Skip to main content
This guide covers common issues you may encounter when using the Extrator de Tarefas Auvo application and how to resolve them.

​
File Upload Errors

​
Unsupported File Format

Error Message: “Por favor, selecione um arquivo .csv, .xls ou .xlsx”This error occurs when you attempt to upload a file that is not in a supported format.
Solution: The application only accepts the following file formats:
  • .csv - Comma-separated values
  • .xls - Excel 97-2003 format
  • .xlsx - Excel 2007+ format
Ensure your Auvo export file has one of these extensions. If you have a different format, convert it using Excel or another spreadsheet application.

​
No File Selected Error

Error Message: “Nenhum arquivo selecionado”This appears when you click “Processar Relatório” without selecting a file.
Solution:
  1. Click the “Selecionar arquivo” button on the upload page
  2. Choose your Auvo CSV/Excel file from your computer
  3. Verify the filename appears next to the button before clicking “Processar Relatório”

​
Empty File or Missing Columns

Error Message: “Erro ao processar o arquivo: [KeyError or column not found]”This occurs when the uploaded file doesn’t match the expected Auvo export format.
Solution: The application expects files with these specific columns after skipping 5 header rows:
  • Data
  • Cliente
  • Endereco
  • OS Digital
  • Relato
The application automatically skips the first 5 rows of your file (app.py:38, app.py:42). Ensure your Auvo export follows this format.
To verify your file:
  1. Open the CSV/Excel file in a spreadsheet application
  2. Check that row 6 contains the column headers listed above
  3. Ensure the Relato column exists and contains task descriptions

​
Dependency and Installation Issues

​
WeasyPrint Installation Problems

Error Message: PDF download fails or WeasyPrint import errorsWeasyPrint requires system-level dependencies that may not be installed by default.
Solution for Windows:
  1. Install GTK3 runtime from: https://github.com/tschoonj/GTK-for-Windows-Runtime-Environment-Installer
  2. Restart your terminal/command prompt
  3. Reinstall WeasyPrint:
pip install --force-reinstall weasyprint==66.0
Solution for Linux (Ubuntu/Debian): 
sudo apt-get update
sudo apt-get install -y \
    python3-pip \
    python3-cffi \
    python3-brotli \
    libpango-1.0-0 \
    libpangoft2-1.0-0 \
    libgdk-pixbuf2.0-0 \
    libffi-dev \
    shared-mime-info

pip install weasyprint==66.0
Solution for macOS: 
brew install pango gdk-pixbuf libffi
pip install weasyprint==66.0
After installing system dependencies, always restart your terminal and reactivate your virtual environment before running the application.

​
Python Version Incompatibility

Error Message: Package installation fails or import errorsThe application requires Python 3.10 or higher.
Solution:
  1. Check your Python version:
python --version
  1. If you have Python < 3.10, install a newer version from https://www.python.org/downloads/
  2. Create a new virtual environment with the correct version:
python3.10 -m venv venv
source venv/bin/activate  # On Windows: .\venv\Scripts\activate
pip install -r requirements.txt

​
Missing Dependencies

Error Message: “ModuleNotFoundError: No module named ‘pandas’” or similarRequired packages are not installed in your environment.
Solution:
  1. Ensure your virtual environment is activated
  2. Install all dependencies from requirements.txt:
pip install -r requirements.txt
  1. Verify critical packages are installed:
pip list | grep -E "Flask|pandas|weasyprint|openpyxl"
Expected versions (from requirements.txt):
  • Flask==3.1.2
  • pandas==2.3.2
  • weasyprint==66.0
  • openpyxl==3.1.5

​
CSV Format and Data Issues

​
Pandas Read Errors

Error Message: “Error tokenizing data” or “ParserError”The CSV file has formatting issues or encoding problems.
Solution:
  1. Open the CSV file in a text editor that shows encoding (like Notepad++ or VS Code)
  2. Save the file with UTF-8 encoding
  3. Re-upload to the application
Alternatively, open in Excel and “Save As” CSV UTF-8 format.
If your CSV uses semicolons (;) instead of commas (,):
  1. Open the file in Excel
  2. Go to File → Save As
  3. Choose “CSV (Comma delimited) (*.csv)”
  4. Save and re-upload
If you see data corruption errors:
  1. Export a fresh copy from Auvo
  2. Don’t manually edit the CSV file before uploading
  3. Ensure the file download completed successfully (check file size)

