Transport protocols

df_overall = load_parquet("transport_overall", target_date)

df_overall["label"] = df_overall.apply(
    lambda r: f"{'QUIC' if r['transport'] == 'udp' else 'TCP'} ({r['percentage']:.1f}%)",
    axis=1
)

fig = px.pie(
    df_overall,
    values="connections",
    names="label",
    color="transport",
    color_discrete_map={"tcp": "#3b82f6", "udp": "#22c55e"},
    hole=0.4,
)
fig.update_layout(
    title="Transport protocol distribution (7-day rolling)",
    height=400,
    showlegend=True,
    legend=dict(orientation="h", yanchor="bottom", y=-0.15, xanchor="center", x=0.5),
)
fig.show()

df_daily = load_parquet("transport_daily", target_date)

df_daily["transport_label"] = df_daily["transport"].map({"tcp": "TCP", "udp": "QUIC"})

fig = px.bar(
    df_daily,
    x="date",
    y="connections",
    color="transport_label",
    color_discrete_map={"TCP": "#3b82f6", "QUIC": "#22c55e"},
    barmode="stack",
    labels={"date": "Date", "connections": "Connections", "transport_label": "Transport"},
)
fig.update_layout(
    title="Daily connections by transport protocol",
    height=400,
    legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
)
fig.show()

df_peer_breakdown = load_parquet("transport_peers", target_date)

peer_data = [
    {"category": "TCP only", "peers": int(df_peer_breakdown["tcp_only"].iloc[0])},
    {"category": "QUIC only", "peers": int(df_peer_breakdown["quic_only"].iloc[0])},
    {"category": "Both", "peers": int(df_peer_breakdown["both"].iloc[0])},
]
df_peers = pd.DataFrame(peer_data)
df_peers["percentage"] = (df_peers["peers"] / df_peers["peers"].sum() * 100).round(1)

fig = px.bar(
    df_peers,
    x="category",
    y="peers",
    color="category",
    color_discrete_map={"TCP only": "#3b82f6", "QUIC only": "#22c55e", "Both": "#a855f7"},
    text=df_peers.apply(lambda r: f"{r['peers']:,} ({r['percentage']}%)", axis=1),
)
fig.update_traces(textposition="outside")
fig.update_layout(
    title="Unique peers by transport capability (7-day rolling)",
    height=400,
    showlegend=False,
    xaxis_title="",
    yaxis_title="Unique peers",
)
fig.show()

df_clients = load_parquet("transport_by_client", target_date)

df_clients

df_clients_long = df_clients.melt(
    id_vars=["client", "total"],
    value_vars=["tcp_only", "quic_only", "both"],
    var_name="protocol_type",
    value_name="peers",
)
df_clients_long["protocol_label"] = df_clients_long["protocol_type"].map({
    "tcp_only": "TCP only",
    "quic_only": "QUIC only",
    "both": "Both",
})

client_order = df_clients.sort_values("total", ascending=True)["client"].tolist()

fig = px.bar(
    df_clients_long,
    x="peers",
    y="client",
    color="protocol_label",
    color_discrete_map={"TCP only": "#3b82f6", "QUIC only": "#22c55e", "Both": "#a855f7"},
    orientation="h",
    category_orders={"client": client_order},
    labels={"peers": "Unique peers", "client": "Client", "protocol_label": "Transport"},
)
fig.update_layout(
    title="Transport protocol support by client (7-day rolling)",
    height=500,
    legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
    barmode="stack",
)
fig.show()

df_quic_pct = df_clients.sort_values("quic_capable_pct", ascending=True).copy()

fig = px.bar(
    df_quic_pct,
    x="quic_capable_pct",
    y="client",
    orientation="h",
    text=df_quic_pct["quic_capable_pct"].apply(lambda x: f"{x:.1f}%"),
    color="quic_capable_pct",
    color_continuous_scale="Greens",
)
fig.update_traces(textposition="outside")
fig.update_layout(
    title="QUIC-capable peers by client (7-day rolling)",
    height=500,
    showlegend=False,
    xaxis_title="% of peers supporting QUIC",
    yaxis_title="",
    coloraxis_showscale=False,
)
fig.update_xaxes(range=[0, 100])
fig.show()

df_conn_patterns = load_parquet("transport_connection_patterns", target_date)

df_conn_patterns["transport_label"] = df_conn_patterns["transport"].map({"tcp": "TCP", "udp": "QUIC"})

fig = make_subplots(
    rows=1, cols=2,
    subplot_titles=("Unique peers", "Connections per peer"),
)

colors = {"TCP": "#3b82f6", "QUIC": "#22c55e"}

fig.add_trace(
    go.Bar(
        x=df_conn_patterns["transport_label"],
        y=df_conn_patterns["unique_peers"],
        marker_color=[colors[t] for t in df_conn_patterns["transport_label"]],
        text=df_conn_patterns["unique_peers"].apply(lambda x: f"{x:,}"),
        textposition="outside",
        showlegend=False,
    ),
    row=1, col=1,
)

