Rewrite as uv-based Flask web app with Dockerfile

- Flask dashboard with Plotly charts (stores, monthly, hourly, weekday, heatmap)
- Spotify Wrapped-style summary with year dropdown and inflation toggle
- CSV upload flow (ephemeral, no storage)
- Homepage with upload and saved data options
- Import script for loading CSVs into SQLite
- Dockerized with gunicorn for production

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

.dockerignore

@@ -0,0 +1,11 @@
+.git
+.venv
+env
+venv
+__pycache__
+*.pyc
+.DS_Store
+images
+*.db
+*.csv
+*.db.bak

.gitignore

@@ -0,0 +1,9 @@
+# who the fuck forgets to add this smh
+
+env/
+venv/
+.venv/
+__pycache__/
+*.pyc
+.DS_Store
+*.db.bak

.python-version

@@ -0,0 +1 @@
+3.14

Dockerfile

@@ -0,0 +1,14 @@
+FROM python:3.14-slim
+
+COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
+
+WORKDIR /app
+
+COPY pyproject.toml uv.lock ./
+RUN uv sync --frozen --no-dev
+
+COPY app.py import_csv.py ./
+
+EXPOSE 8000
+
+CMD ["uv", "run", "gunicorn", "app:app", "--bind", "0.0.0.0:8000", "--workers", "2", "--timeout", "120"]

README.md

@@ -2,4 +2,10 @@
 
 Visualizing Akshay's moments of weakness.
 
+A tool to visualize your Doordash spending habits. To get the CSV required to use this repository, go to your Doordash settings and request your data. In around a day you will get an email with the CSV of your data. Use that with the tool and enjoy your horror.
+
+## Testimonials
+
+> That's not a moment of weakness. That's a life of weakness. - Noah
+
 ![[images/weaknessByDayWeek.png]]

