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Loading Data from Fivetran to AWS S3 with dlt in Python

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This documentation provides a comprehensive guide on loading data from fivetran to AWS S3 using the open-source Python library dlt. fivetran is an ETL tool that helps customers leverage their data for various applications, including AI, machine learning, predictive analytics, and operational workloads. On the other hand, the AWS S3 filesystem destination allows for easy creation of data lakes by storing data as JSONL, Parquet, or CSV files. This guide will walk you through the steps required to set up and use dlt for seamless data transfer from fivetran to AWS S3. For more information about fivetran, visit their website.

dlt Key Features

  • Pipeline Metadata: dlt pipelines leverage metadata including load IDs, which consist of a timestamp and pipeline name, enabling incremental transformations and data vaulting by tracking data loads. Read more.
  • Schema Enforcement and Curation: dlt empowers users to enforce and curate schemas, ensuring data consistency and quality. Read more.
  • Scalability via Iterators, Chunking, and Parallelization: dlt offers scalable data extraction by leveraging iterators, chunking, and parallelization techniques. Read more.
  • Implicit Extraction DAGs: dlt incorporates the concept of implicit extraction DAGs to handle dependencies between data sources and their transformations automatically. Read more.
  • AWS S3 Setup: Detailed instructions on setting up AWS S3 bucket storage and credentials for use 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 fivetran --url https://raw.githubusercontent.com/dlt-hub/openapi-specs/main/open_api_specs/Business/fivetran.yaml --global-limit 2
cd fivetran_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:

fivetran_pipeline/
├── .dlt/
│ ├── config.toml # configs for your pipeline
│ └── secrets.toml # secrets for your pipeline
├── rest_api/ # The rest api verified source
│ └── ...
├── fivetran/
│ └── __init__.py # TODO: possibly tweak this file
├── fivetran_pipeline.py # your main pipeline script
├── requirements.txt # dependencies for your pipeline
└── .gitignore # ignore files for git (not required)

1.1. Tweak fivetran/__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 fivetran source will look like this:

Click to view full file (885 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="fivetran_source", max_table_nesting=2)
def fivetran_source(
username: str = dlt.secrets.value,
password: str = dlt.secrets.value,
base_url: str = dlt.config.value,
) -> List[DltResource]:

