Load GitLab
Data to BigQuery
with dlt
in Python
Join our Slack community or book a call with our support engineer Violetta.
This documentation provides a guide on loading data from GitLab
to BigQuery
using the open-source Python library dlt
. GitLab
is a web-based DevOps lifecycle tool that offers a Git repository manager with wiki, issue-tracking, and CI/CD pipeline features. BigQuery
is a serverless, cost-effective enterprise data warehouse that scales with your data and works across clouds. This guide will walk you through the steps to efficiently transfer your GitLab
data to BigQuery
using dlt
. For more information about GitLab
, visit here.
dlt
Key Features
- Automated Maintenance:
dlt
offers schema inference, evolution, and alerts, simplifying maintenance with short declarative code. Learn more - Run Anywhere Python Runs: Deploy on Airflow, serverless functions, or notebooks without external APIs, backends, or containers. Learn more
- User-Friendly Interface: A declarative interface that lowers the barrier for beginners while empowering experienced professionals. Learn more
- Governance Support: Utilize pipeline metadata, schema enforcement, and schema change alerts for better data management and compliance. Learn more
- Flexible Scaling and Fine-Tuning: Scale pipelines with parallel execution and fine-tune memory buffers, intermediary file sizes, and compression options. Learn 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 gitlab --url https://raw.githubusercontent.com/dlt-hub/openapi-specs/main/open_api_specs/Public/gitlab.yaml --global-limit 2
cd gitlab_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:
gitlab_pipeline/
├── .dlt/
│ ├── config.toml # configs for your pipeline
│ └── secrets.toml # secrets for your pipeline
├── rest_api/ # The rest api verified source
│ └── ...
├── gitlab/
│ └── __init__.py # TODO: possibly tweak this file
├── gitlab_pipeline.py # your main pipeline script
├── requirements.txt # dependencies for your pipeline
└── .gitignore # ignore files for git (not required)
1.1. Tweak gitlab/__init__.py
This file contains the generated configuration of your rest_api. You can continue with the next steps and leave it as is, but you might want to come back here and make adjustments if you need your rest_api
source set up in a different way. The generated file for the gitlab source will look like this:
Click to view full file (579 lines)
from typing import List
import dlt
from dlt.extract.source import DltResource
from rest_api import rest_api_source
from rest_api.typing import RESTAPIConfig
@dlt.source(name="gitlab_source", max_table_nesting=2)
def gitlab_source(
api_key: str = dlt.secrets.value,
base_url: str = dlt.config.value,
) -> List[DltResource]:
# source configuration
source_config: RESTAPIConfig = {
"client": {
"base_url": base_url,
"auth": {
"type": "api_key",
"api_key": api_key,
"name": "Private-Token",
"location": "header"
},
"paginator": {
"type":
"page_number",
"page_param":
"page",
"total_path":
"",
"maximum_page":
20,
},
},
"resources":
[
# Get the current appearance
{
"name": "get_api_v4_application_appearance",
"table_name": "api_entities_appearance",
"endpoint": {
"data_selector": "$",
"path": "/application/appearance",
}
},
# List all registered applications
{
"name": "get_api_v4_applications",
"table_name": "api_entities_application",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/applications",
}
},
# Return avatar url for a user
{
"name": "get_api_v4_avatar",
"table_name": "api_entities_avatar",
"endpoint": {
"data_selector": "$",
"path": "/avatar",
"params": {
"email": "FILL_ME_IN", # TODO: fill in required query parameter
# the parameters below can optionally be configured
# "size": "OPTIONAL_CONFIG",
},
}
},
# This feature was introduced in GitLab 10.6.
{
"name": "get_api_v4_groups_id_badges_badge_id",
"table_name": "api_entities_badge",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/groups/{id}/badges/{badge_id}",