app.py

@@ -0,0 +1,591 @@
+import os
+import sqlite3
+import json
+from datetime import datetime
+from collections import defaultdict
+import csv
+import io
+from flask import Flask, render_template_string, request, redirect, url_for, flash
+
+DB_PATH = os.environ.get("WEAKNESS_DB_PATH", "doordash.db")
+
+# CPI-U annual average multipliers to 2026 dollars
+CPI_TO_2026 = {
+    "2019": 1.28, "2020": 1.25, "2021": 1.18, "2022": 1.10,
+    "2023": 1.06, "2024": 1.03, "2025": 1.01, "2026": 1.00,
+}
+
+app = Flask(__name__)
+app.secret_key = os.environ.get("SECRET_KEY", os.urandom(32))
+app.config["MAX_CONTENT_LENGTH"] = 16 * 1024 * 1024  # 16MB max upload
+
+EXPECTED_HEADER = [
+    "ITEM", "CATEGORY", "STORE_NAME", "UNIT_PRICE", "QUANTITY",
+    "SUBTOTAL", "CREATED_AT", "DELIVERY_TIME", "DELIVERY_ADDRESS",
+]
+
+
+def compute_wrapped(subset_rows, inflation_adjust=False):
+    if not subset_rows:
+        return None
+    ss = defaultdict(float)
+    hc = defaultdict(int)
+    wc = defaultdict(int)
+    ms = defaultdict(float)
+    ic = defaultdict(int)
+    orders = set()
+    t_spent = 0.0
+    for r in subset_rows:
+        sub = float(r["SUBTOTAL"])
+        if inflation_adjust:
+            try:
+                yr = str(datetime.fromisoformat(r["CREATED_AT"]).year)
+            except (ValueError, TypeError):
+                yr = "2026"
+            sub *= CPI_TO_2026.get(yr, 1.0)
+        t_spent += sub
+        ss[r["STORE_NAME"]] += sub
+        ic[r["ITEM"]] += 1
+        try:
+            dt = datetime.fromisoformat(r["CREATED_AT"])
+        except (ValueError, TypeError):
+            continue
+        orders.add(r["CREATED_AT"])
+        hc[dt.hour] += 1
+        wc[dt.strftime("%A")] += 1
+        ms[dt.strftime("%Y-%m")] += sub
+
+    fs = max(ss.items(), key=lambda x: x[1])
+    ph = max(hc.items(), key=lambda x: x[1])
+    pd = max(wc.items(), key=lambda x: x[1])
+    bm = max(ms.items(), key=lambda x: x[1])
+    fi = max(ic.items(), key=lambda x: x[1])
+    avg = round(t_spent / len(orders), 2) if orders else 0
+    return {
+        "fav_store_name": fs[0],
+        "fav_store_total": f"${fs[1]:,.2f}",
+        "fav_store_pct": round(fs[1] / t_spent * 100, 1) if t_spent else 0,
+        "peak_hour_label": f"{ph[0]}:00",
+        "peak_hour_count": ph[1],
+        "peak_day_name": pd[0],
+        "biggest_month_label": datetime.strptime(bm[0], "%Y-%m").strftime("%B %Y"),
+        "biggest_month_total": f"${bm[1]:,.2f}",
+        "avg_per_order": f"${avg:,.2f}",
+        "fav_item_name": fi[0],
+        "fav_item_count": fi[1],
+        "total_spent": f"${t_spent:,.2f}",
+        "total_items": len(subset_rows),
+        "total_orders": len(orders),
+    }
+
+
+def render_dashboard(rows):
+    import numpy as np
+
+    total_spent = sum(float(r["SUBTOTAL"]) for r in rows)
+    total_orders_set = set()
+    store_spend = defaultdict(float)
+    month_spend = defaultdict(float)
+    hour_counts = defaultdict(int)
+    weekday_counts = defaultdict(int)
+    week_grid = [[0] * 7 for _ in range(53)]
+
+    for r in rows:
+        store_spend[r["STORE_NAME"]] += float(r["SUBTOTAL"])
+        try:
+            dt = datetime.fromisoformat(r["CREATED_AT"])
+        except (ValueError, TypeError):
+            continue
+        total_orders_set.add(r["CREATED_AT"])
+        month_key = dt.strftime("%Y-%m")
+        month_spend[month_key] += float(r["SUBTOTAL"])
+        hour_counts[dt.hour] += 1
+        weekday_counts[dt.strftime("%A")] += 1
+        week = min(dt.isocalendar().week - 1, 52)
+        day = dt.isocalendar().weekday - 1
+        week_grid[week][day] += float(r["SUBTOTAL"])
+
+    year_data = defaultdict(list)
+    for r in rows:
+        try:
+            dt = datetime.fromisoformat(r["CREATED_AT"])
+            year_data[str(dt.year)].append(r)
+        except (ValueError, TypeError):
+            pass
+
+    wrapped_by_year = {"All Time": compute_wrapped(rows)}
+    wrapped_by_year_adj = {"All Time": compute_wrapped(rows, inflation_adjust=True)}
+    for year in sorted(year_data.keys()):
+        wrapped_by_year[year] = compute_wrapped(year_data[year])
+        wrapped_by_year_adj[year] = compute_wrapped(year_data[year], inflation_adjust=True)
+
+    top_stores = sorted(store_spend.items(), key=lambda x: x[1], reverse=True)[:15]
+    store_names = [s[0] for s in top_stores]
+    store_totals = [round(s[1], 2) for s in top_stores]
+
+    sorted_months = sorted(month_spend.keys())
+    month_totals = [round(month_spend[m], 2) for m in sorted_months]
+
+    hour_labels = list(range(24))
+    hour_values = [hour_counts.get(h, 0) for h in hour_labels]
+    hour_labels_str = [f"{h}:00" for h in hour_labels]
+
+    day_order = ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday"]
+    weekday_values = [weekday_counts.get(d, 0) for d in day_order]
+
+    grid = np.array(week_grid)
+    heatmap_data = np.rot90(grid).tolist()
