Libraries tagged by large-dataset

Export large datasets to a JSON file without memory exhaustion

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Fast export of large datasets to feeds for marketplaces and services

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# SendX REST API Documentation ## 🚀 Introduction The SendX API is organized around REST principles. Our API has predictable resource-oriented URLs, accepts JSON-encoded request bodies, returns JSON-encoded responses, and uses standard HTTP response codes, authentication, and verbs. **Key Features:** - 🔒 **Security**: Team-based authentication with optional member-level access - 🎯 **Resource-Oriented**: RESTful design with clear resource boundaries - 📊 **Rich Data Models**: Three-layer model system (Input/Output/Internal) - 🔗 **Relationships**: Automatic prefix handling for resource relationships - 📈 **Scalable**: Built for high-volume email marketing operations ## 🏗️ Architecture Overview SendX uses a three-layer model architecture: 1. **Input Models** (`RestE*`): For API requests 2. **Output Models** (`RestR*`): For API responses with prefixed IDs 3. **Internal Models**: Core business logic (not exposed in API) ## 🔐 Security & Authentication SendX uses API key authentication: ### Team API Key ```http X-Team-ApiKey: YOUR_TEAM_API_KEY ``` - **Required for all requests** - Team-level access to resources - Available in SendX Settings → Team API Key ## 🆔 Encrypted ID System SendX uses encrypted IDs for security and better developer experience: - **Internal IDs**: Sequential integers (not exposed) - **Encrypted IDs**: 22-character alphanumeric strings - **Prefixed IDs**: Resource-type prefixes in API responses (`contact_`) ### ID Format **All resource IDs follow this pattern:** ``` _ ``` **Example:** ```json { "id": "contact_BnKjkbBBS500CoBCP0oChQ", "lists": ["list_OcuxJHdiAvujmwQVJfd3ss", "list_0tOFLp5RgV7s3LNiHrjGYs"], "tags": ["tag_UhsDkjL772Qbj5lWtT62VK", "tag_fL7t9lsnZ9swvx2HrtQ9wM"] } ``` ## 📚 Resource Prefixes | Resource | Prefix | Example | |----------|--------|---------| | Contact | `contact_` | `contact_BnKjkbBBS500CoBCP0oChQ` | | Campaign | `campaign_` | `campaign_LUE9BTxmksSmqHWbh96zsn` | | List | `list_` | `list_OcuxJHdiAvujmwQVJfd3ss` | | Tag | `tag_` | `tag_UhsDkjL772Qbj5lWtT62VK` | | Sender | `sender_` | `sender_4vK3WFhMgvOwUNyaL4QxCD` | | Template | `template_` | `template_f3lJvTEhSjKGVb5Lwc5SWS` | | Custom Field | `field_` | `field_MnuqBAG2NPLm7PZMWbjQxt` | | Webhook | `webhook_` | `webhook_9l154iiXlZoPo7vngmamee` | | Post | `post_` | `post_XyZ123aBc456DeF789GhI` | | Post Category | `post_category_` | `post_category_YzS1wOU20yw87UUHKxMzwn` | | Post Tag | `post_tag_` | `post_tag_123XyZ456AbC` | | Member | `member_` | `member_JkL012MnO345PqR678` | ## 🎯 Best Practices ### Error Handling - **Always check status codes**: 2xx = success, 4xx = client error, 5xx = server error - **Read error messages**: Descriptive messages help debug issues - **Handle rate limits**: Respect API rate limits for optimal performance ### Data Validation - **Email format**: Must be valid email addresses - **Required fields**: Check documentation for mandatory fields - **Field lengths**: Respect maximum length constraints ### Performance - **Pagination**: Use offset/limit for large datasets - **Batch operations**: Process multiple items when supported - **Caching**: Cache responses when appropriate ## 🛠️ SDKs & Integration Official SDKs available for: - [Golang](https://github.com/sendx/sendx-go-sdk) - [Python](https://github.com/sendx/sendx-python-sdk) - [Ruby](https://github.com/sendx/sendx-ruby-sdk) - [Java](https://github.com/sendx/sendx-java-sdk) - [PHP](https://github.com/sendx/sendx-php-sdk) - [JavaScript](https://github.com/sendx/sendx-javascript-sdk) ## 📞 Support Need help? Contact us: - 💬 **Website Chat**: Available on sendx.io - 📧 **Email**: [email protected] - 📚 **Documentation**: Full guides at help.sendx.io --- **API Endpoint:** `https://api.sendx.io/api/v1/rest` [](https://god.gw.postman.com/run-collection/33476323-44b198b0-5219-4619-a01f-cfc24d573885?action=collection%2Ffork&source=rip_markdown&collection-url=entityId%3D33476323-44b198b0-5219-4619-a01f-cfc24d573885%26entityType%3Dcollection%26workspaceId%3D6b1e4f65-96a9-4136-9512-6266c852517e)

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PHP BigQuery for Laravel is a seamless integration package that allows you to harness the power of Google BigQuery in your Laravel applications effortlessly. With a zero-configuration setup, plug and play this library to perform high-speed querying and advanced analytics on large datasets.

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Scroller is a virtual rendering plug-in for DataTables which allows large datasets to be drawn on screen very quickly. Virtual rendering means is that only the visible portion of the table is drawn, while the scrolling container gives the visual impression that the whole table is visible, allowing excellent browser performance. This is Scroller for DataTables

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Scroller is a virtual rendering plug-in for DataTables which allows large datasets to be drawn on screen very quickly. Virtual rendering means is that only the visible portion of the table is drawn, while the scrolling container gives the visual impression that the whole table is visible, allowing excellent browser performance. This is Scroller for DataTables with styling for [DataTables](https://datatables.net/)

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Scroller is a virtual rendering plug-in for DataTables which allows large datasets to be drawn on screen very quickly. Virtual rendering means is that only the visible portion of the table is drawn, while the scrolling container gives the visual impression that the whole table is visible, allowing excellent browser performance. This is Scroller for DataTables with styling for [Bootstrap4](https://getbootstrap.com/docs/4.6/getting-started/introduction/)

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An asynchronous publishing hook for large datasets.

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A memory-efficient Laravel package for streaming Excel exports without holding data in memory

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A flexible and efficient library for exporting data to Excel (XLS, XLSX) with support for mappings, formatters, and handling large datasets. Working with less dependencies, avoid future breaks & conclusions.

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Iterate through large datasets

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Use Ajax in Dropdowns for large datasets

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Scroller is a virtual rendering plug-in for DataTables which allows large datasets to be drawn on screen very quickly. Virtual rendering means is that only the visible portion of the table is drawn, while the scrolling container gives the visual impression that the whole table is visible, allowing excellent browser performance. This is Scroller for DataTables with styling for [Bootstrap5](https://getbootstrap.com/)

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High-performance PHP library for memory-efficient processing of large datasets with streaming, batching, and time/space complexity optimization

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Simple but powerful PHP library to generate on-disk XLSX spreadsheets focused in low memory usage.

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