How to load data from Pexels API to Clickhouse

Learn how to use Airbyte to synchronize your Pexels API data into Clickhouse within minutes.

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Pexels API connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Clickhouse for your extracted Pexels API data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Pexels API to Clickhouse in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
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How to Sync to Manually

Step 1: Set Up Your Environment

Start by setting up a development environment. Ensure you have Python installed, as it will be used to interact with the Pexels API and ClickHouse. Install necessary packages such as `requests` for API calls and `clickhouse_driver` for interfacing with ClickHouse.

Register for an API key on the Pexels website. This key is necessary for authenticating your requests to the Pexels API. Store this key securely in your environment variables or a configuration file.

Use Python and the `requests` library to send HTTP GET requests to the Pexels API endpoint. Construct the request URL using your API key and any required parameters, such as search queries or filters. Parse the JSON response to extract the data you need.

Format the fetched data into a structure that matches your ClickHouse database schema. This may involve selecting specific fields, converting data types, and preparing the data in a tabular format such as CSV or JSON, which is compatible with ClickHouse.

Ensure your ClickHouse server is installed and running. Use the `clickhouse-client` command-line tool or `clickhouse_driver` Python module to create a database and table that will store the Pexels data. Define the table schema according to the data structure you prepared in the previous step.

Use the `clickhouse_driver` Python module to establish a connection to your ClickHouse server. Prepare an `INSERT` statement to load the prepared data into the ClickHouse table. Execute this statement using a batch insert method to efficiently load large datasets.

Once the data is loaded, run a series of `SELECT` queries using either the `clickhouse-client` or the Python module to verify that the data has been accurately transferred and is accessible in ClickHouse. Check for data integrity and completeness to ensure successful integration.

By following these steps, you can efficiently transfer data from the Pexels API to a ClickHouse warehouse without relying on third-party connectors or integrations.