svr/usr/bin/expresso_graph

#!/usr/bin/env python3
import sys
import subprocess
import os

# === AUTO INSTALL ===
def ensure(pkg):
    try:
        __import__(pkg)
    except ImportError:
        subprocess.check_call([sys.executable, "-m", "pip", "install", pkg])

ensure("pandas")
ensure("matplotlib")

import pandas as pd
import matplotlib.pyplot as plt

# === ARGS ===
if len(sys.argv) < 2:
    print("Usage: python graph.py data.csv [output_dir]")
    sys.exit(1)

FILE = sys.argv[1]
OUTDIR = sys.argv[2] if len(sys.argv) > 2 else "graphs"

os.makedirs(OUTDIR, exist_ok=True)

# === LOAD ===
df = pd.read_csv(FILE)

required_cols = ["datetime", "profit", "buy_in"]
for col in required_cols:
    if col not in df.columns:
        print(f"Missing column: {col}")
        sys.exit(1)

df["datetime"] = pd.to_datetime(df["datetime"], errors="coerce")
df = df.dropna(subset=["datetime"])
df = df.sort_values("datetime")

# === CLEAN NUMERIC ===
df["profit"] = pd.to_numeric(df["profit"], errors="coerce").fillna(0)
df["buy_in"] = pd.to_numeric(df["buy_in"], errors="coerce").fillna(0)

# === CUMULATIVE PROFIT ===
df["cum_profit"] = df["profit"].cumsum()

plt.figure()
plt.plot(df["datetime"], df["cum_profit"])
plt.title("Cumulative Profit")
plt.xlabel("Time")
plt.ylabel("€")
plt.xticks(rotation=45)
plt.tight_layout()
plt.savefig(f"{OUTDIR}/cum_profit.png")
plt.close()

# === PROFIT PER GAME ===
plt.figure()
plt.scatter(range(len(df)), df["profit"])
plt.title("Profit per Game")
plt.xlabel("Game #")
plt.ylabel("€")
plt.tight_layout()
plt.savefig(f"{OUTDIR}/profit_scatter.png")
plt.close()

# === ROI BY CATEGORY (SAFE) ===
if "category" in df.columns:
    df_valid = df[df["buy_in"] > 0]

    if not df_valid.empty:
        roi = df_valid.groupby("category").apply(
            lambda x: x["profit"].sum() / x["buy_in"].sum()
        )

        plt.figure()
        roi.plot(kind="bar")
        plt.title("ROI by Category")
        plt.xlabel("Category")
        plt.ylabel("ROI")
        plt.tight_layout()
        plt.savefig(f"{OUTDIR}/roi_category.png")
        plt.close()

# === SESSION PERFORMANCE ===
if "session" in df.columns:
    session_profit = df.groupby("session")["profit"].sum()

    plt.figure()
    session_profit.plot(kind="bar")
    plt.title("Profit by Session")
    plt.xlabel("Session")
    plt.ylabel("€")
    plt.tight_layout()
    plt.savefig(f"{OUTDIR}/session_profit.png")
    plt.close()

# === POSITION DISTRIBUTION ===
if "position" in df.columns:
    pos_counts = df["position"].value_counts()

    plt.figure()
    pos_counts.plot(kind="bar")
    plt.title("Position Distribution")
    plt.xlabel("Position")
    plt.ylabel("Count")
    plt.tight_layout()
    plt.savefig(f"{OUTDIR}/positions.png")
    plt.close()

print(f"✅ Graphs saved in: {OUTDIR}")