Loading Data from X
to Dremio
Using dlt
in Python
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Loading data from X
, commonly referred to by its former name Twitter, to Dremio
using the open-source Python library dlt
is straightforward. The X
API allows programmatic access to core elements like Posts, Direct Messages, Spaces, Lists, users, and more. Dremio
offers a data lakehouse solution that provides flexibility, scalability, and performance, making it ideal for various stages of the data journey. By leveraging dlt
, you can efficiently extract data from X
and load it into Dremio
, ensuring seamless integration and robust data handling. For more information on the X
API, visit X.com.
dlt
Key Features
- Scalability via iterators, chunking, and parallelization:
dlt
offers scalable data extraction by leveraging iterators, chunking, and parallelization techniques. Read more - Implicit extraction DAGs: Automatically handles dependencies between data sources and transformations, ensuring data consistency and integrity. Read more
- Pipeline Metadata: Leverages metadata to provide governance capabilities, including load IDs for tracking data loads and facilitating data lineage. Read more
- Schema Enforcement and Curation: Ensures data consistency and quality by enforcing and curating schemas. Read more
- Schema Evolution: Alerts users to schema changes, allowing necessary actions to maintain data integrity. Read more
Getting started with your pipeline locally
dlt-init-openapi
0. Prerequisites
dlt
and dlt-init-openapi
requires Python 3.9 or higher. Additionally, you need to have the pip
package manager installed, and we recommend using a virtual environment to manage your dependencies. You can learn more about preparing your computer for dlt in our installation reference.
1. Install dlt and dlt-init-openapi
First you need to install the dlt-init-openapi
cli tool.
pip install dlt-init-openapi
The dlt-init-openapi
cli is a powerful generator which you can use to turn any OpenAPI spec into a dlt
source to ingest data from that api. The quality of the generator source is dependent on how well the API is designed and how accurate the OpenAPI spec you are using is. You may need to make tweaks to the generated code, you can learn more about this here.
# generate pipeline
# NOTE: add_limit adds a global limit, you can remove this later
# NOTE: you will need to select which endpoints to render, you
# can just hit Enter and all will be rendered.
dlt-init-openapi x --url https://raw.githubusercontent.com/dlt-hub/openapi-specs/main/open_api_specs/Business/twitter.yaml --global-limit 2
cd x_pipeline
# install generated requirements
pip install -r requirements.txt
The last command will install the required dependencies for your pipeline. The dependencies are listed in the requirements.txt
:
dlt>=0.4.12
You now have the following folder structure in your project:
x_pipeline/
├── .dlt/
│ ├── config.toml # configs for your pipeline
│ └── secrets.toml # secrets for your pipeline
├── rest_api/ # The rest api verified source
│ └── ...
├── x/
│ └── __init__.py # TODO: possibly tweak this file
├── x_pipeline.py # your main pipeline script