+    heatmap_days = ["Sun", "Sat", "Fri", "Thu", "Wed", "Tue", "Mon"]
+
+    return render_template_string(
+        TEMPLATE,
+        total_spent=f"${total_spent:,.2f}",
+        total_items=len(rows),
+        total_orders=len(total_orders_set),
+        store_names=json.dumps(store_names),
+        store_totals=json.dumps(store_totals),
+        month_labels=json.dumps(sorted_months),
+        month_totals=json.dumps(month_totals),
+        hour_labels=json.dumps(hour_labels_str),
+        hour_values=json.dumps(hour_values),
+        day_order=json.dumps(day_order),
+        weekday_values=json.dumps(weekday_values),
+        heatmap_data=json.dumps(heatmap_data),
+        heatmap_days=json.dumps(heatmap_days),
+        wrapped_data=json.dumps(wrapped_by_year),
+        wrapped_data_adj=json.dumps(wrapped_by_year_adj),
+    )
+
+
+def parse_csv_to_rows(text):
+    reader = csv.reader(io.StringIO(text))
+    header = [h.strip().upper() for h in next(reader)]
+    if header != EXPECTED_HEADER:
+        return None, "Invalid CSV header"
+    rows = []
+    for row in reader:
+        if len(row) != 9:
+            continue
+        rows.append({
+            "ITEM": row[0], "CATEGORY": row[1], "STORE_NAME": row[2],
+            "UNIT_PRICE": row[3], "QUANTITY": row[4], "SUBTOTAL": row[5],
+            "CREATED_AT": row[6], "DELIVERY_TIME": row[7], "DELIVERY_ADDRESS": row[8],
+        })
+    return rows, None
+
+
+@app.route("/")
+def home():
+    return render_template_string(HOME_TEMPLATE)
+
+
+@app.route("/dashboard")
+def dashboard():
+    conn = sqlite3.connect(DB_PATH)
+    conn.row_factory = sqlite3.Row
+    rows = conn.execute(
+        "SELECT ITEM, STORE_NAME, UNIT_PRICE, QUANTITY, SUBTOTAL, CREATED_AT FROM doordash"
+    ).fetchall()
+    conn.close()
+    return render_dashboard(rows)
+
+
+@app.route("/upload", methods=["GET", "POST"])
+def upload():
+    if request.method == "POST":
+        file = request.files.get("csv_file")
+        if not file or not file.filename.endswith(".csv"):
+            flash("Please upload a .csv file", "error")
+            return redirect(url_for("home"))
+
+        text = file.stream.read().decode("utf-8")
+        rows, err = parse_csv_to_rows(text)
+        if err:
+            flash(err, "error")
+            return redirect(url_for("home"))
+
+        return render_dashboard(rows)
+
+    return redirect(url_for("home"))
+
+
+HOME_TEMPLATE = """<!DOCTYPE html>
+<html>
+<head>
+    <title>Moments of Weakness</title>
+    <link href="https://fonts.googleapis.com/css2?family=Nunito:wght@400;700;800&display=swap" rel="stylesheet">
+    <style>
+        * { margin: 0; padding: 0; box-sizing: border-box; }
+        body {
+            font-family: 'Nunito', sans-serif;
+            background: #f9f3e3;
+            color: #5c4a32;
+            min-height: 100vh;
+            display: flex; justify-content: center; align-items: center;
+            background-image:
+                radial-gradient(circle at 20% 80%, #e8f5e9 0%, transparent 40%),
+                radial-gradient(circle at 80% 20%, #fff8e1 0%, transparent 40%);
+        }
+        .home {
+            text-align: center;
+            max-width: 560px; width: 100%;
+            padding: 24px;
+        }
+        h1 { font-size: 42px; color: #3e7c17; font-weight: 800; margin-bottom: 8px; }
+        .tagline { color: #8b7355; font-size: 16px; margin-bottom: 40px; }
+        .flash { padding: 10px 16px; border-radius: 8px; margin-bottom: 16px; font-size: 14px; font-weight: 700; }
+        .flash.error { background: #fde8e8; color: #c0392b; border: 1px solid #e6b0aa; }
+        .cards { display: flex; flex-direction: column; gap: 16px; }
+        .card {
+            background: #fffef5;
+            border: 3px solid #c4a96a;
+            border-radius: 20px;
+            padding: 32px;
+            box-shadow: 2px 3px 0 #c4a96a;
+            transition: transform 0.15s, box-shadow 0.15s;
+        }
+        .card:hover { transform: translateY(-2px); box-shadow: 2px 5px 0 #c4a96a; }
+        .card h2 { font-size: 20px; color: #3e7c17; margin-bottom: 6px; }
+        .card p { font-size: 14px; color: #8b7355; margin-bottom: 16px; }
+
+        .drop-zone {
+            border: 3px dashed #c4a96a;
+            border-radius: 14px;
+            padding: 32px 20px;
+            cursor: pointer;
+            transition: background 0.2s;
+            margin-bottom: 16px;
+        }
+        .drop-zone:hover, .drop-zone.dragover { background: #f5eed8; }
+        .drop-zone .icon { font-size: 36px; margin-bottom: 6px; }
+        .drop-zone .label { font-size: 14px; font-weight: 700; color: #5c4a32; }
+        .drop-zone .sublabel { font-size: 12px; color: #8b7355; margin-top: 4px; }
+        .file-name { font-size: 13px; color: #3e7c17; font-weight: 700; margin-bottom: 12px; display: none; }
+
+        .btn {
+            font-family: 'Nunito', sans-serif;
