How to load data from Lokalise to Weaviate

Learn how to use Airbyte to synchronize your Lokalise data into Weaviate within minutes.

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Lokalise connector in Airbyte

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

Set up Weaviate for your extracted Lokalise 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 Lokalise to Weaviate 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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Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

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How to Sync to Manually

Step 1: Export Data from Lokalise

Begin by logging into your Lokalise account. Navigate to the project dashboard and select the project you wish to export data from. Use the export feature to download your data in a supported format such as CSV, JSON, or XLSX. Ensure you choose a format that is easiest for you to manipulate and compatible with your data processing tools.

Once you have your exported file, open it in a data manipulation tool like Excel or a text editor. Review the structure of the data to understand its format and contents. Identify any fields or data points that need modification or renaming to align with the schema requirements of Weaviate. This step is crucial for a smooth transformation process.

Weaviate uses JSON-LD as its data format. Use a scripting language like Python to write a script that converts your Lokalise data into JSON-LD. This involves mapping Lokalise fields to the appropriate JSON-LD structure and adding any necessary context. Ensure that your JSON-LD includes all required attributes for your Weaviate schema, such as class names and properties.

Before importing data into Weaviate, you need to set up a schema that defines the classes and properties your data will map to. Log into your Weaviate instance and access the schema management interface. Define classes and properties according to your data structure, ensuring alignment with the JSON-LD you prepared. This step ensures Weaviate can correctly interpret and store your data.

With your JSON-LD data and Weaviate schema prepared, you can now load the data into Weaviate. Use the Weaviate REST API to send POST requests that upload your JSON-LD data. Ensure you handle authentication correctly and verify that your requests are formatted according to Weaviate’s API documentation. Check for successful responses to confirm data import.

After importing your data, it's crucial to verify that it was correctly integrated into Weaviate. Use the Weaviate console or API to query your data classes and properties. Check for consistency and accuracy against your original Lokalise data. This step helps ensure that no data was lost or misrepresented during the transfer.

Establish a routine for maintaining and updating your data in Weaviate. This could involve setting up scripts to periodically extract and transform new Lokalise data, followed by importing it into Weaviate. Regular updates help keep your Weaviate database current and reliable, especially if your Lokalise data is frequently updated.