--- headline: Export by SDK, REST, and UI | Opik Documentation og:description: Learn to export traces and spans using Opik SDK, REST, and UI for enhanced model tuning and deeper analysis. og:site_name: Opik Documentation og:title: Export Data Efficiently with Opik title: Export by SDK, REST, and UI toc_max_heading_level: 4 canonical-url: https://www.comet.com/docs/opik/tracing/advanced/export-data --- When working with Opik, it is important to be able to export traces, spans, and threads so that you can use them to fine-tune your models or run deeper analysis. You can export the data you have logged to the Opik platform using: 1. Using the Opik SDK: You can use the Python SDK methods ([`Opik.search_traces`](https://www.comet.com/docs/opik/python-sdk-reference/Opik.html#opik.Opik.search_traces), [`Opik.search_spans`](https://www.comet.com/docs/opik/python-sdk-reference/Opik.html#opik.Opik.search_spans), and [`Opik.search_threads`](https://www.comet.com/docs/opik/python-sdk-reference/Opik.html#opik.Opik.search_threads)) or the TypeScript SDK method (`client.searchTraces()`) to export traces, spans, and threads. 2. Using the Opik REST API: You can use the [`/traces`](/reference/rest-api/traces/get-traces-by-project) and [`/spans`](/reference/rest-api/spans/get-spans-by-project) endpoints to export traces and spans. 3. Using the UI: Once you have selected the traces or spans you want to export, you can click on the `Export CSV` button in the `Actions` dropdown. The recommended way to export data is to use the SDK methods in the Opik Python SDK ([`Opik.search_traces`](https://www.comet.com/docs/opik/python-sdk-reference/Opik.html#opik.Opik.search_traces), [`Opik.search_spans`](https://www.comet.com/docs/opik/python-sdk-reference/Opik.html#opik.Opik.search_spans), and [`Opik.search_threads`](https://www.comet.com/docs/opik/python-sdk-reference/Opik.html#opik.Opik.search_threads)) or TypeScript SDK (`client.searchTraces()`). ## Using the Opik SDK ### Exporting traces The Python SDK [`Opik.search_traces`](https://www.comet.com/docs/opik/python-sdk-reference/Opik.html#opik.Opik.search_traces) method and TypeScript SDK `client.searchTraces()` method allow you to both export all the traces in a project or search for specific traces and export them. #### Exporting all traces To export all traces, you will need to specify a `max_results` / `maxResults` value that is higher than the total number of traces in your project: ```python import opik client = opik.Opik() traces = client.search_traces(project_name="Default project", max_results=1000000) ``` ```typescript import { Opik } from "opik"; const client = new Opik(); const traces = await client.searchTraces({ projectName: "Default project", maxResults: 1000000 }); ``` #### Search for specific traces You can use the `filter_string` (Python) / `filterString` (TypeScript) parameter to search for specific traces: ```python import opik client = opik.Opik() traces = client.search_traces( project_name="Default project", filter_string='input contains "Opik"' ) # Convert to Dict if required traces = [trace.dict() for trace in traces] ``` ```typescript import { Opik } from "opik"; const client = new Opik(); const traces = await client.searchTraces({ projectName: "Default project", filterString: 'input contains "Opik"' }); ``` ### Filtering with Opik Query Language (OQL) All search methods (`search_traces`, `search_spans`, and `search_threads`) accept a `filter_string` (Python) / `filterString` (TypeScript) parameter that uses Opik Query Language (OQL): ``` " [AND ]*" ``` **Rules:** - String values must be wrapped in double quotes - Multiple conditions can be combined with `AND` (OR is not supported) - DateTime fields require ISO 8601 format (e.g., `"2024-01-01T00:00:00Z"`) - Use dot notation for nested fields: `metadata.model`, `feedback_scores.accuracy` Each entity type supports a different set of filter columns. The tables below list the available columns for each. #### Trace columns | Column | Type | Operators | | ------------------------- | ---------- | --------------------------------------------------------------------------- | | `id` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `name` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `input`, `output` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `thread_id` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `guardrails` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `experiment_id` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `start_time`, `end_time` | DateTime | `=`, `!