+            font-size: 15px; font-weight: 800;
+            border: none; border-radius: 12px;
+            padding: 12px 32px;
+            cursor: pointer; transition: background 0.2s;
+            text-decoration: none; display: inline-block;
+        }
+        .btn-primary { background: #3e7c17; color: #fff; }
+        .btn-primary:hover { background: #2d6b1e; }
+        .btn-primary:disabled { background: #aaa; cursor: not-allowed; }
+        .btn-outline { background: transparent; color: #3e7c17; border: 2px solid #3e7c17; }
+        .btn-outline:hover { background: #3e7c17; color: #fff; }
+        .or-divider { color: #c4a96a; font-size: 13px; font-weight: 700; margin: 8px 0; }
+    </style>
+</head>
+<body>
+    <div class="home">
+        <h1>Moments of Weakness</h1>
+        <p class="tagline">See exactly how much you've been spending on delivery</p>
+
+        {% with messages = get_flashed_messages(with_categories=true) %}
+        {% for cat, msg in messages %}
+        <div class="flash {{ cat }}">{{ msg }}</div>
+        {% endfor %}
+        {% endwith %}
+
+        <div class="cards">
+            <div class="card">
+                <h2>Upload Your Data</h2>
+                <p>Drop your DoorDash CSV export to see your dashboard. Nothing is stored.</p>
+                <form method="POST" action="/upload" enctype="multipart/form-data" id="upload-form">
+                    <div class="drop-zone" id="drop-zone">
+                        <div class="icon">&#128196;</div>
+                        <div class="label">Click or drag a CSV file here</div>
+                        <div class="sublabel">consumer_order_details.csv from DoorDash</div>
+                    </div>
+                    <input type="file" name="csv_file" id="csv-input" accept=".csv" hidden>
+                    <div class="file-name" id="file-name"></div>
+                    <button type="submit" class="btn btn-primary" id="submit-btn" disabled>View Dashboard</button>
+                </form>
+            </div>
+
+            <div class="or-divider">or</div>
+
+            <div class="card">
+                <h2>View Saved Data</h2>
+                <p>Browse the dashboard with previously imported order history.</p>
+                <a href="/dashboard" class="btn btn-outline">Open Dashboard</a>
+            </div>
+        </div>
+    </div>
+
+    <script>
+        const dropZone = document.getElementById('drop-zone');
+        const input = document.getElementById('csv-input');
+        const fileName = document.getElementById('file-name');
+        const submitBtn = document.getElementById('submit-btn');
+
+        dropZone.addEventListener('click', () => input.click());
+        dropZone.addEventListener('dragover', e => { e.preventDefault(); dropZone.classList.add('dragover'); });
+        dropZone.addEventListener('dragleave', () => dropZone.classList.remove('dragover'));
+        dropZone.addEventListener('drop', e => {
+            e.preventDefault(); dropZone.classList.remove('dragover');
+            if (e.dataTransfer.files.length) { input.files = e.dataTransfer.files; showFile(); }
+        });
+        input.addEventListener('change', showFile);
+
+        function showFile() {
+            if (input.files.length) {
+                fileName.textContent = input.files[0].name;
+                fileName.style.display = 'block';
+                submitBtn.disabled = false;
+            }
+        }
+    </script>
+</body>
+</html>
+"""
+
+TEMPLATE = """<!DOCTYPE html>
+<html>
+<head>
+    <title>Weakness Dashboard</title>
+    <script src="https://cdn.plot.ly/plotly-2.35.2.min.js"></script>
+    <link href="https://fonts.googleapis.com/css2?family=Nunito:wght@400;700;800&display=swap" rel="stylesheet">
+    <style>
+        * { margin: 0; padding: 0; box-sizing: border-box; }
+        body {
+            font-family: 'Nunito', sans-serif;
+            background: #f9f3e3;
+            color: #5c4a32;
+            padding: 24px;
+            background-image:
+                radial-gradient(circle at 20% 80%, #e8f5e9 0%, transparent 40%),
+                radial-gradient(circle at 80% 20%, #fff8e1 0%, transparent 40%);
+        }
+        h1 { font-size: 32px; margin-bottom: 4px; color: #3e7c17; font-weight: 800; }
+        .subtitle { color: #8b7355; margin-bottom: 24px; font-size: 14px; }
+        .stats { display: flex; gap: 16px; margin-bottom: 24px; }
+        .stat {
+            background: #fffef5;
+            border: 3px solid #c4a96a;
+            border-radius: 16px;
+            padding: 16px 24px;
+            flex: 1;
+            box-shadow: 2px 3px 0 #c4a96a;
+        }
+        .stat .value { font-size: 28px; font-weight: 800; color: #d4652a; }
+        .stat .label { color: #8b7355; font-size: 13px; margin-top: 4px; font-weight: 700; }
+        .wrapped {
+            background: linear-gradient(135deg, #d4652a, #e88b6a, #f4c842);