​
No Results Found

Issue: File processes successfully but shows 0 tarefas encontradasThis means none of the records in the Relato column contain your configured keywords.
Solution:
  1. Go to the Configurações page in the application
  2. Review your current keywords
  3. Add keywords that match the terminology used in your Auvo reports
  4. Keywords are case-insensitive and search for partial matches
Default keywords (app.py:115):
  • solicitar peça
  • quebrado, quebrada, quebrados
  • orçamento
  • danificada, danificado, danificados, danificadas
  • trocar cabo
  • soldar
  • trocar
  • instalar
Use the comma-separated format when adding keywords: keyword1, keyword2, keyword3

​
Excel Engine Errors

Error Message: “Missing optional dependency ‘openpyxl’”The Excel engine is not installed.
Solution: 
pip install openpyxl==3.1.5
This dependency is required for reading .xlsx files (app.py:42).

​
Session and Temporary File Issues

​
Results Expired Error

Error Message: “Os resultados expiraram. Por favor, processe o arquivo novamente.”This occurs when attempting to download results after the session has expired or been cleared.
Solution: The application stores filtered results in temporary files using session data (app.py:145-152). Sessions can expire when:
  • Your browser session ends
  • You clear browser cookies
  • The server restarts
  • You switch browsers or use incognito mode
Best Practice: Download your Excel/PDF reports immediately after processing. Don’t rely on the session persisting between visits.
To process the file again:
  1. Return to the home page
  2. Upload your CSV/Excel file again
  3. Click “Processar Relatório”
  4. Download the results immediately

​
Temporary Files Accumulating

Issue: The temp folder grows large over timeEach upload creates a temporary CSV file with a unique UUID filename (app.py:145).
Solution: Periodically clean the temp folder: 
# From the application root directory
rm -f temp/*.csv  # Linux/macOS
del /Q temp\*.csv  # Windows
Consider setting up a cron job or scheduled task to automatically clean temporary files older than 24 hours.

​
Missing SECRET_KEY Error

Error Message: Application fails to start or session errorsThe .env file is missing or doesn’t contain a SECRET_KEY.
Solution:
  1. Create a .env file in the project root directory
  2. Generate a secure secret key:
python -c "import secrets; print('SECRET_KEY=' + secrets.token_hex(32))"
  1. Copy the output to your .env file:
SECRET_KEY=your_generated_key_here
  1. Restart the application
The SECRET_KEY is required for Flask session management (app.py:15). Never commit this file to version control.

​
Browser and Display Issues

​
Table Not Displaying Correctly

Solution: Ensure JavaScript is enabled in your browser. The results table uses dynamic search functionality that requires JavaScript.

​
Download Buttons Not Working

Solution:
  1. Check your browser’s pop-up blocker settings
  2. Ensure downloads are not blocked for localhost
  3. Check browser console for JavaScript errors (F12 → Console tab)
The OS Digital column should contain clickable URLs (app.py:160).
Solution: If links aren’t clickable:
  1. Verify the URLs in your CSV start with http:// or https://
  2. The criar_links function only converts strings starting with “http” (app.py:28)
  3. Update your Auvo export or source data to include complete URLs

​
Performance Issues

​
Slow Processing for Large Files

The application loads the entire CSV into memory using pandas. Very large files (>100MB) may take time to process.
Solutions:
  • Split large exports into smaller date ranges in Auvo
  • Increase available system RAM
  • Process files during off-peak hours
  • Close other applications to free up memory

​
PDF Generation Timeout

Issue: PDF download times out or fails for large result setsWeasyPrint can be slow when rendering tables with hundreds of rows (app.py:257).
Solution:
  1. Use Excel export instead for large datasets
  2. Filter results using more specific keywords to reduce row count
  3. Increase the Flask timeout in app.py if running in production

​
Getting Additional Help

If you encounter errors not covered in this guide:
  1. Check the terminal/console where you ran python app.py
  2. Look for error messages and stack traces
  3. Error logging is printed to stdout (app.py:175)
  4. Share the error message when seeking help
Common debugging steps: 
# Verify Python version
python --version

# Check installed packages
pip list

# Verify virtual environment is activated
which python  # Linux/macOS
where python  # Windows

# Test pandas can read your file
python -c "import pandas as pd; print(pd.read_csv('your_file.csv', skiprows=5).columns)"
When reporting issues, always include:
  • Python version
  • Operating system
  • Full error message
  • Steps to reproduce the problem

Build docs developers (and LLMs) love

Get started for freeTalk to us