=`, `>`, `>=`, `<`, `<=` | | `created_at`, `last_updated_at` | DateTime | `=`, `!=`, `>`, `>=`, `<`, `<=` | | `metadata` | Dictionary | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `>=`, `<`, `<=` | | `input_json`, `output_json` | Dictionary | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `>=`, `<`, `<=` | | `feedback_scores` | Numeric | `=`, `!=`, `>`, `>=`, `<`, `<=`, `is_empty`, `is_not_empty` | | `span_feedback_scores` | Numeric | `=`, `!=`, `>`, `>=`, `<`, `<=`, `is_empty`, `is_not_empty` | | `tags` | List | `=`, `!=`, `contains`, `not_contains`, `is_empty`, `is_not_empty` | | `annotation_queue_ids` | List | `=`, `!=`, `contains`, `not_contains`, `is_empty`, `is_not_empty` | | `usage.total_tokens`, `usage.prompt_tokens`, `usage.completion_tokens` | Numeric | `=`, `!=`, `>`, `>=`, `<`, `<=` | | `duration`, `total_estimated_cost`, `llm_span_count` | Numeric | `=`, `!=`, `>`, `>=`, `<`, `<=` | | `error_info` | Container | `is_empty`, `is_not_empty` | #### Span columns | Column | Type | Operators | | ------------------------- | ---------- | --------------------------------------------------------------------------- | | `id` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `name` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `input`, `output` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `model` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `provider` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `trace_id` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `type` | Enum | `=`, `!=` | | `start_time`, `end_time` | DateTime | `=`, `!=`, `>`, `>=`, `<`, `<=` | | `metadata` | Dictionary | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `>=`, `<`, `<=` | | `input_json`, `output_json` | Dictionary | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `>=`, `<`, `<=` | | `feedback_scores` | Numeric | `=`, `!=`, `>`, `>=`, `<`, `<=`, `is_empty`, `is_not_empty` | | `tags` | List | `=`, `!=`, `contains`, `not_contains`, `is_empty`, `is_not_empty` | | `usage.total_tokens`, `usage.prompt_tokens`, `usage.completion_tokens` | Numeric | `=`, `!=`, `>`, `>=`, `<`, `<=` | | `duration`, `total_estimated_cost` | Numeric | `=`, `!=`, `>`, `>=`, `<`, `<=` | | `error_info` | Container | `is_empty`, `is_not_empty` | #### Thread columns | Column | Type | Operators | | ------------------------- | ---------- | --------------------------------------------------------------------------- | | `id` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `first_message`, `last_message` | String | `=`, `!=`, `contains`, `not_contains`, `starts_with`, `ends_with`, `>`, `<` | | `status` | Enum | `=`, `!=` | | `start_time`, `end_time` | DateTime | `=`, `!=`, `>`, `>=`, `<`, `<=` | | `created_at`, `last_updated_at` | DateTime | `=`, `!=`, `>`, `>=`, `<`, `<=` | | `feedback_scores` | Numeric | `=`, `!=`, `>`, `>=`, `<`, `<=`, `is_empty`, `is_not_empty` | | `tags` | List | `=`, `!=`, `contains`, `not_contains`, `is_empty`, `is_not_empty` | | `annotation_queue_ids` | List | `=`, `!=`, `contains`, `not_contains`, `is_empty`, `is_not_empty` | | `duration`, `number_of_messages` | Numeric | `=`, `!=`, `>`, `>=`, `<`, `<=` | ```python import opik client = opik.Opik(project_name="Default project") # Trace filters traces = client.search_traces(filter_string='input contains "Opik"') traces = client.search_traces(filter_string='start_time >= "2024-01-01T00:00:00Z"') traces = client.search_traces(filter_string='usage.total_tokens > 1000') traces = client.search_traces(filter_string='metadata.model = "gpt-4o"') traces = client.search_traces(filter_string='feedback_scores.user_rating is_not_empty') traces = client.search_traces(filter_string='tags contains "production"') # Thread filters threads = client.search_threads(filter_string='number_of_messages >= 5') threads = client.search_threads(filter_string='first_message contains "hello"') threads = client.search_threads(filter_string='status = "active"') ``` ```typescript import { Opik } from "opik"; const client = new Opik({ projectName: "Default project" }); // Trace filters const t1 = await