+            border-radius: 20px;
+            padding: 32px;
+            margin-bottom: 24px;
+            color: #fff;
+            display: grid;
+            grid-template-columns: 1fr 1fr;
+            gap: 20px;
+        }
+        .wrapped {
+            display: flex; flex-direction: column; gap: 12px;
+        }
+        .wrapped-header {
+            display: flex; justify-content: space-between; align-items: center;
+        }
+        .wrapped h2 { font-size: 24px; font-weight: 800; margin-bottom: 2px; }
+        .wrapped .tagline { font-size: 14px; opacity: 0.85; }
+        #year-select {
+            font-family: 'Nunito', sans-serif; font-size: 15px; font-weight: 700;
+            background: rgba(255,255,255,0.2); color: #fff; border: 2px solid rgba(255,255,255,0.4);
+            border-radius: 10px; padding: 8px 14px; cursor: pointer; appearance: auto;
+        }
+        #year-select option { color: #333; background: #fff; }
+        #wrapped-cards {
+            display: flex; flex-direction: column; gap: 12px;
+        }
+        .wrap-card {
+            background: rgba(255,255,255,0.15);
+            backdrop-filter: blur(4px);
+            border-radius: 14px;
+            padding: 20px;
+        }
+        .wrap-card .big { font-size: 22px; font-weight: 800; line-height: 1.2; }
+        .wrap-card .note { font-size: 13px; opacity: 0.85; margin-top: 6px; }
+        .grid { display: grid; grid-template-columns: 1fr 1fr; gap: 16px; margin-bottom: 16px; }
+        .chart-card {
+            background: #fffef5;
+            border: 3px solid #c4a96a;
+            border-radius: 16px;
+            padding: 16px;
+            min-height: 400px;
+            box-shadow: 2px 3px 0 #c4a96a;
+        }
+        .full-width { grid-column: 1 / -1; }
+    </style>
+</head>
+<body>
+    <div style="display:flex; justify-content:space-between; align-items:center; margin-bottom:4px;">
+        <h1>Moments of Weakness</h1>
+        <a href="/" style="font-size:14px; font-weight:700; color:#3e7c17; text-decoration:none; background:#fffef5; border:2px solid #c4a96a; border-radius:10px; padding:8px 16px;">Home</a>
+    </div>
+    <p class="subtitle">DoorDash spending dashboard</p>
+    {% with messages = get_flashed_messages(with_categories=true) %}
+    {% for cat, msg in messages %}
+    <div style="padding:10px 16px; border-radius:8px; margin-bottom:16px; font-size:14px; font-weight:700;
+        {% if cat == 'success' %}background:#e8f5e9; color:#27ae60; border:1px solid #a9dfbf;
+        {% else %}background:#fde8e8; color:#c0392b; border:1px solid #e6b0aa;{% endif %}">{{ msg }}</div>
+    {% endfor %}
+    {% endwith %}
+
+    <div class="stats">
+        <div class="stat">
+            <div class="value">{{ total_spent }}</div>
+            <div class="label">Total Spent</div>
+        </div>
+        <div class="stat">
+            <div class="value">{{ total_items }}</div>
+            <div class="label">Items Ordered</div>
+        </div>
+        <div class="stat">
+            <div class="value">{{ total_orders }}</div>
+            <div class="label">Unique Orders</div>
+        </div>
+    </div>
+
+    <div class="wrapped">
+        <div class="wrapped-header">
+            <div>
+                <h2>Your Weakness Wrapped</h2>
+                <p class="tagline">A look at your most questionable financial decisions</p>
+            </div>
+            <div style="display:flex; align-items:center; gap:16px;">
+                <label style="display:flex; align-items:center; gap:6px; font-size:13px; font-weight:700; cursor:pointer;">
+                    <input type="checkbox" id="inflation-toggle"> Inflation adjusted (2026 $)
+                </label>
+                <select id="year-select"></select>
+            </div>
+        </div>
+        <div id="wrapped-cards"></div>
+    </div>
+
+    <div class="grid">
+        <div class="chart-card">
+            <div id="stores"></div>
+        </div>
+        <div class="chart-card">
+            <div id="monthly"></div>
+        </div>
+        <div class="chart-card">
+            <div id="hourly"></div>
+        </div>
+        <div class="chart-card">
+            <div id="weekday"></div>
+        </div>
+        <div class="chart-card full-width">
+            <div id="heatmap"></div>
+        </div>
+    </div>
+
+    <script>
+        const bg = '#fffef5';
+        const layout_base = {
+            paper_bgcolor: bg, plot_bgcolor: bg,
+            font: { family: 'Nunito', color: '#5c4a32', size: 12 },
+            margin: { t: 44, b: 60, l: 60, r: 20 },
+            height: 370,
+        };
+        const cfg = { responsive: true };
+
+        Plotly.newPlot('stores', [{
+            x: {{ store_totals|safe }}, y: {{ store_names|safe }},
+            type: 'bar', orientation: 'h',
+            marker: { color: '#6abf69', line: { color: '#3e7c17', width: 1.5 } },