"params": {
"badge_id": {
"type": "resolve",
"resource": "get_api_v4_groups_id_badges",
"field": "id",
},
"id": "FILL_ME_IN", # TODO: fill in required path parameter
},
}
},
# This feature was introduced in GitLab 10.6.
{
"name": "get_api_v4_groups_id_badges",
"table_name": "api_entities_badge",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/groups/{id}/badges",
"params": {
"id": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "per_page": "20",
# "name": "OPTIONAL_CONFIG",
},
}
},
# This feature was introduced in GitLab 10.6.
{
"name": "get_api_v4_projects_id_badges_badge_id",
"table_name": "api_entities_badge",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/projects/{id}/badges/{badge_id}",
"params": {
"badge_id": {
"type": "resolve",
"resource": "get_api_v4_projects_id_badges",
"field": "id",
},
"id": "FILL_ME_IN", # TODO: fill in required path parameter
},
}
},
# This feature was introduced in GitLab 10.6.
{
"name": "get_api_v4_projects_id_badges",
"table_name": "api_entities_badge",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/projects/{id}/badges",
"params": {
"id": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "per_page": "20",
# "name": "OPTIONAL_CONFIG",
},
}
},
# This feature was introduced in GitLab 10.6.
{
"name": "get_api_v4_groups_id_badges_render",
"table_name": "api_entities_basic_badge_details",
"endpoint": {
"data_selector": "$",
"path": "/groups/{id}/badges/render",
"params": {
"id": {
"type": "resolve",
"resource": "get_api_v4_groups_id_badges",
"field": "id",
},
"link_url": "FILL_ME_IN", # TODO: fill in required query parameter
"image_url": "FILL_ME_IN", # TODO: fill in required query parameter
},
}
},
# This feature was introduced in GitLab 10.6.
{
"name": "get_api_v4_projects_id_badges_render",
"table_name": "api_entities_basic_badge_details",
"endpoint": {
"data_selector": "$",
"path": "/projects/{id}/badges/render",
"params": {
"id": {
"type": "resolve",
"resource": "get_api_v4_projects_id_badges",
"field": "id",
},
"link_url": "FILL_ME_IN", # TODO: fill in required query parameter
"image_url": "FILL_ME_IN", # TODO: fill in required query parameter
},
}
},
# Retrieve a batched background migration
{
"name": "get_api_v4_admin_batched_background_migrations_id",
"table_name": "api_entities_batched_background_migration",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/admin/batched_background_migrations/{id}",
"params": {
"id": {
"type": "resolve",
"resource": "get_api_v4_admin_batched_background_migrations",
"field": "id",
},
# the parameters below can optionally be configured
# "database": "main",
},
}
},
# Get the list of batched background migrations
{
"name": "get_api_v4_admin_batched_background_migrations",
"table_name": "api_entities_batched_background_migration",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/admin/batched_background_migrations",
"params": {
# the parameters below can optionally be configured
# "database": "main",
},
}
},
# Get a single repository branch
{
"name": "get_api_v4_projects_id_repository_branches_branch",
"table_name": "api_entities_branch",
"endpoint": {
"data_selector": "$",
"path": "/projects/{id}/repository/branches/{branch}",
"params": {
"id": "FILL_ME_IN", # TODO: fill in required path parameter
"branch": "FILL_ME_IN", # TODO: fill in required path parameter
},
}
},
# Get a project repository branches
{
"name": "get_api_v4_projects_id_repository_branches",
"table_name": "api_entities_branch",
"endpoint": {
"data_selector": "$",
"path": "/projects/{id}/repository/branches",
"params": {
"id": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "per_page": "20",
# "search": "OPTIONAL_CONFIG",
# "regex": "OPTIONAL_CONFIG",
# "sort": "OPTIONAL_CONFIG",
# "page_token": "OPTIONAL_CONFIG",
},
}
},
# This feature was introduced in GitLab 8.12.
{
"name": "get_api_v4_broadcast_messages_id",
"table_name": "api_entities_broadcast_message",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/broadcast_messages/{id}",