# source configuration
source_config: RESTAPIConfig = {
"client": {
"base_url": base_url,
"auth": {

"type": "http_basic",
"username": username,
"password": password,

},
},
"resources":
[
# Returns the list of approved certificates for specified connector.
{
"name": "get_connector_certificates_list",
"table_name": "certificate",
"endpoint": {
"data_selector": "$",
"path": "/v1/connectors/{connectorId}/certificates",
"params": {
"connectorId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns the list of approved certificates for specified destination.
{
"name": "get_destination_certificates_list",
"table_name": "certificate",
"endpoint": {
"data_selector": "$",
"path": "/v1/destinations/{destinationId}/certificates",
"params": {
"destinationId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns details of the certificate approved for specified destination with specified hash.
{
"name": "get_destination_certificate_details",
"table_name": "certificate",
"endpoint": {
"data_selector": "$",
"path": "/v1/destinations/{destinationId}/certificates/{hash}",
"params": {
"destinationId": "FILL_ME_IN", # TODO: fill in required path parameter
"hash": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns details of the certificate approved for specified connector with specified hash.
{
"name": "get_connector_certificate_details",
"table_name": "certificate",
"endpoint": {
"data_selector": "$",
"path": "/v1/connectors/{connectorId}/certificates/{hash}",
"params": {
"connectorId": "FILL_ME_IN", # TODO: fill in required path parameter
"hash": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns the source table columns config for an existing connector within your Fivetran account
{
"name": "connector_column_config",
"table_name": "column",
"endpoint": {
"data_selector": "$",
"path": "/v1/connectors/{connectorId}/schemas/{schema}/tables/{table}/columns",
"params": {
"connectorId": "FILL_ME_IN", # TODO: fill in required path parameter
"schema": "FILL_ME_IN", # TODO: fill in required path parameter
"table": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns all connections attached to the proxy agent.
{
"name": "get_proxy_agent_connections",
"table_name": "connection",
"endpoint": {
"data_selector": "$",
"path": "/v1/proxy/{agentId}/connections",
"params": {
"agentId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns connector memberships within a team.
{
"name": "get_team_memberships_in_connectors",
"table_name": "connector",
"endpoint": {
"data_selector": "$",
"path": "/v1/teams/{teamId}/connectors",
"params": {
"teamId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a connector membership object.
{
"name": "get_user_membership_in_connector",
"table_name": "connector",
"endpoint": {
"data_selector": "$",
"path": "/v1/users/{userId}/connectors/{connectorId}",
"params": {
"userId": "FILL_ME_IN", # TODO: fill in required path parameter
"connectorId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a connector object if a valid identifier was provided
{
"name": "connector_details",
"table_name": "connector",
"endpoint": {
"data_selector": "$",
"path": "/v1/connectors/{connectorId}",
"params": {
"connectorId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a connector membership within a team
{
"name": "get_team_membership_in_connector",
"table_name": "connector",
"endpoint": {
"data_selector": "$",
"path": "/v1/teams/{teamId}/connectors/{connectorId}",
"params": {
"teamId": "FILL_ME_IN", # TODO: fill in required path parameter
"connectorId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a list of information about all connectors within a group in your Fivetran account.
{
"name": "list_all_connectors_in_group",
"table_name": "connector",
"endpoint": {
"data_selector": "$",
"path": "/v1/groups/{groupId}/connectors",
"params": {
"groupId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "schema": "OPTIONAL_CONFIG",
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns all connector membership objects for a user within your Fivetran account
{
"name": "get_user_memberships_in_connectors",
"table_name": "connector",
"endpoint": {
"data_selector": "$",
"path": "/v1/users/{userId}/connectors",
"params": {
"userId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns metadata of configuration parameters and authorization parameters for a specified connector type.
{
"name": "metadata_connector_config",
"table_name": "connector_type",
"endpoint": {
"data_selector": "$",
"path": "/v1/metadata/connector-types/{service}",
"params": {
"service": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns all available source types within your Fivetran account. This endpoint makes it easier to display Fivetran connectors within your application because it provides metadata including the proper source name ('Facebook Ads' instead of 'facebook_ads'), the source icon, and links to Fivetran resources. As we update source names and icons, that metadata will automatically update within this endpoint
{
"name": "metadata_connectors",
"table_name": "connector_type",
"endpoint": {
"data_selector": "$",
"path": "/v1/metadata/connector-types",
"params": {
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a destination object if a valid identifier was provided.
{
"name": "destination_details",