fig.add_trace(
    go.Bar(
        x=df_conn_patterns["transport_label"],
        y=df_conn_patterns["connections_per_peer"],
        marker_color=[colors[t] for t in df_conn_patterns["transport_label"]],
        text=df_conn_patterns["connections_per_peer"].apply(lambda x: f"{x:.1f}"),
        textposition="outside",
        showlegend=False,
    ),
    row=1, col=2,
)

fig.update_layout(
    title="Connection patterns by transport (7-day rolling)",
    height=400,
)
fig.show()

df_daily_pivot = df_daily.pivot(index="date", columns="transport_label", values="unique_peers").reset_index()
df_daily_pivot["QUIC %"] = (df_daily_pivot["QUIC"] / (df_daily_pivot["TCP"] + df_daily_pivot["QUIC"]) * 100).round(1)

fig = make_subplots(
    rows=2, cols=1,
    subplot_titles=("Unique peers by transport", "QUIC share of unique peers"),
    row_heights=[0.6, 0.4],
    vertical_spacing=0.12,
)

fig.add_trace(
    go.Scatter(
        x=df_daily_pivot["date"],
        y=df_daily_pivot["TCP"],
        name="TCP",
        mode="lines+markers",
        line=dict(color="#3b82f6"),
    ),
    row=1, col=1,
)
fig.add_trace(
    go.Scatter(
        x=df_daily_pivot["date"],
        y=df_daily_pivot["QUIC"],
        name="QUIC",
        mode="lines+markers",
        line=dict(color="#22c55e"),
    ),
    row=1, col=1,
)

fig.add_trace(
    go.Scatter(
        x=df_daily_pivot["date"],
        y=df_daily_pivot["QUIC %"],
        name="QUIC %",
        mode="lines+markers",
        line=dict(color="#22c55e"),
        fill="tozeroy",
        fillcolor="rgba(34, 197, 94, 0.2)",
        showlegend=False,
    ),
    row=2, col=1,
)

fig.update_yaxes(title_text="Unique peers", row=1, col=1)
fig.update_yaxes(title_text="QUIC %", range=[0, 20], row=2, col=1)
fig.update_xaxes(title_text="Date", row=2, col=1)

fig.update_layout(
    title="Daily unique peer trends",
    height=600,
    legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1),
)
fig.show()

from IPython.display import HTML, display

tcp_pct = df_overall[df_overall["transport"] == "tcp"]["percentage"].iloc[0]
quic_pct = df_overall[df_overall["transport"] == "udp"]["percentage"].iloc[0]

tcp_only_peers = int(df_peer_breakdown["tcp_only"].iloc[0])
quic_only_peers = int(df_peer_breakdown["quic_only"].iloc[0])
both_peers = int(df_peer_breakdown["both"].iloc[0])
total_peers = int(df_peer_breakdown["total"].iloc[0])

quic_clients = df_clients[df_clients["quic_capable_pct"] > 10]["client"].tolist()
no_quic_clients = df_clients[df_clients["quic_capable_pct"] < 1]["client"].tolist()

html = f'''
<style>
.summary-table {{ border-collapse: collapse; font-family: system-ui; width: 100%; }}
.summary-table th {{ background: #1e293b; color: white; padding: 12px; text-align: left; }}
.summary-table td {{ padding: 10px; border-bottom: 1px solid #e2e8f0; }}
.summary-table tr:hover {{ background: #f8fafc; }}
.metric {{ font-size: 1.5em; font-weight: bold; }}
.tcp {{ color: #3b82f6; }}
.quic {{ color: #22c55e; }}
</style>
<table class="summary-table">
<tr><th colspan="2">Connection distribution</th></tr>
<tr><td>TCP connections</td><td class="metric tcp">{tcp_pct:.1f}%</td></tr>
<tr><td>QUIC connections</td><td class="metric quic">{quic_pct:.1f}%</td></tr>
<tr><th colspan="2">Unique peer breakdown</th></tr>
<tr><td>TCP-only peers</td><td>{tcp_only_peers:,} ({tcp_only_peers/total_peers*100:.1f}%)</td></tr>
<tr><td>QUIC-only peers</td><td>{quic_only_peers:,} ({quic_only_peers/total_peers*100:.1f}%)</td></tr>
<tr><td>Dual-protocol peers</td><td>{both_peers:,} ({both_peers/total_peers*100:.1f}%)</td></tr>
<tr><td>Total unique peers</td><td><b>{total_peers:,}</b></td></tr>
<tr><th colspan="2">Client QUIC support</th></tr>
<tr><td>Significant QUIC support (&gt;10%)</td><td>{", ".join(quic_clients) or "None"}</td></tr>
<tr><td>No QUIC support (&lt;1%)</td><td>{", ".join(no_quic_clients) or "None"}</td></tr>
</table>
'''

display(HTML(html))