"params": {
"id": "FILL_ME_IN", # TODO: fill in required path parameter
},
}
},
# This feature was introduced in GitLab 8.12.
{
"name": "get_api_v4_broadcast_messages",
"table_name": "api_entities_broadcast_message",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/broadcast_messages",
"params": {
# the parameters below can optionally be configured
# "per_page": "20",
},
}
},
# This feature was introduced in GitLab 14.1.
{
"name": "get_api_v4_bulk_imports_import_id",
"table_name": "api_entities_bulk_import",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/bulk_imports/{import_id}",
"params": {
"import_id": {
"type": "resolve",
"resource": "get_api_v4_bulk_imports",
"field": "id",
},
},
}
},
# This feature was introduced in GitLab 14.1.
{
"name": "get_api_v4_bulk_imports",
"table_name": "api_entities_bulk_import",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/bulk_imports",
"params": {
# the parameters below can optionally be configured
# "per_page": "20",
# "sort": "desc",
# "status": "OPTIONAL_CONFIG",
},
}
},
# This feature was introduced in GitLab 14.1.
{
"name": "get_api_v4_bulk_imports_import_id_entities_entity_id",
"table_name": "api_entities_bulk_imports",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/bulk_imports/{import_id}/entities/{entity_id}",
"params": {
"entity_id": {
"type": "resolve",
"resource": "get_api_v4_bulk_imports_import_id_entities",
"field": "id",
},
"import_id": "FILL_ME_IN", # TODO: fill in required path parameter
},
}
},
# This feature was introduced in GitLab 14.1.
{
"name": "get_api_v4_bulk_imports_import_id_entities",
"table_name": "api_entities_bulk_imports",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/bulk_imports/{import_id}/entities",
"params": {
"import_id": {
"type": "resolve",
"resource": "get_api_v4_bulk_imports",
"field": "id",
},
# the parameters below can optionally be configured
# "status": "OPTIONAL_CONFIG",
# "per_page": "20",
},
}
},
# This feature was introduced in GitLab 14.1.
{
"name": "get_api_v4_bulk_imports_entities",
"table_name": "api_entities_bulk_imports",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/bulk_imports/entities",
"params": {
# the parameters below can optionally be configured
# "per_page": "20",
# "sort": "desc",
# "status": "OPTIONAL_CONFIG",
},
}
},
# Get the details of a specific instance-level variable
{
"name": "get_api_v4_admin_ci_variables_key",
"table_name": "api_entities_ci_variable",
"primary_key": "key",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/admin/ci/variables/{key}",
"params": {
"key": "FILL_ME_IN", # TODO: fill in required path parameter
},
}
},
# List all instance-level variables
{
"name": "get_api_v4_admin_ci_variables",
"table_name": "api_entities_ci_variable",
"endpoint": {
"data_selector": "$",
"path": "/admin/ci/variables",
"params": {
# the parameters below can optionally be configured
# "per_page": "20",
},
}
},
# This feature was introduced in GitLab 13.2. Returns a single instance cluster.
{
"name": "get_api_v4_admin_clusters_cluster_id",
"table_name": "api_entities_cluster",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/admin/clusters/{cluster_id}",
"params": {
"cluster_id": {
"type": "resolve",
"resource": "get_api_v4_admin_clusters",
"field": "id",
},
},
}
},
# This feature was introduced in GitLab 13.2. Returns a list of instance clusters.
{
"name": "get_api_v4_admin_clusters",
"table_name": "api_entities_cluster",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/admin/clusters",
