From e28d71fa5ae32138fd29990a6cc2f32a2bf05972 Mon Sep 17 00:00:00 2001 From: Ryan Chen Date: Fri, 13 Mar 2026 17:27:06 -0400 Subject: [PATCH] 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 --- .dockerignore | 11 + .gitignore | 8 +- .python-version | 1 + Dockerfile | 14 ++ app.py | 591 ++++++++++++++++++++++++++++++++++++++++++++++++ import_csv.py | 84 +++++++ pyproject.toml | 15 ++ uv.lock | 204 +++++++++++++++++ 8 files changed, 926 insertions(+), 2 deletions(-) create mode 100644 .dockerignore create mode 100644 .python-version create mode 100644 Dockerfile create mode 100644 app.py create mode 100644 import_csv.py create mode 100644 pyproject.toml create mode 100644 uv.lock diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 0000000..9165e0c --- /dev/null +++ b/.dockerignore @@ -0,0 +1,11 @@ +.git +.venv +env +venv +__pycache__ +*.pyc +.DS_Store +images +*.db +*.csv +*.db.bak diff --git a/.gitignore b/.gitignore index 7aaac2c..3364e7a 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,9 @@ # who the fuck forgets to add this smh - env/ -venv/ \ No newline at end of file +venv/ +.venv/ +__pycache__/ +*.pyc +.DS_Store +*.db.bak \ No newline at end of file diff --git a/.python-version b/.python-version new file mode 100644 index 0000000..6324d40 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.14 diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..81f6fa0 --- /dev/null +++ b/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"] diff --git a/app.py b/app.py new file mode 100644 index 0000000..40397d0 --- /dev/null +++ b/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 = """ + + + Moments of Weakness + + + + +
+

Moments of Weakness

+

See exactly how much you've been spending on delivery

+ + {% with messages = get_flashed_messages(with_categories=true) %} + {% for cat, msg in messages %} +
{{ msg }}
+ {% endfor %} + {% endwith %} + +
+
+

Upload Your Data

+

Drop your DoorDash CSV export to see your dashboard. Nothing is stored.

+
+
+
📄
+
Click or drag a CSV file here
+
consumer_order_details.csv from DoorDash
+
+ +
+ +
+
+ +
or
+ +
+

View Saved Data

+

Browse the dashboard with previously imported order history.

+ Open Dashboard +
+
+
+ + + + +""" + +TEMPLATE = """ + + + Weakness Dashboard + + + + + +
+

Moments of Weakness

+ Home +
+

DoorDash spending dashboard

+ {% with messages = get_flashed_messages(with_categories=true) %} + {% for cat, msg in messages %} +
{{ msg }}
+ {% endfor %} + {% endwith %} + +
+
+
{{ total_spent }}
+
Total Spent
+
+
+
{{ total_items }}
+
Items Ordered
+
+
+
{{ total_orders }}
+
Unique Orders
+
+
+ +
+
+
+

Your Weakness Wrapped

+

A look at your most questionable financial decisions

+
+
+ + +
+
+
+
+ +
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ + + + +""" + +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) diff --git a/import_csv.py b/import_csv.py new file mode 100644 index 0000000..bcc74e0 --- /dev/null +++ b/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_file2 ...]") + sys.exit(1) + + for csv_file in sys.argv[1:]: + print(f"\nImporting {csv_file}...") + import_csv(csv_file) diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..e68d556 --- /dev/null +++ b/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" diff --git a/uv.lock b/uv.lock new file mode 100644 index 0000000..174f30a --- /dev/null +++ b/uv.lock @@ -0,0 +1,204 @@ +version = 1 +revision = 2 +requires-python = ">=3.14" + +[[package]] +name = "blinker" +version = "1.9.0" 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