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from fastapi import FastAPI, HTTPException, File, UploadFile |
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from fastapi.responses import FileResponse |
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from app.services.preprocessing import data_quality, standardize_data_types, handle_missing_data, handle_outliers, generate_final_report, save_cleaned_data |
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import pandas as pd |
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import io |
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import os |
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app = FastAPI(title="Data Preprocessing") |
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os.makedirs("output", exist_ok=True) |
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@app.get("/") |
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async def root(): |
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return {"message": "Welcome to the Data Preprocessing API!"} |
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@app.post("/preprocess_data/") |
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async def upload_csv(upload_file: UploadFile = File(...)): |
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try: |
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if not upload_file.filename.endswith('.csv'): |
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raise HTTPException(status_code=400, detail="File must be in CSV format!") |
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content = await upload_file.read() |
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df = pd.read_csv(io.BytesIO(content), encoding_errors="replace") |
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if df.empty: |
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raise HTTPException(status_code=400, detail="File is empty, upload the correct file") |
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data_quality(df) |
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df = standardize_data_types(df) |
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df = handle_missing_data(df) |
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df = handle_outliers(df) |
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REPORT_PATH = "output/preprocessing_report.txt" |
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generate_final_report(df, REPORT_PATH) |
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CLEANED_DATA_PATH = "output/cleaned_dataset.csv" |
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save_cleaned_data(df, CLEANED_DATA_PATH) |
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return FileResponse(CLEANED_DATA_PATH, media_type="text/csv", filename="cleaned_dataset.csv") |
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except Exception as e: |
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raise HTTPException(status_code=400, detail=f"Error processing file: {str(e)}") |
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