+        }], { ...layout_base, title: { text: 'Top Stores by Spend', font: { size: 16 } }, yaxis: { autorange: 'reversed' }, margin: { ...layout_base.margin, l: 180 } }, cfg);
+
+        Plotly.newPlot('monthly', [{
+            x: {{ month_labels|safe }}, y: {{ month_totals|safe }},
+            type: 'bar',
+            marker: { color: '#7ecce5', line: { color: '#4a9bb5', width: 1.5 } },
+        }], { ...layout_base, title: { text: 'Monthly Spending', font: { size: 16 } } }, cfg);
+
+        Plotly.newPlot('hourly', [{
+            x: {{ hour_labels|safe }}, y: {{ hour_values|safe }},
+            type: 'bar',
+            marker: { color: '#f4c842', line: { color: '#c4a96a', width: 1.5 } },
+        }], { ...layout_base, title: { text: 'Orders by Hour', font: { size: 16 } } }, cfg);
+
+        Plotly.newPlot('weekday', [{
+            x: {{ day_order|safe }}, y: {{ weekday_values|safe }},
+            type: 'bar',
+            marker: { color: '#e88b6a', line: { color: '#c46a4a', width: 1.5 } },
+        }], { ...layout_base, title: { text: 'Orders by Day of Week', font: { size: 16 } } }, cfg);
+
+        // Wrapped
+        const wrappedRaw = {{ wrapped_data|safe }};
+        const wrappedAdj = {{ wrapped_data_adj|safe }};
+        const yearSelect = document.getElementById('year-select');
+        const inflationToggle = document.getElementById('inflation-toggle');
+        const cardsDiv = document.getElementById('wrapped-cards');
+
+        Object.keys(wrappedRaw).forEach(key => {
+            const opt = document.createElement('option');
+            opt.value = key; opt.textContent = key;
+            yearSelect.appendChild(opt);
+        });
+
+        function renderWrapped(key) {
+            const src = inflationToggle.checked ? wrappedAdj : wrappedRaw;
+            const d = src[key];
+            if (!d) { cardsDiv.innerHTML = ''; return; }
+            cardsDiv.innerHTML = `
+                <div style="display:flex; gap:12px;">
+                    <div class="wrap-card" style="flex:1; text-align:center;">
+                        <div class="big">${d.total_spent}</div>
+                        <div class="note">Total spent${key === 'All Time' ? '' : ' in ' + key}</div>
+                    </div>
+                    <div class="wrap-card" style="flex:1; text-align:center;">
+                        <div class="big">${d.total_orders}</div>
+                        <div class="note">Orders placed${key === 'All Time' ? '' : ' in ' + key}</div>
+                    </div>
+                </div>
+                <div class="wrap-card">
+                    <div class="big">${d.fav_store_name}</div>
+                    <div class="note">Your #1 store. You gave them ${d.fav_store_total} (${d.fav_store_pct}% of spending). They should name a menu item after you.</div>
+                </div>
+                <div class="wrap-card">
+                    <div class="big">${d.fav_item_name}</div>
+                    <div class="note">Ordered ${d.fav_item_count} times. At this point it's not a craving, it's a personality trait.</div>
+                </div>
+                <div class="wrap-card">
+                    <div class="big">${d.peak_hour_label} on ${d.peak_day_name}s</div>
+                    <div class="note">Your peak ordering time. ${d.peak_hour_count} orders placed at this hour. The delivery driver knows your face.</div>
+                </div>
+                <div class="wrap-card">
+                    <div class="big">${d.biggest_month_label}</div>
+                    <div class="note">Your weakest month at ${d.biggest_month_total}. Whatever happened that month... we hope you're okay.</div>
+                </div>
+                <div class="wrap-card" style="text-align: center;">
+                    <div class="big">${d.avg_per_order} per order</div>
+                    <div class="note">Your average order total. That's a lot of "I'll just get something small."</div>
+                </div>
+            `;
+        }
+
+        yearSelect.addEventListener('change', () => renderWrapped(yearSelect.value));
+        inflationToggle.addEventListener('change', () => renderWrapped(yearSelect.value));
+        renderWrapped('All Time');
+
+        Plotly.newPlot('heatmap', [{
+            z: {{ heatmap_data|safe }}, y: {{ heatmap_days|safe }},
+            type: 'heatmap',
+            colorscale: [[0, '#fffef5'], [0.25, '#d4e8c2'], [0.5, '#8fc46a'], [0.75, '#4a9b3e'], [1, '#2d6b1e']],
+            colorbar: { title: '$' },
+        }], { ...layout_base, title: { text: 'Weekly Spending Heatmap', font: { size: 16 } }, height: 300, margin: { ...layout_base.margin, l: 60 } }, cfg);
+    </script>
+</body>
+</html>
+"""
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-p", "--port", type=int, default=5000)
+    args = parser.parse_args()
+    app.run(debug=True, port=args.port)

