ gauge = create_gauge_chart(overall, "Övergripande betyg")
+ story.append(Image(gauge, width=10*cm, height=8*cm))
+
+ story.append(Spacer(1, 0.5*cm))
+
+ # Status assessment
+ if overall < 50:
+ story.append(Paragraph(
+ "Webbplatsen har betydande prestandaproblem som kräver omedelbar åtgärd.",
+ s["alert"]))
+ elif overall < 75:
+ story.append(Paragraph(
+ "Webbplatsen har flera förbättringsområden som påverkar användarupplevelse och SEO.",
+ s["warning"]))
+
+ story.append(Spacer(1, 0.5*cm))
+
+ # Key stats table
+ stats_data = [
+ ["Analyserade sidor", str(page_count)],
+ ["Identifierade problemtyper", str(len(all_audits))],
+ ["Resursproblem", str(len(resource_issues))],
+ ["Elementproblem", str(len(element_issues))],
+ ["Rapport genererad", datetime.now().strftime("%Y-%m-%d")],
+ ]
+ stats_table = Table(stats_data, colWidths=[8*cm, 5*cm])
+ stats_table.setStyle(TableStyle([
+ ("FONTSIZE", (0, 0), (-1, -1), 10),
+ ("ALIGN", (1, 0), (1, -1), "RIGHT"),
+ ("TEXTCOLOR", (0, 0), (0, -1), colors.HexColor(UI["muted"])),
+ ("TEXTCOLOR", (1, 0), (1, -1), brand_dark),
+ ("FONTNAME", (1, 0), (1, -1), "Helvetica-Bold"),
+ ("LINEBELOW", (0, -1), (-1, -1), 1, brand_primary),
+ ]))
+ story.append(stats_table)
+
+ if consultant_name:
+ story.append(Spacer(1, 0.5*cm))
+ story.append(Paragraph(f"Utförd av: {consultant_name}", s["footer"]))
+
+ story.append(PageBreak())
+
+ # ===== EXECUTIVE SUMMARY =====
+ story.append(Paragraph("Sammanfattning", s["h1"]))
+
+ summary_text = f"""
+ Denna rapport presenterar resultatet av en teknisk analys av webbplatsen {site_display}.
+ Totalt har {page_count} sidor granskats med avseende på prestanda, tillgänglighet,
+ bästa praxis och sökmotoroptimering.
+ """
+ story.append(Paragraph(summary_text, s["body"]))
+
+ # Performance summary
+ perf_score = data["summary"]["categories"]["performance"]["averageScore"] * 100
+ a11y_score = data["summary"]["categories"]["accessibility"]["averageScore"] * 100
+ bp_score = data["summary"]["categories"]["best-practices"]["averageScore"] * 100
+ seo_score = data["summary"]["categories"]["seo"]["averageScore"] * 100
+
+ findings = []
+ if perf_score < 70:
+ findings.append(f"Prestanda ({perf_score:.0f}%): Problem med laddningstider och rendering.")
+ if a11y_score < 90:
+ findings.append(f"Tillgänglighet ({a11y_score:.0f}%): Brister som påverkar användare.")
+ if bp_score < 80:
+ findings.append(f"Bästa praxis ({bp_score:.0f}%): Tekniska brister.")
+ if seo_score < 90:
+ findings.append(f"SEO ({seo_score:.0f}%): Optimeringsmöjligheter.")
