app_backend.py

import os
import json
import logging
import traceback
import time
import psutil
import polars as pl
from datetime import datetime
from dotenv import load_dotenv
from fastapi import FastAPI, UploadFile, File, Form, HTTPException
from fastapi.middleware.cors import CORSMiddleware

load_dotenv()

app = FastAPI()

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_methods=["*"],
    allow_headers=["*"],
)

# Vercel filesystem is read-only except for /tmp
IS_VERCEL = "VERCEL" in os.environ
UPLOAD_ROOT = "/tmp/uploads" if IS_VERCEL else "uploads"
EXPORT_ROOT = "/tmp/exports" if IS_VERCEL else "exports"

def get_dated_path(root):
    path = os.path.join(root, datetime.now().strftime("%Y-%m-%d"))
    os.makedirs(path, exist_ok=True)
    return path

@app.post("/upload")
async def upload_file(file: UploadFile = File(...)):
    try:
        dir_path = get_dated_path(UPLOAD_ROOT)
        ext = os.path.splitext(file.filename)[1]
        now = datetime.now()
        new_filename = f"{now.strftime('%Y%m%d_%H%M%S')}_{int(now.timestamp())}{ext}"
        file_path = os.path.join(dir_path, new_filename)
        
        content = await file.read()
        with open(file_path, "wb") as f:
            f.write(content)
        
        df = pl.read_excel(file_path) if new_filename.endswith(('.xlsx', '.xls')) else pl.read_csv(file_path)
        return {"filename": new_filename, "path": file_path, "columns": df.columns, "total_rows": len(df)}
    except Exception as e:
        logging.error(traceback.format_exc())
        raise HTTPException(status_code=400, detail=str(e))

@app.post("/filter")
async def filter_data(file_path: str = Form(...), filters: str = Form(...), sorts: str = Form(...)):
    start_time = time.time()
    try:
        process = psutil.Process(os.getpid())
        df = pl.read_excel(file_path) if file_path.endswith(('.xlsx', '.xls')) else pl.read_csv(file_path)
        
        # Filtering
        for f in json.loads(filters):
            col, op, val = f['col'], f['op'], f['val']
            if not val: continue
            selector = pl.col(col)
            if op == "=": df = df.filter(selector.cast(pl.Utf8) == str(val))
            elif op == "!=": df = df.filter(selector.cast(pl.Utf8) != str(val))
            elif op == "like": df = df.filter(selector.cast(pl.Utf8).str.contains(str(val)))

        # Sorting
        sort_list = json.loads(sorts)
        if sort_list:
            df = df.sort([s['col'] for s in sort_list], descending=[s['desc'] for s in sort_list])

        if len(df) > 0:
            if "S.No" in df.columns: df = df.drop("S.No")
            df = df.insert_column(0, pl.Series("S.No", list(range(1, len(df) + 1))))

        return {
            "data": df.to_dicts(),
            "performance": {
                "execution_time": f"{round(time.time() - start_time, 4)}s",
                "memory_usage": f"{round(process.memory_info().rss / (1024 * 1024), 2)} MB",
                "cpu_utilization": f"{psutil.cpu_percent()}%",
                "physical_cores": psutil.cpu_count(logical=False),
                "logical_cores": psutil.cpu_count(logical=True),
                "total_records": len(df)
            }
        }
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.post("/export")
async def export_data(data: str = Form(...)):
    try:
        df = pl.from_dicts(json.loads(data))
        dir_path = get_dated_path(EXPORT_ROOT)
        path = os.path.join(dir_path, f"export_{datetime.now().strftime('%H%M%S')}.xlsx")
        df.write_excel(path)
        return {"path": path}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host=os.getenv("BACKEND_HOST", "172.18.177.164"), port=int(os.getenv("BACKEND_PORT", 8000)))