client.searchTraces({ filterString: 'input contains "Opik"' }); const t2 = await client.searchTraces({ filterString: 'start_time >= "2024-01-01T00:00:00Z"' }); const t3 = await client.searchTraces({ filterString: 'usage.total_tokens > 1000' }); const t4 = await client.searchTraces({ filterString: 'metadata.model = "gpt-4o"' }); const t5 = await client.searchTraces({ filterString: 'feedback_scores.user_rating is_not_empty' }); const t6 = await client.searchTraces({ filterString: 'tags contains "production"' }); ``` If your `feedback_scores` key contains spaces, you will need to wrap it in double quotes: `'feedback_scores."My Score" > 0'` If the `feedback_scores` key contains both spaces and double quotes, you will need to escape the double quotes as `""`: `'feedback_scores."Score ""with"" Quotes" > 0'` or by using different quotes, surrounding in triple-quotes, like this: `'''feedback_scores.'Accuracy "Happy Index"' < 0.8'''` ### Exporting spans You can export spans using the [`Opik.search_spans`](https://www.comet.com/docs/opik/python-sdk-reference/Opik.html#opik.Opik.search_spans) method. This method allows you to search for spans based on `trace_id` or based on a filter string. #### Exporting spans based on `trace_id` To export all the spans associated with a specific trace, you can use the `trace_id` parameter: ```python import opik client = opik.Opik() spans = client.search_spans( project_name="Default project", trace_id="067092dc-e639-73ff-8000-e1c40172450f" ) ``` #### Search for specific spans You can use the `filter_string` parameter to search for specific spans: ```python import opik client = opik.Opik() spans = client.search_spans( project_name="Default project", filter_string='input contains "Opik"' ) ``` ### Exporting threads You can export threads using the [`Opik.search_threads`](https://www.comet.com/docs/opik/python-sdk-reference/Opik.html#opik.Opik.search_threads) method. This method allows you to search for conversational threads in a project. #### Exporting all threads To export all threads, you will need to specify a `max_results` value that is higher than the total number of threads in your project: ```python import opik client = opik.Opik() threads = client.search_threads(project_name="Default project", max_results=1000000) ``` #### Search for specific threads You can use the `filter_string` parameter to search for specific threads: ```python import opik client = opik.Opik() # Search for a specific thread by ID threads = client.search_threads( project_name="Default project", filter_string='id = "thread_123"' ) # Search for threads with many messages threads = client.search_threads( project_name="Default project", filter_string='number_of_messages >= 5' ) # Search for threads with a specific feedback score threads = client.search_threads( project_name="Default project", filter_string='feedback_scores.user_satisfaction > 0.8' ) # Search for threads by tag threads = client.search_threads( project_name="Default project", filter_string='tags contains "important"' ) ``` ## Using the Opik REST API To export traces using the Opik REST API, you can use the [`/traces`](/reference/rest-api/traces/get-traces-by-project) endpoint and the [`/spans`](/reference/rest-api/spans/get-spans-by-project) endpoint. These endpoints are paginated so you will need to make multiple requests to retrieve all the traces or spans you want. To search for specific traces or spans, you can use the `filter` parameter. While this is a string parameter, it does not follow the same format as the `filter_string` parameter in the Opik SDK. Instead it is a list of json objects with the following format: ```json [ { "field": "name", "type": "string", "operator": "=", "value": "Opik" } ] ``` The `filter` parameter was designed to be used with the Opik UI and has therefore limited flexibility. If you need more flexibility, please raise an issue on [GitHub](https://github.com/comet-ml/opik/issues) so we can help. ## Using the UI To export traces as a CSV file from the UI, you can simply select the traces or spans you wish to export and click on `Export CSV` in the `Actions` dropdown: The UI only allows you to export up to 100 traces or spans at a time as it is linked to the page size of the traces table. If you need to export more traces or spans, we recommend using the Opik SDK.