"table_name": "destination",
"endpoint": {
"data_selector": "$",
"path": "/v1/destinations/{destinationId}",
"params": {
"destinationId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a logging service object if a valid identifier was provided.
{
"name": "get_log_service_details",
"table_name": "external_logging",
"endpoint": {
"data_selector": "$",
"path": "/v1/external-logging/{logId}",
"params": {
"logId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns SSH fingerprint details approved for specified destination with specified hash
{
"name": "get_destination_fingerprint_details",
"table_name": "fingerprint",
"endpoint": {
"data_selector": "$",
"path": "/v1/destinations/{destinationId}/fingerprints/{hash}",
"params": {
"destinationId": "FILL_ME_IN", # TODO: fill in required path parameter
"hash": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns SSH fingerprint details approved for specified connector with specified hash
{
"name": "get_connector_fingerprint_details",
"table_name": "fingerprint",
"endpoint": {
"data_selector": "$",
"path": "/v1/connectors/{connectorId}/fingerprints/{hash}",
"params": {
"connectorId": "FILL_ME_IN", # TODO: fill in required path parameter
"hash": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns the list of approved SSH fingerprints for specified destination
{
"name": "get_destination_fingerprints_list",
"table_name": "fingerprint",
"endpoint": {
"data_selector": "$",
"path": "/v1/destinations/{destinationId}/fingerprints",
"params": {
"destinationId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns the list of approved SSH fingerprints for specified connector
{
"name": "get_connector_fingerprints_list",
"table_name": "fingerprint",
"endpoint": {
"data_selector": "$",
"path": "/v1/connectors/{connectorId}/fingerprints",
"params": {
"connectorId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns all group membership objects for a user within your Fivetran account.
{
"name": "get_user_memberships_in_groups",
"table_name": "group",
"endpoint": {
"data_selector": "$",
"path": "/v1/users/{userId}/groups",
"params": {
"userId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a group membership within a team
{
"name": "get_team_memberships_in_groups",
"table_name": "group",
"endpoint": {
"data_selector": "$",
"path": "/v1/teams/{teamId}/groups",
"params": {
"teamId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a group object if a valid identifier was provided.
{
"name": "group_details",
"table_name": "group",
"endpoint": {
"data_selector": "$",
"path": "/v1/groups/{groupId}",
"params": {
"groupId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a group membership within a team.
{
"name": "get_team_membership_in_group",
"table_name": "group",
"endpoint": {
"data_selector": "$",
"path": "/v1/teams/{teamId}/groups/{groupId}",
"params": {
"teamId": "FILL_ME_IN", # TODO: fill in required path parameter
"groupId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a list of all groups within your Fivetran account.
{
"name": "list_all_groups",
"table_name": "group",
"endpoint": {
"data_selector": "$",
"path": "/v1/groups",
"params": {
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a group membership object.
{
"name": "get_user_membership_in_group",
"table_name": "group",
"endpoint": {
"data_selector": "$",
"path": "/v1/users/{userId}/groups/{groupId}",
"params": {
"userId": "FILL_ME_IN", # TODO: fill in required path parameter
"groupId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns information about current account from API key.
{
"name": "get_account_info",
"table_name": "info",
"endpoint": {
"data_selector": "$",
"path": "/v1/account/info",
"paginator": "auto",
}
},
# Returns Local Processing Agent Details.
{
"name": "get_local_processing_agent",
"table_name": "local_processing_agent",
"endpoint": {
"data_selector": "$",
"path": "/v1/local-processing-agents/{agentId}",
"params": {
"agentId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns list of all Local Processing Agents within your Fivetran account, along with usage. Optionally filtered to a single group.
{
"name": "get_local_processing_agent_list",
"table_name": "local_processing_agent",
"endpoint": {
"data_selector": "$",
"path": "/v1/local-processing-agents",
"params": {
# the parameters below can optionally be configured
# "groupId": "OPTIONAL_CONFIG",
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a list of all dbt Models within dbt Project.
{
"name": "list_dbt_project_models",
"table_name": "model",
"endpoint": {
"data_selector": "$",
"path": "/v1/dbt/models",
"params": {
"project_id": "FILL_ME_IN", # TODO: fill in required query parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a list of all dbt Models within dbt Project. (Deprecated)
{
"name": "list_dbt_project_models_deprecated",
"table_name": "model",
"endpoint": {
"data_selector": "$",
"path": "/v1/dbt/projects/{projectId}/models",
"params": {
"projectId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a dbt Model details if a valid identifier was provided.
{
"name": "dbt_model_details",
"table_name": "model",
"endpoint": {
"data_selector": "$",
"path": "/v1/dbt/models/{modelId}",
"params": {
"modelId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a list of all private links.
