from flask import Flask, render_template, request, redirect, url_for, send_file
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import io
import os

app = Flask(__name__)
app.config["UPLOAD_FOLDER"] = "uploads"
os.makedirs(app.config["UPLOAD_FOLDER"], exist_ok=True)

# Global variables to hold data between requests
df1, df2, limits, cols_to_plot = None, None, {}, []

def process_files(golden_file, test_file):
    global df1, df2, limits, cols_to_plot
    limits_df1 = pd.read_excel(golden_file, nrows=4)
    df1 = pd.read_excel(golden_file)
    df1 = df1.drop([0, 1, 2, 3])
    df2 = pd.read_excel(test_file)
    df2 = df2.drop([0, 1, 2, 3])

    df1 = df1.apply(pd.to_numeric, errors="coerce")
    df2 = df2.apply(pd.to_numeric, errors="coerce")

    limits_df1 = limits_df1.drop([0])
    ignore_cols = ["SITE_NUM", "PART_ID", "PASSFG", "SOFT_BIN", "T_TIME", "TEST_NUM"]
    cols_to_plot = [col for col in limits_df1.columns if "_" in col and col not in ignore_cols]
    limits_df1 = limits_df1.drop(columns=ignore_cols)

    limits = {
        col: {"LL": limits_df1.iloc[0][col], "UL": limits_df1.iloc[1][col]}
        for col in limits_df1.columns
    }
    return df1, df2, limits, cols_to_plot


def generate_plot(col):
    """Generate a matplotlib plot for a single column."""
    plt.figure(figsize=(6, 4))

    x1 = np.arange(1, len(df1[col]) + 1)
    y1 = pd.to_numeric(df1[col], errors="coerce").values
    plt.plot(x1, y1, marker="o", linestyle="-", color="blue", label="Golden")

    if col in df2.columns:
        x2 = np.arange(1, len(df2[col]) + 1)
        y2 = pd.to_numeric(df2[col], errors="coerce").values
        plt.plot(x2, y2, marker="s", linestyle="--", color="red", label="Test")

    if col in limits:
        ll, ul = limits[col]["LL"], limits[col]["UL"]
        plt.axhline(ll, color="green", linestyle="--", linewidth=2, label="LL")
        plt.axhline(ul, color="orange", linestyle="--", linewidth=2, label="UL")

    plt.title(f"{col}")
    plt.xlabel("Part # (sequence)")
    plt.ylabel("Value")
    plt.grid(True, linestyle="--", alpha=0.7)
    plt.legend(fontsize="small")
    plt.tight_layout()

    buf = io.BytesIO()
    plt.savefig(buf, format="png", bbox_inches="tight")
    buf.seek(0)
    plt.close()
    return buf


@app.route("/", methods=["GET", "POST"])
def index():
    global df1, df2, limits, cols_to_plot

    if request.method == "POST":
        golden_file = request.files.get("golden_file")
        test_file = request.files.get("test_file")

        if not golden_file or not test_file:
            return render_template("index.html", error="Please upload both files.")

        try:
            df1, df2, limits, cols_to_plot = process_files(golden_file, test_file)

            # Show the first 3 plots initially
            preview_cols = cols_to_plot[:3]
            return render_template(
                "plot.html",
                cols=cols_to_plot,
                preview_cols=preview_cols,
            )

        except Exception as e:
            return render_template("index.html", error=f"Error: {str(e)}")

    return render_template("index.html")


@app.route("/plot_image/<col>")
def plot_image(col):
    """Return plot as PNG stream for the selected column."""
    buf = generate_plot(col)
    return send_file(buf, mimetype="image/png")


if __name__ == "__main__":
    app.run(host="0.0.0.0", port=7860, debug=True)