+
+ if findings:
+ story.append(Paragraph("Huvudsakliga fynd:", s["body"]))
+ for f in findings:
+ story.append(Paragraph(f"• {f}", s["body"]))
+
+ story.append(Spacer(1, 0.3*cm))
+
+ # Category chart
+ cat_chart = create_overview_chart(data["summary"]["categories"], category_names)
+ story.append(Image(cat_chart, width=16*cm, height=6.5*cm))
+
+ story.append(Spacer(1, 0.3*cm))
+
+ # Category table
+ cat_table_data = [["Kategori", "Medel", "Lägsta", "Högsta", "Bedömning"]]
+ for cat_id, cat_info in data["summary"]["categories"].items():
+ avg = cat_info["averageScore"] * 100
+ scores = cat_info["scores"]
+ min_s, max_s = min(scores) * 100, max(scores) * 100
+
+ if avg >= 90:
+ status = "✓ Godkänt"
+ elif avg >= 50:
+ status = "⚠ Kräver åtgärd"
+ else:
+ status = "✗ Kritiskt"
+
+ cat_table_data.append([
+ category_names.get(cat_id, cat_id),
+ f"{avg:.0f}%", f"{min_s:.0f}%", f"{max_s:.0f}%", status
+ ])
+
+ t = Table(cat_table_data, colWidths=[5*cm, 2*cm, 2*cm, 2*cm, 3*cm])
+ t.setStyle(TableStyle([
+ ("BACKGROUND", (0, 0), (-1, 0), brand_dark),
+ ("TEXTCOLOR", (0, 0), (-1, 0), colors.white),
+ ("ALIGN", (1, 0), (-1, -1), "CENTER"),
+ ("FONTSIZE", (0, 0), (-1, -1), 9),
+ ("GRID", (0, 0), (-1, -1), 0.5, border_color),
+ ("ROWBACKGROUNDS", (0, 1), (-1, -1), [colors.white, light_bg])
+ ]))
+ story.append(t)
+
+ story.append(PageBreak())
+
+ # ===== CORE WEB VITALS =====
+ story.append(Paragraph("Core Web Vitals", s["h1"]))
+ story.append(Paragraph(
+ "Core Web Vitals är Googles officiella mätvärden för användarupplevelse. "
+ "Dessa påverkar direkt webbplatsens ranking i sökresultat.", s["body"]))
+
+ cwv_chart = create_core_web_vitals_chart(data["summary"]["metrics"])
+ story.append(Image(cwv_chart, width=16*cm, height=5*cm))
+
+ # Metrics table
+ metrics_data = [["Mätvärde", "Värde", "Bra", "Dåligt", "Status"]]
+ metric_info = [
+ ("LCP (Largest Contentful Paint)", "largest-contentful-paint", 1000, "s", 2.5, 4.0),
+ ("FCP (First Contentful Paint)", "first-contentful-paint", 1000, "s", 1.8, 3.0),
+ ("CLS (Cumulative Layout Shift)", "cumulative-layout-shift", 1, "", 0.1, 0.25),
+ ("TBT (Total Blocking Time)", "total-blocking-time", 1, "ms", 200, 600),
+ ("TTI (Time to Interactive)", "interactive", 1000, "s", 3.8, 7.3),
+ ]
+
+ for name, key, divisor, unit, good, bad in metric_info:
+ val = data["summary"]["metrics"].get(key, {}).get("averageNumericValue", 0) / divisor
+ status = "✓" if val <= good else "⚠" if val <= bad else "✗"
+ metrics_data.append([name, f"{val:.2f}{unit}", f"≤{good}{unit}", f">{bad}{unit}", status])
+
+ mt = Table(metrics_data, colWidths=[6.5*cm, 2.5*cm, 2*cm, 2*cm, 1.5*cm])
+ mt.setStyle(TableStyle([
+ ("BACKGROUND", (0, 0), (-1, 0), brand_dark),
+ ("TEXTCOLOR", (0, 0), (-1, 0), colors.white),
+ ("ALIGN", (1, 0), (-1, -1), "CENTER"),
+ ("FONTSIZE", (0, 0), (-1, -1), 8),
+ ("GRID", (0, 0), (-1, -1), 0.5, border_color),
+ ("ROWBACKGROUNDS", (0, 1), (-1, -1), [colors.white, light_bg])
+ ]))
+ story.append(mt)
+
+ story.append(PageBreak())
+
+ # ===== SCORE DISTRIBUTION =====
+ story.append(Paragraph("Poängfördelning per kategori", s["h1"]))
+ story.append(Paragraph(
+ f"Följande diagram visar hur de {page_count} sidorna presterar. "
+ "Majoriteten bör ligga i det gröna området (≥90).", s["body"]))
+
+ hist_chart = create_score_histogram(data.get("routes", []), category_names)
+ story.append(Image(hist_chart, width=16*cm, height=11*cm))
+
+ story.append(PageBreak())
+
+ # ===== MOST COMMON ISSUES =====
+ story.append(Paragraph("Vanligaste problemen", s["h1"]))
+ story.append(Paragraph(
+ "Problem som påverkar >80% av sidorna indikerar systemiska brister.", s["body"]))
+
+ issues_chart = create_issues_chart(all_audits, page_count, 12)
+ story.append(Image(issues_chart, width=16*cm, height=10*cm))
+
+ story.append(PageBreak())
+
+ # ===== POTENTIAL SAVINGS =====
+ story.append(Paragraph("Potentiella besparingar", s["h1"]))
+