}
},
# This feature was introduced in GitLab 8.11.
{
"name": "get_api_v4_groups_id_access_requests",
"table_name": "api_entities_custom_attribute",
"endpoint": {
"data_selector": "custom_attributes",
"path": "/groups/{id}/access_requests",
"params": {
"id": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "per_page": "20",
},
}
},
# This feature was introduced in GitLab 8.11.
{
"name": "get_api_v4_projects_id_access_requests",
"table_name": "api_entities_custom_attribute",
"endpoint": {
"data_selector": "custom_attributes",
"path": "/projects/{id}/access_requests",
"params": {
"id": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "per_page": "20",
},
}
},
# Retrieve dictionary details
{
"name": "get_api_v4_admin_databases_database_name_dictionary_tables_table_name",
"table_name": "api_entities_dictionary_table",
"primary_key": "table_name",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/admin/databases/{database_name}/dictionary/tables/{table_name}",
"params": {
"database_name": "FILL_ME_IN", # TODO: fill in required path parameter
"table_name": "FILL_ME_IN", # TODO: fill in required path parameter
},
}
},
{
"name": "list_project_jobs",
"table_name": "api_entities_job",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/projects/{id}/jobs",
"params": {
"id": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "scope": "OPTIONAL_CONFIG",
},
}
},
{
"name": "get_single_job",
"table_name": "api_entities_job",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/projects/{id}/jobs/{job_id}",
"params": {
"job_id": {
"type": "resolve",
"resource": "list_project_jobs",
"field": "id",
},
"id": "FILL_ME_IN", # TODO: fill in required path parameter
},
}
},
# This feature was introduced in GitLab 15.2.
{
"name": "get_api_v4_metadata",
"table_name": "api_entities_metadata",
"endpoint": {
"data_selector": "$",
"path": "/metadata",
}
},
# This feature was introduced in GitLab 8.13 and deprecated in 15.5. We recommend you instead use the Metadata API.
{
"name": "get_api_v4_version",
"table_name": "api_entities_metadata",
"endpoint": {
"data_selector": "$",
"path": "/version",
}
},
# Metric Images for alert
{
"name": "get_api_v4_projects_id_alert_management_alerts_alert_iid_metric_images",
"table_name": "api_entities_metric_image",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/projects/{id}/alert_management_alerts/{alert_iid}/metric_images",
"params": {
"id": "FILL_ME_IN", # TODO: fill in required path parameter
"alert_iid": "FILL_ME_IN", # TODO: fill in required path parameter
},
}
},
# List the current limits of a plan on the GitLab instance.
{
"name": "get_api_v4_application_plan_limits",
"table_name": "api_entities_plan_limit",
"endpoint": {
"data_selector": "$",
"path": "/application/plan_limits",
"params": {
# the parameters below can optionally be configured
# "plan_name": "default",
},
}
},
]
}
return rest_api_source(source_config)
2. Configuring your source and destination credentials
dlt-init-openapi
will try to detect which authentication mechanism (if any) is used by the API in question and add a placeholder in your secrets.toml
.
The dlt
cli will have created a .dlt
directory in your project folder. This directory contains a config.toml
file and a secrets.toml
file that you can use to configure your pipeline. The automatically created version of these files look like this:
generated config.toml
[runtime]
log_level="INFO"
[sources.gitlab]
# Base URL for the API
base_url = "https://www.gitlab.com/api/v4"
generated secrets.toml
[sources.gitlab]
# secrets for your gitlab source
api_key = "FILL ME OUT" # TODO: fill in your credentials
2.1. Adjust the generated code to your usecase
At this time, the dlt-init-openapi
cli tool will always create pipelines that load to a local duckdb
instance. Switching to a different destination is trivial, all you need to do is change the destination
parameter in gitlab_pipeline.py
to bigquery and supply the credentials as outlined in the destination doc linked below.
3. Running your pipeline for the first time
The dlt
cli has also created a main pipeline script for you at gitlab_pipeline.py
, as well as a folder gitlab
that contains additional python files for your source. These files are your local copies which you can modify to fit your needs. In some cases you may find that you only need to do small changes to your pipelines or add some configurations, in other cases these files can serve as a working starting point for your code, but will need to be adjusted to do what you need them to do.
