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| title: Salesforce Data Loader | |
| emoji: 🚀 | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 4.20.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # 🚀 Salesforce Data Loader | |
| A powerful, user-friendly web application for uploading and downloading data from Salesforce. Built with Gradio and designed for easy bulk data operations. | |
| ## ✨ Features | |
| ### 🔐 Secure Authentication | |
| - Connect to Salesforce production or sandbox environments | |
| - Secure credential handling with username, password, and security token | |
| - Real-time connection status feedback | |
| ### 📤 Data Upload | |
| - **File Support**: Upload CSV and Excel files (.csv, .xlsx, .xls) | |
| - **Bulk Operations**: | |
| - **Insert**: Add new records | |
| - **Update**: Modify existing records | |
| - **Upsert**: Insert or update based on external ID | |
| - **Object Support**: Works with common Salesforce objects (Account, Contact, Lead, Opportunity, Case, etc.) | |
| - **Field Mapping**: Automatic field detection and validation | |
| - **Results Tracking**: Download detailed results with success/error reports | |
| ### 📥 Data Export | |
| - Export data from any accessible Salesforce object | |
| - Select specific fields to export | |
| - Configurable record limits (100-10,000 records) | |
| - Download as CSV format | |
| - SOQL query generation | |
| ### 🛡️ Error Handling | |
| - Comprehensive error reporting | |
| - Field validation and type checking | |
| - Bulk operation result tracking | |
| - Detailed logging for debugging | |
| ## 🚀 How to Use | |
| ### 1. Connect to Salesforce | |
| 1. Navigate to the **🔐 Connection** tab | |
| 2. Enter your Salesforce credentials: | |
| - **Username**: Your Salesforce email | |
| - **Password**: Your Salesforce password | |
| - **Security Token**: Get this from Salesforce Setup → Personal Information → Reset Security Token | |
| 3. Check "Sandbox Environment" if connecting to a sandbox | |
| 4. Click "🔗 Connect to Salesforce" | |
| ### 2. Upload Data | |
| 1. Go to the **📤 Upload Data** tab (appears after successful connection) | |
| 2. Upload your CSV or Excel file | |
| 3. Select the target Salesforce object | |
| 4. Choose operation type: | |
| - **Insert**: For new records | |
| - **Update**: For existing records (requires record IDs) | |
| - **Upsert**: For insert/update based on external ID | |
| 5. Click "📤 Upload Data" | |
| 6. Download the results file to see detailed operation results | |
| ### 3. Export Data | |
| 1. Go to the **📥 Export Data** tab | |
| 2. Select the Salesforce object to export | |
| 3. Choose specific fields or leave empty for default fields | |
| 4. Set the record limit (max 10,000) | |
| 5. Click "📥 Export Data" | |
| 6. Download the exported CSV file | |
| ## 📋 Supported Salesforce Objects | |
| - **Account** - Companies and organizations | |
| - **Contact** - Individual people | |
| - **Lead** - Potential customers | |
| - **Opportunity** - Sales deals | |
| - **Case** - Customer service cases | |
| - **Campaign** - Marketing campaigns | |
| - **User** - Salesforce users | |
| - **Product2** - Products and services | |
| *Note: The application automatically detects which objects you have access to based on your Salesforce permissions.* | |
| ## 🔧 Technical Requirements | |
| ### For Users | |
| - Valid Salesforce credentials (username, password, security token) | |
| - CSV or Excel files for data upload | |
| - Modern web browser | |
| ### For Developers | |
| - Python 3.8+ | |
| - Required packages (see requirements.txt): | |
| - gradio==4.32.0 | |
| - simple-salesforce==1.12.6 | |
| - pandas==2.1.4 | |
| - openpyxl==3.1.2 | |
| - xlsxwriter==3.1.9 | |
| - python-dotenv==1.0.0 | |
| - requests==2.31.0 | |
| - numpy==1.24.3 | |
| ## 🔒 Security & Privacy | |
| - **No Data Storage**: Your Salesforce credentials and data are not stored on our servers | |
| - **Secure Connections**: All API calls use HTTPS encryption | |
| - **Session-Based**: Connections are only maintained during your browser session | |
| - **Local Processing**: File processing happens in real-time without permanent storage | |
| ## 🚨 Important Notes | |
| 1. **Security Token**: If you've never used the security token, reset it in Salesforce Setup | |
| 2. **API Limits**: Be mindful of your Salesforce API call limits | |
| 3. **Field Mapping**: Ensure your CSV/Excel column names match Salesforce field names | |
| 4. **Required Fields**: Make sure all required Salesforce fields are included in your data | |
| 5. **Data Validation**: Review your data before upload to avoid errors | |
| ## 🛠️ Local Development | |
| To run this application locally: | |
| ```bash | |
| # Clone the repository | |
| git clone <your-repo-url> | |
| cd salesforce-data-loader | |
| # Install dependencies | |
| pip install -r requirements.txt | |
| # Run the application | |
| python app.py | |
| ``` | |
| The application will be available at `http://localhost:7860` | |
| ## 🤝 Contributing | |
| Contributions are welcome! Please feel free to submit a Pull Request. | |
| ## 📄 License | |
| This project is licensed under the MIT License - see the LICENSE file for details. | |
| ## 🆘 Support | |
| If you encounter any issues: | |
| 1. Check your Salesforce credentials and permissions | |
| 2. Verify your security token is current | |
| 3. Ensure your data format matches Salesforce field requirements | |
| 4. Review the error messages in the results download | |
| --- | |
| **Built with ❤️ using Gradio and Simple-Salesforce** |