+ total_savings = sum(a["total_wasted_bytes"] for a in all_audits.values())
+ story.append(Paragraph(
+ f"Total potentiell besparing: {format_bytes(total_savings)}", s["body_bold"]))
+
+ savings_chart = create_savings_chart(all_audits)
+ if savings_chart:
+ story.append(Image(savings_chart, width=15*cm, height=6*cm))
+
+ story.append(PageBreak())
+
+ # ===== DETAILED ISSUES =====
+ story.append(Paragraph("Detaljerade problem", s["h1"]))
+
+ for group_id, group_info in AUDIT_GROUPS.items():
+ group_audits = []
+ for audit_id, audit_data in all_audits.items():
+ for pattern in group_info["audits"]:
+ if pattern.endswith("-"):
+ if audit_id.startswith(pattern):
+ group_audits.append((audit_id, audit_data))
+ break
+ elif audit_id == pattern:
+ group_audits.append((audit_id, audit_data))
+ break
+
+ if not group_audits:
+ continue
+
+ group_audits.sort(key=lambda x: x[1]["count"], reverse=True)
+ total_in_group = sum(a[1]["count"] for a in group_audits)
+ if total_in_group == 0:
+ continue
+
+ label = "ENGÅNGSÅTGÄRD" if group_info["onetime"] else "SIDSPECIFIK"
+ story.append(Paragraph(
+ f"{group_info['title']} [{label}]", s["h2"]))
+ story.append(Paragraph(group_info["description"], s["small"]))
+
+ for audit_id, audit_data in group_audits[:8]:
+ if audit_data["count"] == 0:
+ continue
+
+ title = xml_escape(audit_data["title"][:65])
+ pct = (audit_data["count"] / page_count) * 100
+
+ story.append(Paragraph(f"• {title}", s["body"]))
+
+ details = [f"{audit_data['count']}/{page_count} sidor ({pct:.0f}%)"]
+ if audit_data["total_wasted_bytes"] > 1024:
+ details.append(f"Besparing: {format_bytes(audit_data['total_wasted_bytes'])}")
+
+ story.append(Paragraph(" " + " | ".join(details), s["small"]))
+
+ story.append(Spacer(1, 0.2*cm))
+
+ story.append(PageBreak())
+
+ # ===== RESOURCE ISSUES =====
+ story.append(Paragraph("Resurser som kräver åtgärd", s["h1"]))
+
+ resource_by_audit = defaultdict(list)
+ for (audit_id, url), rdata in resource_issues.items():
+ if rdata["count"] >= 10 and rdata["wasted_bytes"] > 5000:
+ resource_by_audit[audit_id].append((url, rdata))
+
+ for audit_id in ["unused-css-rules", "unused-javascript", "render-blocking-resources",
+ "modern-image-formats", "uses-long-cache-ttl"]:
+ resources = resource_by_audit.get(audit_id, [])
+ if not resources:
+ continue
+
+ audit_title = all_audits.get(audit_id, {}).get("title", audit_id)
+ story.append(Paragraph(f"{xml_escape(audit_title[:50])}", s["h3"]))
+
+ resources.sort(key=lambda x: x[1]["wasted_bytes"], reverse=True)
+
+ resource_table = [["Resurs", "Sidor", "Bortkastade data"]]
+ for url, rdata in resources[:8]:
+ url_display = "..." + url[-42:] if len(url) > 45 else url
+ resource_table.append([
+ url_display, str(rdata["count"]), format_bytes(rdata["wasted_bytes"])
+ ])
+
+ if len(resource_table) > 1:
+ rt = Table(resource_table, colWidths=[9*cm, 2*cm, 3*cm])
+ rt.setStyle(TableStyle([
+ ("BACKGROUND", (0, 0), (-1, 0), brand_dark),
+ ("TEXTCOLOR", (0, 0), (-1, 0), colors.white),
+ ("FONTSIZE", (0, 0), (-1, -1), 7),
+ ("FONTNAME", (0, 1), (0, -1), "Courier"),
+ ("ALIGN", (1, 0), (-1, -1), "CENTER"),
+ ("GRID", (0, 0), (-1, -1), 0.5, border_color),
+ ("ROWBACKGROUNDS", (0, 1), (-1, -1), [colors.white, light_bg])
+ ]))
+ story.append(rt)
+ story.append(Spacer(1, 0.2*cm))
+
+ story.append(PageBreak())
+
+ # ===== WORST PAGES =====
+ story.append(Paragraph("Sidor som kräver mest arbete", s["h1"]))
+
+ routes = data.get("routes", [])
+ for cat_id, cat_name in [("performance", "Prestanda"), ("accessibility", "Tillgänglighet")]:
+ story.append(Paragraph(f"{cat_name} – sämsta 10", s["h2"]))
+
+ sorted_routes = sorted(
+ routes, key=lambda r: r.get("categories", {}).get(cat_id, {}).get("score", 1)
+ )[:10]
+
+ worst_table = [["Sida", "Poäng"]]
+ for route in sorted_routes:
+ score = route.get("categories", {}).get(cat_id, {}).get("score", 1) * 100
+ path = route.get("path", "/")
+ if len(path) > 50:
+ path = path[:47] + "..."