The main pipeline script will look something like this:
import dlt
from gitlab import gitlab_source
if __name__ == "__main__":
pipeline = dlt.pipeline(
pipeline_name="gitlab_pipeline",
destination='duckdb',
dataset_name="gitlab_data",
progress="log",
export_schema_path="schemas/export"
)
source = gitlab_source()
info = pipeline.run(source)
print(info)
Provided you have set up your credentials, you can run your pipeline like a regular python script with the following command:
python gitlab_pipeline.py
4. Inspecting your load result
You can now inspect the state of your pipeline with the dlt
cli:
dlt pipeline gitlab_pipeline info
You can also use streamlit to inspect the contents of your BigQuery
destination for this:
# install streamlit
pip install streamlit
# run the streamlit app for your pipeline with the dlt cli:
dlt pipeline gitlab_pipeline show
5. Next steps to get your pipeline running in production
One of the beauties of dlt
is, that we are just a plain Python library, so you can run your pipeline in any environment that supports Python >= 3.8. We have a couple of helpers and guides in our docs to get you there:
The Deploy section will show you how to deploy your pipeline to
- Deploy with GitHub Actions: Utilize GitHub Actions for CI/CD to deploy your
dlt
pipelines. Learn more here. - Deploy with Airflow and Google Composer: Integrate
dlt
with Airflow and Google Composer for managed workflows. Find detailed instructions here. - Deploy with Google Cloud Functions: Use Google Cloud Functions to deploy serverless
dlt
pipelines. Explore the guide here. - More Deployment Options: Discover various other methods to deploy your
dlt
pipelines here.
The running in production section will teach you about:
- How to Monitor your pipeline: Learn how to effectively monitor your
dlt
pipeline in production to ensure smooth operation and quick identification of issues. How to Monitor your pipeline - Set up alerts: Set up alerts to get notified of any issues or anomalies in your
dlt
pipeline, ensuring timely intervention and resolution. Set up alerts - Set up tracing: Implement tracing to gain detailed insights into the execution of your
dlt
pipeline, helping you understand performance and troubleshoot problems. And set up tracing
Available Sources and Resources
For this verified source the following sources and resources are available
Source GitLab
Loads various GitLab API data including badges, clusters, jobs, and metadata.
Resource Name | Write Disposition | Description |
---|---|---|
api_entities_badge | append | Represents badges associated with GitLab entities. |
api_entities_basic_badge_details | append | Contains basic details about badges in GitLab. |
api_entities_batched_background_migration | append | Information about batched background migrations. |
api_entities_cluster | append | Details about clusters in GitLab. |
api_entities_dictionary_table | append | Represents dictionary tables used in GitLab. |
api_entities_metric_image | append | Stores metric images used in GitLab. |
api_entities_broadcast_message | append | Broadcast messages sent within GitLab. |
api_entities_avatar | append | Information about avatars in GitLab. |
api_entities_plan_limit | append | Limits associated with different plans in GitLab. |
api_entities_custom_attribute | append | Custom attributes assigned to GitLab entities. |
api_entities_job | append | Details about jobs executed in GitLab CI/CD pipelines. |
api_entities_metadata | append | Metadata related to various GitLab entities. |
api_entities_application | append | Information about applications integrated with GitLab. |
api_entities_branch | append | Details about branches in Git repositories managed by GitLab. |
api_entities_appearance | append | Appearance settings and customizations in GitLab. |
api_entities_bulk_imports | append | Information about bulk imports executed in GitLab. |
api_entities_ci_variable | append | CI/CD variables used in GitLab pipelines. |
api_entities_bulk_import | append | Details about individual bulk import operations in GitLab. |
Additional pipeline guides
- Load data from Cisco Meraki to Azure Cloud Storage in python with dlt
- Load data from IFTTT to Azure Synapse in python with dlt
- Load data from Chess.com to YugabyteDB in python with dlt
- Load data from Harvest to The Local Filesystem in python with dlt
- Load data from Adobe Analytics to Dremio in python with dlt
- Load data from Fivetran to Neon Serverless Postgres in python with dlt
- Load data from Rest API to YugabyteDB in python with dlt
- Load data from Harvest to AWS S3 in python with dlt
- Load data from MongoDB to Redshift in python with dlt
- Load data from Attio to BigQuery in python with dlt