From 5ba20a25637b3d5999582a80faaa36e20ffae119 Mon Sep 17 00:00:00 2001
From: falsycat <me@falsy.cat>
Date: Sat, 19 Jul 2025 19:59:17 +0900
Subject: [PATCH] add pretty-report program

---
 pretty-report/__main__.py | 137 ++++++++++++++++++++++++++++++++++++++
 requirements.txt          |   5 +-
 2 files changed, 140 insertions(+), 2 deletions(-)
 create mode 100644 pretty-report/__main__.py

diff --git a/pretty-report/__main__.py b/pretty-report/__main__.py
new file mode 100644
index 0000000..cb6c9d1
--- /dev/null
+++ b/pretty-report/__main__.py
@@ -0,0 +1,137 @@
+import sys
+ 
+import dash
+from dash import dcc, html
+import pandas as pd
+import plotly.graph_objects as go
+import plotly.express as px
+
+def numerize(df, column):
+  if isinstance(column, list):
+    for item in column:
+      df = numerize(df, item)
+  else:
+    df[column] = pd.to_numeric(df[column], errors="coerce")
+  return df
+
+data = []
+with open("financials.txt", "r") as f:
+  for line in f:
+    line = line.strip()
+    if line == "":
+      pass
+    elif line.startswith("#"):
+      data.append([])
+    else:
+      data[-1].append(line.split(","))
+
+asset = numerize(pd.DataFrame(data[0], columns=["Name", "Amount"]), "Amount")
+debt  = numerize(pd.DataFrame(data[2], columns=["Name", "Amount"]), "Amount")
+net   = numerize(pd.DataFrame(data[3], columns=["Name", "Amount"]), "Amount")
+
+expense = numerize(pd.DataFrame(data[4], columns=["Name", "Amount"]), "Amount")
+revenue = numerize(pd.DataFrame(data[5], columns=["Name", "Amount"]), "Amount")
+
+inv_asset   = numerize(pd.DataFrame(data[1], columns=["Name", "Amount"]), "Amount")
+inv_expense = numerize(pd.DataFrame(data[7], columns=["Name", "Amount"]), "Amount")
+inv_revenue = numerize(pd.DataFrame(data[8], columns=["Name", "Amount"]), "Amount")
+
+food_expense = numerize(pd.DataFrame(data[6], columns=["Name", "Amount"]), "Amount")
+
+daily = numerize(pd.DataFrame(data[9], columns=["Date", "Asset", "RealNet", "Risked"]), ["Asset", "RealNet", "Risked"])
+
+# ---- displaying ----
+def PieAndTable(title, data):
+  total = sum(data["Amount"])
+
+  fig = px.pie(
+    data.sort_values(by="Amount", ascending=False),
+    names="Name",
+    values="Amount",
+    hole=0.5,
+    hover_name="Name",
+    title=title,
+  )
+  fig.update_traces(
+    hovertemplate="%{label}<br>%{value} (%{percent})",
+    textinfo="label",
+  )
+  fig.update_layout(
+    annotations=[
+      dict(
+        x=0.5, y=0.5,
+        text=f"{total:,}",
+        showarrow=False,
+      ),
+    ],
+    showlegend=False,
+  )
+  return dcc.Graph(
+    style={"flex": "1", "height": "20rem"},
+    figure=fig,
+  )
+def PlWaterfall(title, e, r):
+  merged = pd.merge(e, r, on="Name", suffixes=["E", "R"], how="outer")
+  merged["Amount"] = merged["AmountR"].fillna(0) - merged["AmountE"].fillna(0)
+  merged = merged.sort_values(by="Amount", ascending=False)
+
+  fig = go.Figure(go.Waterfall(
+    orientation="v",
+    x=merged["Name"],
+    y=merged["Amount"],
+  ))
+  fig.update_layout(title=title)
+  return dcc.Graph(figure=fig)
+
+def DailyLines(df):
+  fig = go.Figure()
+  fig.add_trace(go.Scatter(
+    x=df["Date"],
+    y=df["Asset"],
+    mode="lines",
+    name="Total"
+  ))
+  fig.add_trace(go.Scatter(
+    x=df["Date"],
+    y=df["RealNet"],
+    mode="lines",
+    name="Realtime Net"
+  ))
+  fig.add_trace(go.Scatter(
+    x=df["Date"],
+    y=df["Risked"],
+    mode="lines",
+    name="Risked"
+  ))
+  fig.update_layout(hovermode="x unified")
+  return dcc.Graph(figure=fig)
+
+app = dash.Dash(__name__)
+app.layout = html.Div([
+  html.H2("WHOLE"),
+  html.Div(
+    style={"display": "flex", "gap": "1rem"},
+    children=[
+      PieAndTable("Asset", asset),
+      PieAndTable("Debt", debt),
+      PieAndTable("Net", net),
+    ],
+  ),
+  PlWaterfall("P&L", expense, revenue),
+
+  html.H2("DAILY"),
+  html.Div(children=[
+    DailyLines(daily),
+  ]),
+
+  html.H2("DETAILS"),
+  html.Div(
+    style={"display": "flex", "gap": "1rem"},
+    children=[
+      PieAndTable("Food Expenses", food_expense),
+      PieAndTable("RiskedAsset", inv_asset),
+    ],
+  ),
+  PlWaterfall("Investment P&L", inv_expense, inv_revenue),
+])
+app.run(debug=True)
diff --git a/requirements.txt b/requirements.txt
index aa094d9..b686c0e 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,2 +1,3 @@
-numpy
-matplotlib
+pandas
+plotly
+dash