+ worst_table.append([path, f"{score:.0f}%"])
+
+ wt = Table(worst_table, colWidths=[12*cm, 2.5*cm])
+ wt.setStyle(TableStyle([
+ ("BACKGROUND", (0, 0), (-1, 0), brand_dark),
+ ("TEXTCOLOR", (0, 0), (-1, 0), colors.white),
+ ("FONTSIZE", (0, 0), (-1, -1), 8),
+ ("ALIGN", (1, 0), (1, -1), "CENTER"),
+ ("GRID", (0, 0), (-1, -1), 0.5, border_color),
+ ("ROWBACKGROUNDS", (0, 1), (-1, -1), [colors.white, light_bg])
+ ]))
+ story.append(wt)
+ story.append(Spacer(1, 0.3*cm))
+
+ story.append(PageBreak())
+
+ # ===== RECOMMENDATIONS =====
+ story.append(Paragraph("Rekommenderade åtgärder", s["h1"]))
+
+ story.append(Paragraph("Fas 1: Engångsåtgärder", s["h2"]))
+ story.append(Paragraph("Åtgärdas en gång, förbättrar alla sidor automatiskt.", s["small"]))
+
+ phase1 = [
+ ("Bildoptimering",
+ f"WebP-konvertering och komprimering. Besparing: {format_bytes(all_audits.get('modern-image-formats', {}).get('total_wasted_bytes', 0))}.",
+ "2-4 tim"),
+ ("Caching och minifiering",
+ "Aktivera minifiering av CSS/JS, lazy loading och browser caching.",
+ "4-6 tim"),
+ ("Render-blocking resurser",
+ "Kritisk CSS-inlining och uppskjuten JavaScript-laddning.",
+ "2-4 tim"),
+ ("Console-fel",
+ f"Åtgärda JavaScript-fel på {all_audits.get('errors-in-console', {}).get('count', 0)} sidor.",
+ "2-4 tim"),
+ ]
+
+ for title, desc, time in phase1:
+ story.append(Paragraph(f"{title} [{time}]", s["body"]))
+ story.append(Paragraph(desc, s["small"]))
+
+ story.append(Spacer(1, 0.3*cm))
+ story.append(Paragraph("Fas 2: Sidspecifika förbättringar", s["h2"]))
+
+ phase2 = [
+ ("Färgkontrast",
+ f"{all_audits.get('color-contrast', {}).get('count', 0)} sidor har otillräcklig kontrast.",
+ f"{all_audits.get('color-contrast', {}).get('count', 0) * 15} min"),
+ ("Länktexter",
+ f"{all_audits.get('link-name', {}).get('count', 0)} sidor har länkar utan beskrivande text.",
+ f"{all_audits.get('link-name', {}).get('count', 0) * 10} min"),
+ ("Layout Shift (CLS)",
+ "Definiera dimensioner på bilder, undvik dynamiskt innehåll.",
+ "4-8 tim"),
+ ]
+
+ for title, desc, time in phase2:
+ story.append(Paragraph(f"{title} [{time}]", s["body"]))
+ story.append(Paragraph(desc, s["small"]))
+
+ story.append(Spacer(1, 0.5*cm))
+
+ # Time estimate
+ story.append(Paragraph("Sammanfattning arbetsinsats", s["h2"]))
+
+ total_time_low = int(15 + page_count * 0.25)
+ total_time_high = int(28 + page_count * 0.3)
+
+ time_data = [
+ ["Fas", "Åtgärd", "Tid", "Påverkan"],
+ ["1", "Bildoptimering + CDN", "4-8 tim", f"{page_count} sidor"],
+ ["1", "Caching & minifiering", "4-6 tim", f"{page_count} sidor"],
+ ["1", "Grundläggande a11y", "1-2 tim", f"{page_count} sidor"],
+ ["1", "Felsökning", "2-4 tim", f"{page_count} sidor"],
+ ["2", "Färgkontrast & länkar", f"{int(page_count * 0.2)}-{int(page_count * 0.3)} tim", "Specifika sidor"],
+ ["2", "CLS-optimering", "4-8 tim", "Berörda mallar"],
+ ["", "TOTALT ESTIMAT", f"{total_time_low}-{total_time_high} tim", ""],
+ ]
+
+ tt = Table(time_data, colWidths=[1.2*cm, 7*cm, 3*cm, 3*cm])
+ tt.setStyle(TableStyle([
+ ("BACKGROUND", (0, 0), (-1, 0), brand_dark),
+ ("TEXTCOLOR", (0, 0), (-1, 0), colors.white),
+ ("FONTSIZE", (0, 0), (-1, -1), 9),
+ ("ALIGN", (0, 0), (0, -1), "CENTER"),
+ ("ALIGN", (2, 0), (3, -1), "CENTER"),
+ ("GRID", (0, 0), (-1, -1), 0.5, border_color),
+ ("ROWBACKGROUNDS", (0, 1), (-1, -2), [colors.white, light_bg]),
+ ("BACKGROUND", (0, -1), (-1, -1), brand_primary),
+ ("TEXTCOLOR", (0, -1), (-1, -1), colors.white),
+ ("FONTNAME", (0, -1), (-1, -1), "Helvetica-Bold"),
