# Sending documents You'll first need to create a document import, then you'll be able to launch executions. ## Create a document import The first step if you want to use bulk imports is to create a document import. See this as creating a configuration for your imports of the same type. Creating a document import is done with a simple request to `POST /v1/datamarts//documents_imports`. Let's create a document import for user activities that we will call "My user activity document import". You will need to replace `` with your datamart id (which can be found in the UI in Settings > Datamart > Datamarts) and `` with your authentication token. ``` curl -X POST \ https://api.mediarithmics.com/v1/datamarts//document_imports \ -H 'Authorization: ' \ -H 'Content-Type: application/json' \ -d '{ "document_type": "USER_ACTIVITY", "mime_type": "APPLICATION_X_NDJSON", "encoding": "utf-8", "name": "My user activity document import" }' ``` Let's unpack this: * for `document_type` we have chosen `USER_ACTIVITY` in order to send user activities. Other valid values would be `USER_SEGMENT`, `USER_PROFILE`, `USER_IDENTIFIERS_ASSOCIATION_DECLARATIONS` * `mime_type` should match the type of format you will use for your data. Valid values are `APPLICATION_X_NDJSON` (if you will send data in a `NDJSON` format) or `TEXT_CSV` (if you format your data as comma-separated values). In the case of `USER_ACTIVITY`, only `NDJSON` is valid * `encoding` is the encoding of the data that will be imported * `name` is the name you want to give this document import See the ~~API documentation on this endpoint~~ or our guide on ~~document imports~~ for more information on the other types of document.If everything went well, the response should look something like this: ``` { "status": "ok", "data": { "id": "", "datafarm_key": "DF_EU_YYYY_MM", "datamart_id": "", "document_type": "USER_ACTIVITY", "mime_type": "APPLICATION_X_NDJSON", "encoding": "utf-8", "name": "My user activity document import", "priority": "MEDIUM" } } ``` Let's take note of provided the ``. ## Create a document import execution Once we have created our document import, we can start creating executions (i.e. actually sending data!). Let's send some store visits. First, we will prepare our `JSON` file: ``` { "$email_hash": { "$email": "some.email@dummy.com" }, "$type": "TOUCH", "$session_status": "NO_SESSION", "$ts": 1605262037783, "$events": [{ "$event_name": "store-visit", "$ts": 1605262037783, "$properties": {} }], "$location": { "$country": "france", "$city": "paris", "$zip_code": "75001" } } ``` Please check ~~our guide on user activity imports~~ for a complete explanation of all the properties in our payload. Now we will convert our `JSON` file to `NDJSON` and send in the body of the following request. If you want to learn more about the NDJSON format, check out [this site](http://ndjson.org/). ``` curl --location --request POST 'https://api.mediarithmics.com/v1/datamarts//document_imports//executions' \ --header 'Content-Type: application/x-ndjson' \ --header 'Authorization: ' \ --data-raw '{"$email_hash": {"$email": "some.email@dummy.com"},"$type": "TOUCH","$session_status": "NO_SESSION","$ts": 1605262037783,"$events": [{"$event_name": "store-visit","$ts": 1605262037783,"$properties": {}}],"$location": {"$country": "france","$city": "paris","$zip_code": "75001"}}' ``` You will need to replace `` with your datamart id, `` with the document import id you got in the previous request and `` with your authentication token. Please note that your `Content-Type` header must match the `mime_type` you set when creating the document import earlier. The response should look like this: ``` { "status": "ok", "data": { "parameters": null, "result": null, "error": null, "id": "", "status": "PENDING", "creation_date": 1605271495713, "start_date": null, "duration": null, "organisation_id": "", "user_id": null, "cancel_status": null, "debug": null, "is_retryable": false, "permalink_uri": "xxxxxx", "num_tasks": null, "completed_tasks": null, "erroneous_tasks": null, "retry_count": 0, "job_type": "DOCUMENT_IMPORT", "import_mode": "MANUAL_FILE", "import_type": null } } ``` Take note of the `` here, you will need it if you want to check the status of your execution. ## Checking your document import execution status You can check the status of your execution with this simple request: ``` curl --location --request GET 'https://api.mediarithmics.com/v1/datamarts//document_imports//executions/' \ --header 'Authorization: ' ``` The response should look like this: ``` { "status": "ok", "data": { "parameters": { "datamart_id": 1502, "document_import_id": 20517, "mime_type": "APPLICATION_X_NDJSON", "document_type": "USER_ACTIVITY", "input_file_name": "xxxxxx", "file_uri": "xxxxxx", "number_of_lines": 1, "segment_id": null }, "result": { "total_success": 1, "total_failure": 0, "input_file_name": "xxxxxx", "input_file_uri": "xxxxxx", "error_file_uri": "xxxxxx", "possible_issue_on_identifiers": false, "top_identifiers": {} }, "error": null, "id": "", "status": "PENDING", "creation_date": 1605627687764, "start_date": 1605627714053, "duration": 1065, "organisation_id": "", "user_id": null, "cancel_status": null, "debug": null, "is_retryable": false, "permalink_uri": "xxxxxxx", "num_tasks": 1, "completed_tasks": 1, "erroneous_tasks": 0, "retry_count": 0, "job_type": "DOCUMENT_IMPORT", "import_mode": "MANUAL_FILE", "import_type": null, "end_date": 1605627715118 } } ``` Notice the `PENDING` status: after a while, the execution will be processed and if you check again, status will be changed to `RUNNING` then to `SUCCEEDED`. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://developer.mediarithmics.io/resources/your-first-integration/make-the-first-bulk-import/send-documents-using-the-api/sending-documents.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.