Merge branch 'main' of github.com:nidionis/svr

usr/bin/expresso_graph

@@ -0,0 +1,113 @@
+#!/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}")

usr/bin/expresso_parser

@@ -0,0 +1,135 @@
+#!/usr/bin/env python
+#!/usr/bin/env python3
+import sys
+import subprocess
+import re
+from datetime import datetime
+
+# === 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 script.py input.txt [output.csv]")
+    sys.exit(1)
+
+INPUT = sys.argv[1]
+OUTPUT = sys.argv[2] if len(sys.argv) > 2 else "poker_clean.csv"
+
+# === HELPERS ===
+def money(x):
+    if not x or x.strip() in ["-", ""]:
+        return 0.0
+    return float(x.replace("€", "").replace(",", ".").strip())
+
+def category(name):
+    n = name.lower()
+    if "freeroll" in n: return "freeroll"
+    if "nitro" in n: return "nitro"
+    return "expresso"
+
+def stake(b):
+    return "micro" if b <= 1 else "low" if b <= 5 else "mid" if b <= 20 else "high"
+
+def session(h):
+    if 6 <= h < 12: return "morning"
+    if 12 <= h < 18: return "afternoon"
+    if 18 <= h < 24: return "evening"
+    return "night"
+
+# === PARSE ===
+rows = []
+errors = 0
+
+with open(INPUT, encoding="utf-8") as f:
+    for line in f:
+        raw = line.strip()
+        if not raw:
+            continue
+
+        parts = re.split(r"\s{2,}", raw)
+
+        try:
+            # DEBUG FIRST RUN ONLY (comment after)
+            # print(parts)
+
+            dt = datetime.strptime(parts[0], "%d/%m/%Y %H:%M:%S")
+            name = parts[1]
+            buy = float(parts[2]) if len(parts) > 2 else 0.0
+            players = int(parts[5]) if len(parts) > 5 and parts[5].isdigit() else None
+
+            pos = parts[6] if len(parts) > 6 and parts[6] != "-" else None
+            prize = money(parts[7]) if len(parts) > 7 else 0.0
+            net = money(parts[8]) if len(parts) > 8 else 0.0
+
+            profit = net - buy
+            h = dt.hour
+
+            rows.append({
+                "datetime": dt,
+                "game": name,
+                "buy_in": buy,
+                "players": players,
+                "position": pos,
+                "prize": prize,
+                "net": net,
+                "profit": profit,
+                "category": category(name),
+                "stake": stake(buy),
+                "hour": h,
+                "day": dt.strftime("%A"),
+                "session": session(h),
+                "result": "win" if pos == "1" else "itm" if prize > 0 else "loss"
+            })
+
+        except Exception as e:
+            errors += 1
+            if errors < 5:
+                print("Skip:", raw)
+                print("Reason:", e)
+
+# === VALIDATION ===
+if not rows:
+    print("❌ No valid rows parsed. Your format is different. Enable debug print.")
+    sys.exit(1)
+
+df = pd.DataFrame(rows)
+
+if "datetime" not in df.columns:
+    print("❌ Broken parse. Columns:", df.columns)
+    sys.exit(1)
+
+# === PROCESS ===
+df = df.sort_values("datetime")
+df["cum_profit"] = df["profit"].cumsum()
+
+# === SAVE ===
+df.to_csv(OUTPUT, index=False)
+print(f"✅ Saved {len(df)} rows → {OUTPUT}")
+print(f"⚠️ Skipped lines: {errors}")
+
+print("Games:", len(df))
+print("Total profit:", df["profit"].sum())
+print("ROI:", df["profit"].sum() / df["buy_in"].sum())
+print("Win rate:", (df["position"] == "1").mean())
+print("ITM:", (df["prize"] > 0).mean())
+
+# === GRAPH ===
+plt.figure()
+plt.plot(df["datetime"], df["cum_profit"])
+plt.xlabel("Time")
+plt.ylabel("€")
+plt.title("Cumulative Profit")
+plt.xticks(rotation=45)
+plt.tight_layout()
+plt.show()

usr/bin/openoffice-docker

@@ -0,0 +1,23 @@
+#!/bin/bash
+
+BASE_DIR=${1:-"/tmp"}
+
+if [ -z "$BASE_DIR" ]; then
+    echo "usage: $0 <base_dir>"
+    exit 1
+fi
+
+DOCKER_DIR="$BASE_DIR/docker"
+SRC_DIR="$BASE_DIR/AOO"
+
+mkdir -p "$DOCKER_DIR" "$SRC_DIR"
+
+cd "$DOCKER_DIR" || exit 1
+wget https://svn.apache.org/repos/asf/openoffice/devtools/build-scripts/4.2.0/containers/linux/Dockerfile
+
+docker build -t aoo_centos .
+
+cd "$SRC_DIR" || exit 1
+git clone https://gitbox.apache.org/repos/asf/openoffice.git .
+
+docker run -ti -v "$SRC_DIR:/workspace/AOO" aoo_centos

usr/etc/resolv.conf

@@ -1,3 +1,3 @@
-
 nameserver 1.1.1.1
 nameserver 0.0.0.0
+nameserver 8.8.8.8

usr/home/.bash_aliases

@@ -29,7 +29,7 @@ alias s="sudo -E"
 function src() {
 	source $HOME/.bashrc || true
 	d="$PWD"; while [ "$d" != "/" ]; do
-		for a in "$d/bin/activate" "$d/.env/bin/activate"; do
+		for a in "$d/bin/activate" "$d/.venv/bin/activate" "$d/.env/bin/activate"; do
 			[ -f $a ] && echo "found at $a" && . "$a" && break 2
 		done
 		d=$(dirname "$d")

usr/home/.bashrc

@@ -129,7 +129,7 @@ if [ -f /home/.bash_aliases ]; then
 fi
 
 # permet les accents
-setxkbmap us -variant intl
+#setxkbmap us -variant intl
 
 #envsubst < ${MACHINE_PATH}/dotfiles/ssh/config.template > ~/.ssh/config