+ ("FONTSIZE", (0, -1), (-1, -1), 10),
+ ]))
+ story.append(tt)
+
+ # Build PDF
+ doc.build(story)
+
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..900e245
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,8 @@
+# Webbplatsanalys Report Generator
+# Install: pip install -r requirements.txt
+
+reportlab>=4.0
+matplotlib>=3.7
+numpy>=1.24
+pillow>=9.0
+
diff --git a/s-logo.png b/s-logo.png
new file mode 100644
index 0000000..1ebfafb
Binary files /dev/null and b/s-logo.png differ
diff --git a/shell.nix b/shell.nix
new file mode 100644
index 0000000..1c13d0c
--- /dev/null
+++ b/shell.nix
@@ -0,0 +1,17 @@
+{ pkgs ? import {} }:
+
+pkgs.mkShell {
+ buildInputs = with pkgs; [
+ python313
+ python313Packages.reportlab
+ python313Packages.matplotlib
+ python313Packages.numpy
+ python313Packages.pillow # For logo handling
+ python313Packages.cairosvg # For SVG logo conversion
+ ];
+
+ shellHook = ''
+ echo "Webbplatsanalys redo. Kör: python webbanalys.py"
+ '';
+}
+
diff --git a/unlighthouse.config.ts b/unlighthouse.config.ts
new file mode 100644
index 0000000..86270f0
--- /dev/null
+++ b/unlighthouse.config.ts
@@ -0,0 +1,6 @@
+export default defineUnlighthouseConfig({
+ server: {
+ open: false,
+ },
+})
+
diff --git a/webbanalys.py b/webbanalys.py
new file mode 100644
index 0000000..d05d7ec
--- /dev/null
+++ b/webbanalys.py
@@ -0,0 +1,482 @@
+#!/usr/bin/env python3
+"""
+╔═══════════════════════════════════════════════════════════════════════╗
+║ WEBBPLATSANALYS RAPPORTGENERATOR ║
+║ ║
+║ Analysera webbplatser och generera professionella PDF-rapporter ║
+╚═══════════════════════════════════════════════════════════════════════╝
+
+Usage:
+ python webbanalys.py scan # Run analysis
+ python webbanalys.py generate # Generate PDF report
+ python webbanalys.py run # Scan + generate in one step
+
+Requirements (NixOS):
+ nix-shell shell.nix
+
+Requirements (pip):
+ pip install -r requirements.txt
+"""
+
+import argparse
+import json
+import subprocess
+import shutil
+import sys
+from pathlib import Path
+from datetime import datetime
+
+# Ensure lib is importable
+sys.path.insert(0, str(Path(__file__).parent))
+
+from lib.analyzer import load_ci_result, load_all_audits
+from lib.pdf_report import generate_pdf
+
+
+BANNER = """
+╔═══════════════════════════════════════════════════════════════════════╗
+║ WEBBPLATSANALYS RAPPORTGENERATOR ║
+╚═══════════════════════════════════════════════════════════════════════╝
+"""
+
+
+def load_config(config_path: Path) -> dict:
+ """Load project configuration from JSON file."""
+ if config_path.exists():
+ with open(config_path, "r", encoding="utf-8") as f:
+ return json.load(f)
+ return {}
+
+
+def save_config(config_path: Path, config: dict):
+ """Save project configuration to JSON file."""
+ with open(config_path, "w", encoding="utf-8") as f:
+ json.dump(config, f, indent=2, ensure_ascii=False)
+
+
+def find_data_files(base_path: Path) -> tuple[Path, Path]:
+ """Find ci-result.json and reports directory."""
+ search_paths = [
+ base_path / "rapport",
+ base_path / ".unlighthouse",
+ base_path,
+ ]
+
+ ci_result = None
+ reports_dir = None
+
+ for path in search_paths:
+ if not path.exists():
+ continue
+
+ candidate = path / "ci-result.json"
+ if candidate.exists():
+ ci_result = candidate
+
+ candidate = path / "reports"
+ if candidate.exists() and candidate.is_dir():
+ reports_dir = candidate
+
+ if ci_result and reports_dir:
+ break
+
+ return ci_result, reports_dir
+
+
+def find_logo(base_path: Path) -> Path:
+ """Find logo file in project."""
