Initial DevSecOps Pipeline Explorer Space

README.md

@@ -1,12 +1,25 @@
 ---
-title: Devsecops Pipeline Explorer
-emoji: 🦀
+title: DevSecOps Pipeline Explorer
+emoji: 🔒
 colorFrom: blue
 colorTo: green
 sdk: gradio
-sdk_version: 6.5.1
+sdk_version: "5.50.0"
 app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# DevSecOps Pipeline Explorer
+
+Explore 130 DevSecOps entries covering practices, SAST/DAST/SCA tools, pipeline templates, container security, secret management, and Q&A.
+
+**Features:**
+- Bilingual support (FR / EN)
+- 9 tabs: Practices, SAST, DAST, SCA, Pipelines, Container Security, Secret Management, Q&A, Statistics
+- Interactive filters for maturity level and CI platform
+- Plotly charts for statistics
+- YAML code blocks for pipeline templates
+
+**Datasets:**
+- [AYI-NEDJIMI/devsecops-pipeline-fr](https://huggingface.co/datasets/AYI-NEDJIMI/devsecops-pipeline-fr)
+- [AYI-NEDJIMI/devsecops-pipeline-en](https://huggingface.co/datasets/AYI-NEDJIMI/devsecops-pipeline-en)

app.py

@@ -0,0 +1,299 @@
+import gradio as gr
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+from datasets import load_dataset
+
+# ---------------------------------------------------------------------------
+# Data Loading
+# ---------------------------------------------------------------------------
+
+DATASETS = {
+    "FR": "AYI-NEDJIMI/devsecops-pipeline-fr",
+    "EN": "AYI-NEDJIMI/devsecops-pipeline-en",
+}
+
+_cache = {}
+
+
+def _load(lang: str) -> pd.DataFrame:
+    if lang not in _cache:
+        try:
+            ds = load_dataset(DATASETS[lang], split="train")
+            _cache[lang] = ds.to_pandas()
+        except Exception as e:
+            print(f"Error loading {lang} dataset: {e}")
+            _cache[lang] = pd.DataFrame()
+    return _cache[lang]
+
+
+def _safe(df: pd.DataFrame, col: str):
+    """Return column values if it exists, else empty Series."""
+    if col in df.columns:
+        return df[col].fillna("")
+    return pd.Series([""] * len(df), index=df.index)
+
+
+def _filter_type(lang, t):
+    df = _load(lang)
+    if "type" in df.columns:
+        return df[df["type"] == t].reset_index(drop=True)
+    return df
+
+
+# ---------------------------------------------------------------------------
+# Helper – build a display DataFrame with only the requested columns
+# ---------------------------------------------------------------------------
+
+def _display(df, cols):
+    present = [c for c in cols if c in df.columns]
+    out = df[present].copy() if present else pd.DataFrame()
+    return out
+
+
+# ---------------------------------------------------------------------------
+# Tab builders
+# ---------------------------------------------------------------------------
+
+def tab_practices(lang, maturity_filter):
+    df = _filter_type(lang, "practice")
+    if maturity_filter and maturity_filter != "All":
+        df = df[_safe(df, "maturity_level") == maturity_filter]
+    cols = ["practice_name", "description", "benefits", "tools", "metrics"]
+    return _display(df, cols)
+
+
+def tab_sast(lang):
+    df = _filter_type(lang, "sast_tool")
+    cols = ["name", "vendor", "supported_languages", "ci_integration", "strengths", "weaknesses"]
+    return _display(df, cols)
+
+
+def tab_dast(lang):
+    df = _filter_type(lang, "dast_tool")
+    cols = ["name", "vendor", "scan_types", "api_support", "strengths", "weaknesses"]
+    return _display(df, cols)
+
+
+def tab_sca(lang):
+    df = _filter_type(lang, "sca_tool")
+    cols = ["name", "vendor", "package_managers_supported", "vulnerability_db", "strengths", "weaknesses"]
+    return _display(df, cols)
+
+
+def tab_pipeline(lang, ci_filter):
+    df = _filter_type(lang, "pipeline_template")
+    if ci_filter and ci_filter != "All":
+        df = df[_safe(df, "ci_platform") == ci_filter]
+    cols = ["pipeline_name", "stages", "yaml_example", "security_gates"]
+    return _display(df, cols)
+
+
+def tab_container(lang):
+    df = _filter_type(lang, "container_security")
+    cols = ["category", "name", "implementation", "best_practices", "common_misconfigurations"]
+    return _display(df, cols)
+
+
+def tab_secret(lang):
+    df = _filter_type(lang, "secret_management")
+    cols = ["name", "vendor", "features", "integration", "strengths", "weaknesses"]
+    return _display(df, cols)
+
+
+def tab_qa(lang):
+    df = _filter_type(lang, "qa")
+    cols = ["question", "answer", "difficulty"]