import_csv.py

@@ -0,0 +1,84 @@
+#!/usr/bin/env python3
+"""Import a DoorDash CSV export into doordash.db."""
+
+import csv
+import sqlite3
+import sys
+from pathlib import Path
+
+DB_PATH = Path(__file__).parent / "doordash.db"
+
+CREATE_TABLE = """CREATE TABLE IF NOT EXISTS "doordash"(
+    "ITEM" TEXT, "CATEGORY" TEXT, "STORE_NAME" TEXT, "UNIT_PRICE" TEXT,
+    "QUANTITY" TEXT, "SUBTOTAL" TEXT, "CREATED_AT" TEXT, "DELIVERY_TIME" TEXT,
+    "DELIVERY_ADDRESS" TEXT
+);"""
+
+EXPECTED_HEADER = [
+    "ITEM", "CATEGORY", "STORE_NAME", "UNIT_PRICE", "QUANTITY",
+    "SUBTOTAL", "CREATED_AT", "DELIVERY_TIME", "DELIVERY_ADDRESS",
+]
+
+
+def import_csv(csv_path: str):
+    path = Path(csv_path)
+    if not path.exists():
+        print(f"Error: {csv_path} not found")
+        sys.exit(1)
+
+    conn = sqlite3.connect(DB_PATH)
+    c = conn.cursor()
+    c.execute(CREATE_TABLE)
+
+    # Get existing row count for reporting
+    before_count = c.execute("SELECT COUNT(*) FROM doordash").fetchone()[0]
+
+    # Check for duplicates using CREATED_AT + ITEM + STORE_NAME
+    existing = set()
+    for row in c.execute("SELECT ITEM, STORE_NAME, CREATED_AT FROM doordash"):
+        existing.add((row[0], row[1], row[2]))
+
+    imported = 0
+    skipped = 0
+
+    with open(path, newline="") as f:
+        reader = csv.reader(f)
+        header = next(reader)
+
+        # Validate header
+        header_upper = [h.strip().upper() for h in header]
+        if header_upper != EXPECTED_HEADER:
+            print(f"Error: unexpected CSV header.\nExpected: {EXPECTED_HEADER}\nGot:      {header_upper}")
+            sys.exit(1)
+
+        for row in reader:
+            if len(row) != 9:
+                print(f"Warning: skipping row with {len(row)} columns: {row[:3]}...")
+                skipped += 1
+                continue
+
+            key = (row[0], row[2], row[6])  # ITEM, STORE_NAME, CREATED_AT
+            if key in existing:
+                skipped += 1
+                continue
+
+            c.execute("INSERT INTO doordash VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)", row)
+            existing.add(key)
+            imported += 1
+
+    conn.commit()
+    after_count = c.execute("SELECT COUNT(*) FROM doordash").fetchone()[0]
+    conn.close()
+
+    print(f"Done! Imported {imported} rows, skipped {skipped} duplicates.")
+    print(f"Total rows: {before_count} -> {after_count}")
+
+
+if __name__ == "__main__":
+    if len(sys.argv) < 2:
+        print(f"Usage: {sys.argv[0]} <csv_file> [csv_file2 ...]")
+        sys.exit(1)
+
+    for csv_file in sys.argv[1:]:
+        print(f"\nImporting {csv_file}...")
+        import_csv(csv_file)

main.py

@@ -1,10 +1,13 @@
 import sqlite3
+import csv
+import sys
 from pprint import pprint
 import matplotlib.pyplot as plt
 import numpy as np
 from datetime import datetime
 from collections import defaultdict
 
+
 def weakness_by_hours(hours):
     keys = list(hours.keys())
     keys.sort()
@@ -12,9 +15,8 @@ def weakness_by_hours(hours):
     for key in keys:
         print(key, len(hours.get(key)))
 
-
     fig, ax = plt.subplots()
-    ax.tick_params(axis='x', labelrotation=45)
+    ax.tick_params(axis="x", labelrotation=45)
     hour_list = keys
     counts = [len(hours.get(key)) for key in hours]
     ax.bar(hour_list, counts)
@@ -22,6 +24,7 @@ def weakness_by_hours(hours):
     ax.set_title("akshay's moments of weakness")
     plt.show()
 
+
 class Weakness:
     def __init__(self, row):
         self.name = row[0]
@@ -31,6 +34,7 @@ class Weakness:
             self.time = datetime.today()
         self.total = row[2]
 
+
 def weaknessInAnHour(results):
     weaknesses = [Weakness(row) for row in results]
     restaurants = defaultdict(lambda: 0)
@@ -39,13 +43,12 @@ def weaknessInAnHour(results):
         if weakness.time.hour == 0:
             restaurants[weakness.name] += 1
 
-    print(restaurants)
-
     fig, ax = plt.subplots()
-    plt.xticks(rotation=45, ha='right')
+    plt.xticks(rotation=45, ha="right")
     ax.bar(restaurants.keys(), restaurants.values())
     plt.show()
 
+
 def weaknessPerMonth(results):
     weaknesses = [Weakness(row) for row in results]
     months = defaultdict(lambda: 0)
@@ -59,6 +62,7 @@ def weaknessPerMonth(results):
     ax.bar(sorted_keys, sorted_amounts)
     plt.show()
 