+ # Prefer PNG/JPG, then SVG
+ for pattern in ["*logo*.png", "*logo*.jpg", "*.png", "*.jpg"]:
+ for f in base_path.glob(pattern):
+ if f.is_file() and f.suffix.lower() in [".png", ".jpg", ".jpeg"]:
+ return f
+ # Check for SVG (will be converted)
+ for pattern in ["*logo*.svg", "*.svg"]:
+ for f in base_path.glob(pattern):
+ if f.is_file():
+ return f
+ return None
+
+
+def convert_svg_to_png(svg_path: Path) -> Path:
+ """Convert SVG to PNG for PDF embedding."""
+ try:
+ import cairosvg
+ png_path = svg_path.with_suffix(".png")
+ if not png_path.exists() or png_path.stat().st_mtime < svg_path.stat().st_mtime:
+ cairosvg.svg2png(url=str(svg_path), write_to=str(png_path), output_width=200)
+ return png_path
+ except ImportError:
+ return None
+ except Exception:
+ return None
+
+
+def cmd_generate(args, base_path: Path):
+ """Generate PDF report."""
+ config_path = base_path / "webbanalys.json"
+ config = load_config(config_path)
+
+ # Find data files
+ print("\n🔍 Söker efter analysdata...")
+
+ ci_result_path, reports_dir = find_data_files(base_path)
+
+ if not ci_result_path:
+ print("❌ Kunde inte hitta ci-result.json")
+ print(" Kör först: unlighthouse-ci --site ")
+ print(f" Sökte i: {base_path}")
+ sys.exit(1)
+
+ if not reports_dir:
+ print("❌ Kunde inte hitta reports/ katalog")
+ sys.exit(1)
+
+ print(f" ✓ Hittade data i: {ci_result_path.parent}")
+
+ # Determine parameters (CLI > config > default)
+ customer = args.customer or config.get("customer", "")
+ site_url = args.url or config.get("site_url", "")
+ consultant = args.consultant or config.get("consultant", "")
+
+ # Find logo
+ logo_path = None
+ if args.logo:
+ logo_path = Path(args.logo)
+ elif config.get("logo"):
+ logo_path = base_path / config["logo"]
+ else:
+ logo_path = find_logo(base_path)
+
+ # Convert SVG to PNG if needed
+ if logo_path and logo_path.exists():
+ if logo_path.suffix.lower() == ".svg":
+ png_path = convert_svg_to_png(logo_path)
+ if png_path:
+ logo_path = png_path
+ print(f" ✓ Logotyp: {logo_path.name} (konverterad från SVG)")
+ else:
+ print(f" ⚠ Kunde inte konvertera SVG-logotyp")
+ logo_path = None
+ else:
+ print(f" ✓ Logotyp: {logo_path.name}")
+
+ # Load data
+ print("\n📊 Laddar analysdata...")
+ data = load_ci_result(ci_result_path)
+
+ # Extract site URL from data if not provided
+ if not site_url:
+ routes = data.get("routes", [])
+ if routes:
+ first_path = routes[0].get("path", "")
+ # Try to construct from common patterns
+ for route in routes[:5]:
+ path = route.get("path", "")
+ if path.startswith("http"):
+ site_url = "/".join(path.split("/")[:3])
+ break
+
+ print(f" Webbplats: {site_url or '(okänd)'}")
+ if customer:
+ print(f" Kund: {customer}")
+
+ # Analyze
+ print("\n🔬 Analyserar sidor...")
+ all_audits, resource_issues, element_issues, page_count = load_all_audits(
+ reports_dir, site_url
+ )
+
+ print(f" Sidor analyserade: {page_count}")
+ print(f" Problemtyper: {len(all_audits)}")
+ print(f" Resursproblem: {len(resource_issues)}")
+ print(f" Elementproblem: {len(element_issues)}")
+
+ # Overall score
+ overall = data["summary"]["score"] * 100
+ if overall >= 90:
+ score_emoji = "🟢"
+ elif overall >= 50:
+ score_emoji = "🟡"
+ else:
+ score_emoji = "🔴"
+ print(f"\n Övergripande betyg: {score_emoji} {overall:.0f}/100")
+
+ # Determine output path
+ if args.output:
+ output_path = Path(args.output)
+ else:
+ date_str = datetime.now().strftime("%Y%m%d")
+ site_slug = site_url.replace("https://", "").replace("http://", "").replace("/", "_").replace(".", "_")
+ output_path = base_path / f"rapport_{site_slug}_{date_str}.pdf"
+
+ # Generate report
+ print(f"\n📝 Genererar rapport...")
