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Load Data from GitLab to Google Cloud Storage using dlt in Python

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GitLab is a web-based DevOps lifecycle tool that offers a Git repository manager with wiki, issue-tracking, and CI/CD pipeline features, all under an open-source license. This documentation will guide you through the process of loading data from GitLab to Google Cloud Storage using the open-source Python library, dlt. Google Cloud Storage is a filesystem destination on the Google Cloud Platform, allowing for easy creation of data lakes. Data can be uploaded in formats such as JSONL, Parquet, or CSV. For further information about GitLab, visit here.

dlt Key Features

  • Pipeline Metadata: dlt pipelines leverage metadata to provide governance capabilities, including load IDs for tracking data loads and facilitating data lineage and traceability. Read more.
  • Schema Enforcement and Curation: dlt empowers users to enforce and curate schemas, ensuring data consistency and quality by defining the structure of normalized data. Read more.
  • Schema Evolution Alerts: dlt enables proactive governance by alerting users to schema changes, allowing stakeholders to review and validate changes. Read more.
  • Scaling and Finetuning: dlt offers several mechanisms and configuration options to scale up and finetune pipelines, such as running extraction, normalization, and load in parallel. Read more.
  • Advanced Features: dlt is a constantly growing library that supports many features and use cases needed by the community. Join our Slack to find recent releases or discuss what you can build with dlt. Read more.

Getting started with your pipeline locally

OpenAPI Source Generator dlt-init-openapi

This walkthrough makes use of the dlt-init-openapi generator cli tool. You can read more about it here. The code generated by this tool uses the dlt rest_api verified source, docs for this are here.

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

info

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.

  • If you know your API needs authentication, but none was detected, you can learn more about adding authentication to the rest_api here.
  • OAuth detection currently is not supported, but you can supply your own authentication mechanism as outlined here.

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

Further help setting up your source and destinations

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 filesystem and supply the credentials as outlined in the destination doc linked below.

  • Read more about setting up the rest_api source in our docs.
  • Read more about setting up the Google Cloud Storage destination in our docs.

The default filesystem destination is configured to connect to AWS S3. To load to Google Cloud Storage, update the [destination.filesystem.credentials] section in your secrets.toml.

[destination.filesystem.credentials]
client_email="Please set me up!"
private_key="Please set me up!"
project_id="Please set me up!"

By default, the filesystem destination will store your files as JSONL. You can tell your pipeline to choose a different format with the loader_file_format property that you can set directly on the pipeline or via your config.toml. Available values are jsonl, parquet and csv:

[pipeline] # in ./dlt/config.toml
loader_file_format="parquet"

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 Google Cloud Storage 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: Learn how to deploy a pipeline using GitHub Actions for CI/CD. Follow the guide here.
  • Deploy with Airflow and Google Composer: Step-by-step instructions to deploy a pipeline with Airflow and Google Composer. Check the details here.
  • Deploy with Google Cloud Functions: Explore how to deploy a pipeline using Google Cloud Functions. Find the guide here.
  • More deployment options: Discover various other ways to deploy your dlt pipelines. See all options 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 and reliable operation. Read more
  • Set up alerts: Set up alerts for your dlt pipeline to stay informed about any issues or important events that may require your attention. Read more
  • Set up tracing: Implement tracing in your dlt pipeline to gain insights into its performance and behavior, helping you to diagnose and resolve issues quickly. Read more

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 NameWrite DispositionDescription
api_entities_badgeappendRepresents badges associated with GitLab entities.
api_entities_basic_badge_detailsappendContains basic details about badges in GitLab.
api_entities_batched_background_migrationappendInformation about batched background migrations.
api_entities_clusterappendDetails about clusters in GitLab.
api_entities_dictionary_tableappendRepresents dictionary tables used in GitLab.
api_entities_metric_imageappendStores metric images used in GitLab.
api_entities_broadcast_messageappendBroadcast messages sent within GitLab.
api_entities_avatarappendInformation about avatars in GitLab.
api_entities_plan_limitappendLimits associated with different plans in GitLab.
api_entities_custom_attributeappendCustom attributes assigned to GitLab entities.
api_entities_jobappendDetails about jobs executed in GitLab CI/CD pipelines.
api_entities_metadataappendMetadata related to various GitLab entities.
api_entities_applicationappendInformation about applications integrated with GitLab.
api_entities_branchappendDetails about branches in Git repositories managed by GitLab.
api_entities_appearanceappendAppearance settings and customizations in GitLab.
api_entities_bulk_importsappendInformation about bulk imports executed in GitLab.
api_entities_ci_variableappendCI/CD variables used in GitLab pipelines.
api_entities_bulk_importappendDetails about individual bulk import operations in GitLab.

Additional pipeline guides

This demo works on codespaces. Codespaces is a development environment available for free to anyone with a Github account. You'll be asked to fork the demo repository and from there the README guides you with further steps.
The demo uses the Continue VSCode extension.

Off to codespaces!

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Welcome to "Codex Central", your next-gen help center, driven by OpenAI's GPT-4 model. It's more than just a forum or a FAQ hub – it's a dynamic knowledge base where coders can find AI-assisted solutions to their pressing problems. With GPT-4's powerful comprehension and predictive abilities, Codex Central provides instantaneous issue resolution, insightful debugging, and personalized guidance. Get your code running smoothly with the unparalleled support at Codex Central - coding help reimagined with AI prowess.