+
 def weaknessPerDayOverYear(results):
     weaknesses = [Weakness(row) for row in results]
     months = defaultdict(lambda: 0)
@@ -70,30 +74,129 @@ def weaknessPerDayOverYear(results):
         day = weakness.time.isocalendar().weekday - 1
         week_array[week][day] += weakness.total
 
-    week_array = np.rot90(np.array(week_array)).round()
+    week_array = np.rot90(np.array(week_array)).round().astype(int)
     fig, ax = plt.subplots()
-    im = ax.imshow(week_array, cmap="RdYlGn_r")
+    im = ax.imshow(week_array, cmap="Reds")
 
-    ax.set_yticks(np.arange(7), labels=["Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday"])
+    ax.set_yticks(
-    ax.set_xticks(np.arange(53), labels=[ f"Week {x+1}" for x in range(53)])
+        np.arange(7),
+        labels=[
+            "Sunday",
+            "Monday",
+            "Tuesday",
+            "Wednesday",
+            "Thursday",
+            "Friday",
+            "Saturday",
+        ],
+    )
+    ax.set_xticks(
+        np.arange(53),
+        labels=[
+            "",
+            "Jan",
+            "",
+            "",
+            "",
+            "Feb",
+            "",
+            "",
+            "",
+            "",
+            "Mar",
+            "",
+            "",
+            "",
+            "Apr",
+            "",
+            "",
+            "",
+            "",
+            "May",
+            "",
+            "",
+            "",
+            "Jun",
+            "",
+            "",
+            "",
+            "Jul",
+            "",
+            "",
+            "",
+            "Aug",
+            "",
+            "",
+            "",
+            "",
+            "Sep",
+            "",
+            "",
+            "",
+            "Oct",
+            "",
+            "",
+            "",
+            "",
+            "Nov",
+            "",
+            "",
+            "",
+            "Dec",
+            "",
+            "",
+            "",
+        ],
+    )
+    # [ f"Week {x+1}" for x in range(53)])
 
-    plt.setp(ax.get_xticklabels(), rotation=45, ha="right",
+    plt.setp(ax.get_xticklabels(), rotation=45, ha="right", rotation_mode="anchor")
-         rotation_mode="anchor")
     for i in range(53):
         for j in range(7):
-            text = ax.text(i, j, week_array[j, i],
+            pass
-                           ha="center", va="center", color="w", fontsize=5.0)
+            # text = ax.text(i, j, week_array[j, i],
-
+            #                ha="center", va="center", color="0", fontsize=12)
 
     ax.set_title("akshay weakness in 2022")
     fig.tight_layout()
     plt.show()
 
+def validateRow(row):
+    if len(row) != 9:
+        raise Exception("Should have 9 columns in Doordash data export")
+
+    float(row[3])
 
     
 
-with sqlite3.connect("doordash.db") as connection:
+def importCSV(filename: str):
-    c = connection.cursor()
+    CREATE_TABLE_COMMAND = """CREATE TABLE IF NOT EXISTS "doordash"(
-    results = c.execute("select STORE_NAME, DELIVERY_TIME, sum(cast(SUBTOTAL as decimal)) from doordash group by DELIVERY_TIME, STORE_NAME;")
+"ITEM" TEXT, "CATEGORY" TEXT, "STORE_NAME" TEXT, "UNIT_PRICE" TEXT,
+ "QUANTITY" TEXT, "SUBTOTAL" TEXT, "CREATED_AT" TEXT, "DELIVERY_TIME" TEXT,
+ "DELIVERY_ADDRESS" TEXT);"""
 
-    weaknessPerDayOverYear(results)
+    csvReader = csv.reader(open("yeet.csv"), delimiter=",", quotechar='"')
+
+    filepart = filename.split(".")[0] + ".db"
+    conn = sqlite3.connect(filepart)
+    c = conn.cursor()
+    c.execute(CREATE_TABLE_COMMAND)
+
+    # Skip first row.
+    next(csvReader)
+
+    for row in csvReader:
+        validateRow(row)
+        c.execute("insert into doordash values (?, ?, ?, ?, ?, ?, ?, ?, ?)", row)
+    conn.commit()
+
+
+
+
+
+
+
+if __name__ == "__main__":
+    if len(sys.argv) < 2:
+        raise Exception("input csv missing")
+    importCSV(sys.argv[1])

pyproject.toml

@@ -0,0 +1,15 @@
+[project]
+name = "weakness"
+version = "0.1.0"
+description = "DoorDash spending dashboard"
+requires-python = ">=3.14"
+dependencies = [
+    "flask>=3.1.3",
+    "plotly>=6.6.0",
+    "numpy>=2.0",
+    "gunicorn>=25.1.0",
+]
+
+[project.scripts]
+weakness = "app:app.run"
+import-csv = "import_csv:main"

uv.lock

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