+ generate_pdf(
+ output_path=output_path,
+ data=data,
+ all_audits=all_audits,
+ resource_issues=resource_issues,
+ element_issues=element_issues,
+ page_count=page_count,
+ customer_name=customer,
+ site_url=site_url,
+ logo_path=logo_path if logo_path and logo_path.exists() else None,
+ consultant_name=consultant
+ )
+
+ file_size = output_path.stat().st_size / 1024
+ print(f"\n✅ Rapport genererad!")
+ print(f" 📄 {output_path}")
+ print(f" 📦 {file_size:.0f} KB")
+
+ # Offer to save config
+ if not config and (customer or site_url):
+ print("\n💾 Spara inställningar för framtida rapporter? (y/n): ", end="")
+ try:
+ if input().lower() == "y":
+ new_config = {}
+ if customer:
+ new_config["customer"] = customer
+ if site_url:
+ new_config["site_url"] = site_url
+ if consultant:
+ new_config["consultant"] = consultant
+ if logo_path:
+ new_config["logo"] = str(logo_path.relative_to(base_path))
+ save_config(config_path, new_config)
+ print(f" ✓ Sparad till {config_path.name}")
+ except (EOFError, KeyboardInterrupt):
+ pass
+
+
+def cmd_init(args, base_path: Path):
+ """Initialize project configuration."""
+ config_path = base_path / "webbanalys.json"
+
+ print("\n🔧 Konfigurera projekt")
+ print(" (tryck Enter för att hoppa över)\n")
+
+ config = load_config(config_path)
+
+ try:
+ customer = input(f" Kundnamn [{config.get('customer', '')}]: ").strip()
+ if customer:
+ config["customer"] = customer
+
+ site_url = input(f" Webbplats URL [{config.get('site_url', '')}]: ").strip()
+ if site_url:
+ config["site_url"] = site_url
+
+ consultant = input(f" Konsultnamn [{config.get('consultant', '')}]: ").strip()
+ if consultant:
+ config["consultant"] = consultant
+
+ save_config(config_path, config)
+ print(f"\n✅ Konfiguration sparad till {config_path.name}")
+
+ except (EOFError, KeyboardInterrupt):
+ print("\n Avbrutet.")
+
+
+def cmd_info(args, base_path: Path):
+ """Show project information."""
+ config_path = base_path / "webbanalys.json"
+ config = load_config(config_path)
+
+ print("\n📋 Projektinformation")
+ print(f" Mapp: {base_path}")
+
+ if config:
+ print(f"\n Konfiguration ({config_path.name}):")
+ for key, value in config.items():
+ print(f" {key}: {value}")
+ else:
+ print(f"\n ⚠ Ingen konfiguration hittad")
+ print(f" Kör: python webbanalys.py init")
+
+ # Check for data
+ ci_result, reports_dir = find_data_files(base_path)
+ print(f"\n Analysdata:")
+ if ci_result:
+ print(f" ✓ ci-result.json: {ci_result}")
+ else:
+ print(f" ✗ ci-result.json saknas")
+
+ if reports_dir:
+ report_count = len(list(reports_dir.glob("*/lighthouse.json")))
+ print(f" ✓ reports/: {report_count} sidor")
+ else:
+ print(f" ✗ reports/ saknas")
+
+ # Check for logo
+ logo = find_logo(base_path)
+ if logo:
+ print(f" ✓ Logotyp: {logo.name}")
+
+
+def cmd_scan(args, base_path: Path):
+ """Run Unlighthouse scan."""
+ config_path = base_path / "webbanalys.json"
+ config = load_config(config_path)
+
+ # Determine URL
+ site_url = args.url or config.get("site_url", "")
+ if not site_url:
+ print("❌ Ingen URL angiven.")
+ print(" Använd: python webbanalys.py scan https://example.com")
+ print(" Eller kör 'python webbanalys.py init' först")
+ sys.exit(1)
+
+ # Ensure URL has protocol
+ if not site_url.startswith("http"):
+ site_url = "https://" + site_url
+
+ samples = args.samples or config.get("samples", 3)
+ output_path = base_path / "rapport"
+
+ print(f"\n🔍 Startar webbanalys...")
+ print(f" URL: {site_url}")
+ print(f" Samples: {samples}")
+ print(f" Output: {output_path}")
+
+ # Check for pnpm
+ pnpm_path = shutil.which("pnpm")
+ npx_path = shutil.which("npx")
+
+ if pnpm_path:
+ cmd = [
+ "pnpm", "dlx", "-p", "@unlighthouse/cli",
+ "unlighthouse-ci",
+ "--site", site_url,
+ "--samples", str(samples),
+ "--output-path", str(output_path),
+ "--reporter", "jsonExpanded"
+ ]
+ elif npx_path:
+ cmd = [
+ "npx", "-y", "@unlighthouse/cli",
+ "unlighthouse-ci",
+ "--site", site_url,
+ "--samples", str(samples),
+ "--output-path", str(output_path),
+ "--reporter", "jsonExpanded"
+ ]
+ else:
+ print("❌ Varken pnpm eller npx hittades.")