+    return _display(df, cols)
+
+
+# ---------------------------------------------------------------------------
+# Pipeline detail – show yaml_example in code block
+# ---------------------------------------------------------------------------
+
+def pipeline_detail(lang, ci_filter):
+    df = _filter_type(lang, "pipeline_template")
+    if ci_filter and ci_filter != "All":
+        df = df[_safe(df, "ci_platform") == ci_filter]
+    parts = []
+    for _, row in df.iterrows():
+        name = row.get("pipeline_name", "N/A")
+        stages = row.get("stages", "N/A")
+        gates = row.get("security_gates", "N/A")
+        yaml_ex = row.get("yaml_example", "")
+        parts.append(f"### {name}\n\n**Stages:** {stages}\n\n**Security Gates:** {gates}\n\n```yaml\n{yaml_ex}\n```\n\n---\n")
+    return "\n".join(parts) if parts else "No pipeline templates found."
+
+
+# ---------------------------------------------------------------------------
+# Statistics charts
+# ---------------------------------------------------------------------------
+
+def stats_type_chart(lang):
+    df = _load(lang)
+    if "type" not in df.columns:
+        return go.Figure()
+    counts = df["type"].value_counts().reset_index()
+    counts.columns = ["type", "count"]
+    fig = px.bar(counts, x="type", y="count", title="Entries by Type",
+                 color="type", text_auto=True)
+    fig.update_layout(showlegend=False)
+    return fig
+
+
+def stats_ci_chart(lang):
+    df = _load(lang)
+    if "ci_platform" not in df.columns:
+        return go.Figure()
+    sub = df[df["ci_platform"].notna() & (df["ci_platform"] != "")]
+    if sub.empty:
+        return go.Figure()
+    counts = sub["ci_platform"].value_counts().reset_index()
+    counts.columns = ["ci_platform", "count"]
+    fig = px.pie(counts, names="ci_platform", values="count", title="Pipeline Templates by CI Platform")
+    return fig
+
+
+def stats_maturity_chart(lang):
+    df = _load(lang)
+    if "maturity_level" not in df.columns:
+        return go.Figure()
+    sub = df[df["maturity_level"].notna() & (df["maturity_level"] != "")]
+    if sub.empty:
+        return go.Figure()
+    counts = sub["maturity_level"].value_counts().reset_index()
+    counts.columns = ["maturity_level", "count"]
+    fig = px.bar(counts, x="maturity_level", y="count", title="Practices by Maturity Level",
+                 color="maturity_level", text_auto=True)
+    fig.update_layout(showlegend=False)
+    return fig
+
+
+# ---------------------------------------------------------------------------
+# Dynamic dropdown choices
+# ---------------------------------------------------------------------------
+
+def _maturity_choices(lang):
+    df = _filter_type(lang, "practice")
+    if "maturity_level" in df.columns:
+        vals = sorted(df["maturity_level"].dropna().unique().tolist())
+    else:
+        vals = []
+    return ["All"] + vals
+
+
+def _ci_choices(lang):
+    df = _filter_type(lang, "pipeline_template")
+    if "ci_platform" in df.columns:
+        vals = sorted(df["ci_platform"].dropna().unique().tolist())
+    else:
+        vals = []
+    return ["All"] + vals
+
+
+# ---------------------------------------------------------------------------
+# Footer HTML
+# ---------------------------------------------------------------------------
+
+FOOTER_HTML = """
+<div style="text-align:center; padding:20px; margin-top:30px; border-top:1px solid #444; font-size:0.9em; color:#aaa;">
+  <p><strong>DevSecOps Pipeline Explorer</strong> — Built by AYI-NEDJIMI Consultants</p>
+  <p>
+    <a href="https://ayinedjimi-consultants.fr" target="_blank" style="margin:0 8px;">🌐 ayinedjimi-consultants.fr</a> |
+    <a href="https://www.linkedin.com/company/ayi-nedjimi" target="_blank" style="margin:0 8px;">LinkedIn</a> |
+    <a href="https://github.com/AYI-NEDJIMI" target="_blank" style="margin:0 8px;">GitHub</a> |
+    <a href="https://x.com/AYI_NEDJIMI" target="_blank" style="margin:0 8px;">X / Twitter</a>
+  </p>
+</div>
+"""
+
+# ---------------------------------------------------------------------------
+# Gradio App
+# ---------------------------------------------------------------------------
+
+def build_app():
+    with gr.Blocks(
+        title="DevSecOps Pipeline Explorer",
+        theme=gr.themes.Soft(),
+    ) as demo:
+        gr.Markdown("# DevSecOps Pipeline Explorer\nExplore 130 DevSecOps practices, tools, pipeline templates, and more.")
+
+        lang = gr.Radio(["EN", "FR"], value="EN", label="Language / Langue", interactive=True)
+
+        with gr.Tabs():
+            # ---- 1. Practices ----
+            with gr.Tab("DevSecOps Practices"):
+                maturity_dd = gr.Dropdown(choices=_maturity_choices("EN"), value="All", label="Filter by Maturity Level")
+                practices_table = gr.Dataframe(value=tab_practices("EN", "All"), label="Practices", wrap=True)
+                btn_practices = gr.Button("Refresh")
+
+                def _refresh_practices(l, m):
+                    return tab_practices(l, m)
+
+                btn_practices.click(_refresh_practices, [lang, maturity_dd], practices_table)
+                lang.change(lambda l: gr.update(choices=_maturity_choices(l), value="All"), lang, maturity_dd)
+                lang.change(lambda l: tab_practices(l, "All"), lang, practices_table)
+                maturity_dd.change(_refresh_practices, [lang, maturity_dd], practices_table)
+
+            # ---- 2. SAST ----
+            with gr.Tab("SAST Tools"):
+                sast_table = gr.Dataframe(value=tab_sast("EN"), label="SAST Tools", wrap=True)
+                lang.change(lambda l: tab_sast(l), lang, sast_table)
+
+            # ---- 3. DAST ----
+            with gr.Tab("DAST Tools"):
+                dast_table = gr.Dataframe(value=tab_dast("EN"), label="DAST Tools", wrap=True)
+                lang.change(lambda l: tab_dast(l), lang, dast_table)
+
+            # ---- 4. SCA ----
+            with gr.Tab("SCA Tools"):
+                sca_table = gr.Dataframe(value=tab_sca("EN"), label="SCA Tools", wrap=True)
+                lang.change(lambda l: tab_sca(l), lang, sca_table)
+
+            # ---- 5. Pipeline Templates ----
+            with gr.Tab("Pipeline Templates"):
+                ci_dd = gr.Dropdown(choices=_ci_choices("EN"), value="All", label="Filter by CI Platform")
+                pipeline_table = gr.Dataframe(value=tab_pipeline("EN", "All"), label="Pipeline Templates", wrap=True)
+                pipeline_md = gr.Markdown(value=pipeline_detail("EN", "All"), label="YAML Details")
+                btn_pipeline = gr.Button("Refresh")
+
+                def _refresh_pipeline(l, c):
+                    return tab_pipeline(l, c), pipeline_detail(l, c)
+
+                btn_pipeline.click(_refresh_pipeline, [lang, ci_dd], [pipeline_table, pipeline_md])
+                lang.change(lambda l: gr.update(choices=_ci_choices(l), value="All"), lang, ci_dd)
+                lang.change(lambda l: (tab_pipeline(l, "All"), pipeline_detail(l, "All")), lang, [pipeline_table, pipeline_md])
+                ci_dd.change(lambda l, c: (tab_pipeline(l, c), pipeline_detail(l, c)), [lang, ci_dd], [pipeline_table, pipeline_md])
+
+            # ---- 6. Container Security ----
+            with gr.Tab("Container Security"):
+                container_table = gr.Dataframe(value=tab_container("EN"), label="Container Security", wrap=True)
+                lang.change(lambda l: tab_container(l), lang, container_table)
+
+            # ---- 7. Secret Management ----
+            with gr.Tab("Secret Management"):
+                secret_table = gr.Dataframe(value=tab_secret("EN"), label="Secret Management", wrap=True)
+                lang.change(lambda l: tab_secret(l), lang, secret_table)
+
+            # ---- 8. Q&A ----
+            with gr.Tab("Q&A"):
+                qa_table = gr.Dataframe(value=tab_qa("EN"), label="Q&A", wrap=True)
+                lang.change(lambda l: tab_qa(l), lang, qa_table)
+
+            # ---- 9. Statistics ----
+            with gr.Tab("Statistics"):
+                chart_type = gr.Plot(value=stats_type_chart("EN"), label="By Type")
+                chart_ci = gr.Plot(value=stats_ci_chart("EN"), label="By CI Platform")
+                chart_maturity = gr.Plot(value=stats_maturity_chart("EN"), label="By Maturity Level")
+                lang.change(lambda l: stats_type_chart(l), lang, chart_type)
+                lang.change(lambda l: stats_ci_chart(l), lang, chart_ci)
+                lang.change(lambda l: stats_maturity_chart(l), lang, chart_maturity)
+
+        gr.HTML(FOOTER_HTML)
+
+    return demo
+
+
+if __name__ == "__main__":
+    demo = build_app()
+    demo.launch()

requirements.txt

@@ -0,0 +1,4 @@
+gradio==5.50.0
+plotly
+pandas
+datasets