backend overhaul

charts.py

@@ -0,0 +1,149 @@
+#!/usr/bin/env python3
+"""Chart data series builders for the frontend."""
+from __future__ import annotations
+
+from typing import Any
+
+from models import SessionEntry, SessionSummary
+from utils import net_result_bucket, session_chart_label, session_sort_key
+
+PLAYER_PALETTE = [
+    "#9b8cf0",  # --line-1 violet
+    "#6fc093",  # --line-2 green
+    "#e0b15c",  # --line-3 gold
+    "#cf6f86",  # --line-4 pink
+    "#8f93c2",  # --line-5 lavender
+    "#7cb9e0",
+    "#f4a261",
+    "#a78bb0",
+    "#5cb8a0",
+    "#e58f3a",
+    "#84cc16",
+    "#06b6d4",
+]
+
+
+def color_for_name(name: str, names: list[str]) -> str:
+    try:
+        index = sorted(names, key=str.casefold).index(name)
+    except ValueError:
+        index = abs(hash(name))
+    return PLAYER_PALETTE[index % len(PLAYER_PALETTE)]
+
+
+def net_tone(value_cents: int) -> str:
+    bucket = net_result_bucket(value_cents)
+
+    if bucket == "win":
+        return "#6fc093"  # --pos
+    if bucket == "loss":
+        return "#e0758a"  # --neg
+    return "#84828e"      # --muted-2
+
+
+def cumulative_profit_series(sessions: list[SessionSummary]) -> dict[str, object]:
+    ordered_sessions = sorted(sessions, key=session_sort_key)
+
+    all_players = sorted(
+        {
+            entry.player_name
+            for session in ordered_sessions
+            for entry in session.entries
+        },
+        key=str.casefold,
+    )
+
+    labels = [session_chart_label(session) for session in ordered_sessions]
+    datasets = []
+
+    for player_name in all_players:
+        running_total = 0
+        seen_player = False
+        sessions_played = 0
+        data: list[float | None] = []
+
+        for session in ordered_sessions:
+            matching_entry = next(
+                (
+                    entry
+                    for entry in session.entries
+                    if entry.player_name == player_name
+                ),
+                None,
+            )
+
+            if matching_entry is None:
+                data.append(running_total / 100 if seen_player else None)
+                continue
+
+            seen_player = True
+            sessions_played += 1
+            running_total += matching_entry.net_cents
+            data.append(round(running_total / 100, 2))
+
+        datasets.append(
+            {
+                "label": player_name,
+                "data": data,
+                "sessions_played": sessions_played,
+            }
+        )
+
+    return {
+        "labels": labels,
+        "datasets": datasets,
+    }
+
+
+def player_session_series(
+    sessions: list[SessionSummary], player_name: str
+) -> dict[str, Any]:
+    ordered_sessions = sorted(sessions, key=session_sort_key)
+    labels: list[str] = []
+    net_values: list[float] = []
+    cumulative_values: list[float] = []
+    running_total = 0
+
+    all_player_names = sorted(
+        {
+            entry.player_name
+            for session in ordered_sessions
+            for entry in session.entries
+        },
+        key=str.casefold,
+    )
+
+    for session in ordered_sessions:
+        matching_entry = next(
+            (entry for entry in session.entries if entry.player_name == player_name),
+            None,
+        )
+        if matching_entry is None:
+            continue
+
+        labels.append(session_chart_label(session))
+        net_values.append(round(matching_entry.net_cents / 100, 2))
+        running_total += matching_entry.net_cents
+        cumulative_values.append(round(running_total / 100, 2))
+
+    return {
+        "labels": labels,
+        "color": color_for_name(player_name, all_player_names),
+        "net_values": net_values,
+        "net_colors": [net_tone(round(value * 100)) for value in net_values],
+        "cumulative_values": cumulative_values,
+    }
+
+
+def session_breakdown_series(session: SessionSummary) -> dict[str, Any]:
+    ordered_entries = sorted(
+        session.entries,
+        key=lambda entry: (entry.net_cents, entry.player_name.casefold()),
+        reverse=True,
+    )
+
+    return {
+        "labels": [entry.player_name for entry in ordered_entries],
+        "net_values": [round(entry.net_cents / 100, 2) for entry in ordered_entries],
+        "net_colors": [net_tone(entry.net_cents) for entry in ordered_entries],
+    }