+ print(" Installera Node.js och pnpm/npm först.")
+ sys.exit(1)
+
+ print(f"\n Kör: {' '.join(cmd)}\n")
+ print("─" * 70)
+
+ try:
+ result = subprocess.run(cmd, cwd=base_path)
+ print("─" * 70)
+
+ if result.returncode == 0:
+ print("\n✅ Analys klar!")
+
+ # Update config with URL
+ if site_url and site_url != config.get("site_url"):
+ config["site_url"] = site_url
+ config["samples"] = samples
+ save_config(config_path, config)
+
+ return True
+ else:
+ print(f"\n❌ Analys misslyckades (kod {result.returncode})")
+ return False
+
+ except KeyboardInterrupt:
+ print("\n\n⚠ Avbruten av användaren")
+ return False
+ except Exception as e:
+ print(f"\n❌ Fel: {e}")
+ return False
+
+
+def cmd_run(args, base_path: Path):
+ """Run scan + generate in one step."""
+ # First scan
+ if cmd_scan(args, base_path):
+ print("\n" + "═" * 70 + "\n")
+ # Then generate
+ cmd_generate(args, base_path)
+
+
+def main():
+ parser = argparse.ArgumentParser(
+ description="Analysera webbplatser och generera PDF-rapporter",
+ formatter_class=argparse.RawDescriptionHelpFormatter,
+ epilog="""
+Kommandon:
+ scan Kör Unlighthouse-analys
+ generate Generera PDF-rapport från befintlig data
+ run Kör analys + generera rapport (allt-i-ett)
+ init Konfigurera projekt
+ info Visa projektinformation
+
+Exempel:
+ python webbanalys.py scan https://example.com
+ python webbanalys.py scan -u https://example.com -s 5
+ python webbanalys.py generate -c "Företag AB"
+ python webbanalys.py run https://example.com -c "Företag AB"
+ """
+ )
+
+ subparsers = parser.add_subparsers(dest="command", help="Kommando")
+
+ # Scan command
+ scan_parser = subparsers.add_parser("scan", help="Kör Unlighthouse-analys")
+ scan_parser.add_argument("url", nargs="?", help="Webbplats-URL")
+ scan_parser.add_argument("--samples", "-s", type=int, default=3, help="Antal samples per sida (default: 3)")
+
+ # Generate command
+ gen_parser = subparsers.add_parser("generate", help="Generera PDF-rapport")
+ gen_parser.add_argument("--customer", "-c", help="Kundnamn")
+ gen_parser.add_argument("--url", "-u", help="Webbplats-URL")
+ gen_parser.add_argument("--consultant", help="Konsultnamn")
+ gen_parser.add_argument("--logo", "-l", help="Sökväg till logotyp (PNG/SVG)")
+ gen_parser.add_argument("--output", "-o", help="Utdatafil")
+
+ # Run command (scan + generate)
+ run_parser = subparsers.add_parser("run", help="Analysera + generera rapport")
+ run_parser.add_argument("url", nargs="?", help="Webbplats-URL")
+ run_parser.add_argument("--samples", "-s", type=int, default=3, help="Antal samples per sida (default: 3)")
+ run_parser.add_argument("--customer", "-c", help="Kundnamn")
+ run_parser.add_argument("--consultant", help="Konsultnamn")
+ run_parser.add_argument("--logo", "-l", help="Sökväg till logotyp (PNG/SVG)")
+ run_parser.add_argument("--output", "-o", help="Utdatafil")
+
+ # Init command
+ subparsers.add_parser("init", help="Konfigurera projekt")
+
+ # Info command
+ subparsers.add_parser("info", help="Visa projektinformation")
+
+ args = parser.parse_args()
+ base_path = Path.cwd()
+
+ print(BANNER)
+
+ if args.command == "scan":
+ cmd_scan(args, base_path)
+ elif args.command == "generate":
+ cmd_generate(args, base_path)
+ elif args.command == "run":
+ cmd_run(args, base_path)
+ elif args.command == "init":
+ cmd_init(args, base_path)
+ elif args.command == "info":
+ cmd_info(args, base_path)
+ else:
+ # Default: show help
+ parser.print_help()
+ print("\n💡 Snabbstart:")
+ print(" python webbanalys.py run https://example.com -c 'Företag AB'")
+
+
+if __name__ == "__main__":
+ main()
+