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Upload README.md with huggingface_hub

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  ---
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- title: SFDataLoader
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- emoji: 🐨
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- colorFrom: indigo
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  colorTo: purple
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  sdk: gradio
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- sdk_version: 5.38.2
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  app_file: app.py
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  pinned: false
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  license: mit
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  ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ title: Salesforce Data Loader
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+ emoji: πŸš€
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+ colorFrom: blue
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  colorTo: purple
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  sdk: gradio
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+ sdk_version: 4.44.0
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  app_file: app.py
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  pinned: false
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  license: mit
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  ---
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+ # πŸš€ Salesforce Data Loader
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+
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+ A powerful, user-friendly web application for uploading and downloading data from Salesforce. Built with Gradio and designed for easy bulk data operations.
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+
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+ ## ✨ Features
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+
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+ ### πŸ” Secure Authentication
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+ - Connect to Salesforce production or sandbox environments
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+ - Secure credential handling with username, password, and security token
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+ - Real-time connection status feedback
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+
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+ ### πŸ“€ Data Upload
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+ - **File Support**: Upload CSV and Excel files (.csv, .xlsx, .xls)
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+ - **Bulk Operations**:
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+ - **Insert**: Add new records
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+ - **Update**: Modify existing records
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+ - **Upsert**: Insert or update based on external ID
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+ - **Object Support**: Works with common Salesforce objects (Account, Contact, Lead, Opportunity, Case, etc.)
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+ - **Field Mapping**: Automatic field detection and validation
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+ - **Results Tracking**: Download detailed results with success/error reports
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+
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+ ### πŸ“₯ Data Export
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+ - Export data from any accessible Salesforce object
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+ - Select specific fields to export
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+ - Configurable record limits (100-10,000 records)
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+ - Download as CSV format
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+ - SOQL query generation
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+
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+ ### πŸ›‘οΈ Error Handling
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+ - Comprehensive error reporting
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+ - Field validation and type checking
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+ - Bulk operation result tracking
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+ - Detailed logging for debugging
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+
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+ ## πŸš€ How to Use
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+
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+ ### 1. Connect to Salesforce
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+ 1. Navigate to the **πŸ” Connection** tab
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+ 2. Enter your Salesforce credentials:
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+ - **Username**: Your Salesforce email
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+ - **Password**: Your Salesforce password
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+ - **Security Token**: Get this from Salesforce Setup β†’ Personal Information β†’ Reset Security Token
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+ 3. Check "Sandbox Environment" if connecting to a sandbox
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+ 4. Click "πŸ”— Connect to Salesforce"
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+
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+ ### 2. Upload Data
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+ 1. Go to the **πŸ“€ Upload Data** tab (appears after successful connection)
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+ 2. Upload your CSV or Excel file
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+ 3. Select the target Salesforce object
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+ 4. Choose operation type:
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+ - **Insert**: For new records
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+ - **Update**: For existing records (requires record IDs)
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+ - **Upsert**: For insert/update based on external ID
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+ 5. Click "πŸ“€ Upload Data"
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+ 6. Download the results file to see detailed operation results
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+
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+ ### 3. Export Data
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+ 1. Go to the **πŸ“₯ Export Data** tab
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+ 2. Select the Salesforce object to export
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+ 3. Choose specific fields or leave empty for default fields
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+ 4. Set the record limit (max 10,000)
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+ 5. Click "πŸ“₯ Export Data"
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+ 6. Download the exported CSV file
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+
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+ ## πŸ“‹ Supported Salesforce Objects
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+
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+ - **Account** - Companies and organizations
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+ - **Contact** - Individual people
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+ - **Lead** - Potential customers
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+ - **Opportunity** - Sales deals
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+ - **Case** - Customer service cases
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+ - **Campaign** - Marketing campaigns
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+ - **User** - Salesforce users
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+ - **Product2** - Products and services
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+
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+ *Note: The application automatically detects which objects you have access to based on your Salesforce permissions.*
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+
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+ ## πŸ”§ Technical Requirements
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+
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+ ### For Users
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+ - Valid Salesforce credentials (username, password, security token)
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+ - CSV or Excel files for data upload
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+ - Modern web browser
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+
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+ ### For Developers
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+ - Python 3.8+
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+ - Required packages (see requirements.txt):
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+ - gradio==4.44.0
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+ - simple-salesforce==1.12.6
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+ - pandas==2.1.4
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+ - openpyxl==3.1.2
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+ - xlsxwriter==3.1.9
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+ - python-dotenv==1.0.0
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+ - requests==2.31.0
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+ - numpy==1.24.3
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+
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+ ## πŸ”’ Security & Privacy
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+
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+ - **No Data Storage**: Your Salesforce credentials and data are not stored on our servers
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+ - **Secure Connections**: All API calls use HTTPS encryption
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+ - **Session-Based**: Connections are only maintained during your browser session
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+ - **Local Processing**: File processing happens in real-time without permanent storage
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+
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+ ## 🚨 Important Notes
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+
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+ 1. **Security Token**: If you've never used the security token, reset it in Salesforce Setup
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+ 2. **API Limits**: Be mindful of your Salesforce API call limits
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+ 3. **Field Mapping**: Ensure your CSV/Excel column names match Salesforce field names
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+ 4. **Required Fields**: Make sure all required Salesforce fields are included in your data
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+ 5. **Data Validation**: Review your data before upload to avoid errors
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+
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+ ## πŸ› οΈ Local Development
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+
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+ To run this application locally:
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+
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+ ```bash
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+ # Clone the repository
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+ git clone <your-repo-url>
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+ cd salesforce-data-loader
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+
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+ # Install dependencies
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+ pip install -r requirements.txt
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+
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+ # Run the application
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+ python app.py
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+ ```
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+
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+ The application will be available at `http://localhost:7860`
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+
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+ ## 🀝 Contributing
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+
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+ Contributions are welcome! Please feel free to submit a Pull Request.
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+
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+ ## πŸ“„ License
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+
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+ This project is licensed under the MIT License - see the LICENSE file for details.
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+
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+ ## πŸ†˜ Support
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+
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+ If you encounter any issues:
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+ 1. Check your Salesforce credentials and permissions
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+ 2. Verify your security token is current
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+ 3. Ensure your data format matches Salesforce field requirements
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+ 4. Review the error messages in the results download
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+
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+ ---
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+
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+ **Built with ❀️ using Gradio and Simple-Salesforce**