{
"name": "get_private_links",
"table_name": "private_link",
"endpoint": {
"data_selector": "$",
"path": "/v1/groups/{groupId}/private-links",
"params": {
"groupId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a private link object if a valid identifier was provided.
{
"name": "get_private_link_details",
"table_name": "private_link",
"endpoint": {
"data_selector": "$",
"path": "/v1/private-links/{privateLinkId}",
"params": {
"privateLinkId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a dbt Project details if a valid identifier was provided.
{
"name": "dbt_project_details",
"table_name": "project",
"endpoint": {
"data_selector": "$",
"path": "/v1/dbt/projects/{projectId}",
"params": {
"projectId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a list of all dbt Projects within your Fivetran account.
{
"name": "list_dbt_projects",
"table_name": "project",
"endpoint": {
"data_selector": "$",
"path": "/v1/dbt/projects",
"params": {
# the parameters below can optionally be configured
# "group_id": "OPTIONAL_CONFIG",
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a list of all proxy agents.
{
"name": "get_proxy_agent",
"table_name": "proxy",
"endpoint": {
"data_selector": "$",
"path": "/v1/proxy",
"params": {
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a proxy agent object if a valid identifier was provided.
{
"name": "get_proxy_agent_details",
"table_name": "proxy_agent_response",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/v1/proxy/{agentId}",
"params": {
"agentId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns public key from SSH key pair associated with the group.
{
"name": "group_ssh_public_key",
"table_name": "public_key",
"endpoint": {
"data_selector": "$",
"path": "/v1/groups/{groupId}/public-key",
"params": {
"groupId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a list of all predefined and custom roles within your Fivetran account.
{
"name": "list_all_roles",
"table_name": "role",
"endpoint": {
"data_selector": "$",
"path": "/v1/roles",
"params": {
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns the connector schema config for an existing connector within your Fivetran account
{
"name": "connector_schema_config",
"table_name": "schema",
"endpoint": {
"data_selector": "$",
"path": "/v1/connectors/{connectorId}/schemas",
"params": {
"connectorId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns Fivetran service account associated with the group.
{
"name": "group_service_account",
"table_name": "service_account",
"endpoint": {
"data_selector": "$",
"path": "/v1/groups/{groupId}/service-account",
"params": {
"groupId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns the connector state. This endpoint is only supported for function connectors.
{
"name": "connector_state",
"table_name": "state",
"endpoint": {
"data_selector": "$",
"path": "/v1/connectors/{connectorId}/state",
"params": {
"connectorId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns information for a given team within your Fivetran account
{
"name": "team_details",
"table_name": "team",
"endpoint": {
"data_selector": "$",
"path": "/v1/teams/{teamId}",
"params": {
"teamId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a list of all teams within your Fivetran account
{
"name": "list_all_teams",
"table_name": "team",
"endpoint": {
"data_selector": "$",
"path": "/v1/teams",
"params": {
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a dbt Transformation details if a valid identifier was provided.
{
"name": "dbt_transformation_details",
"table_name": "transformation",
"endpoint": {
"data_selector": "$",
"path": "/v1/dbt/transformations/{transformationId}",
"params": {
"transformationId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a list of all dbt Transformations within dbt Project.
{
"name": "list_dbt_project_transformations",
"table_name": "transformation",
"endpoint": {
"data_selector": "$",
"path": "/v1/dbt/transformations",
"params": {
"project_id": "FILL_ME_IN", # TODO: fill in required query parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a list of all dbt Transformations within dbt Project. (Deprecated)
{
"name": "list_dbt_project_transformations_deprecated",
"table_name": "transformation",
"endpoint": {
"data_selector": "$",
"path": "/v1/dbt/projects/{projectId}/transformations",
"params": {
"projectId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns the user role a user has within a team
{
"name": "get_user_in_team",
"table_name": "user",
"endpoint": {
"data_selector": "$",
"path": "/v1/teams/{teamId}/users/{userId}",
"params": {
"teamId": "FILL_ME_IN", # TODO: fill in required path parameter
"userId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a list of all users within your Fivetran account.
{
"name": "list_all_users",
"table_name": "user",
"endpoint": {
"data_selector": "$",
"path": "/v1/users",
"params": {
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a user object if a valid identifier was provided.
{
"name": "user_details",
"table_name": "user",
"endpoint": {
"data_selector": "$",
"path": "/v1/users/{userId}",
"params": {
"userId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# Returns a list of information about all users within a group in your Fivetran account.
{
"name": "list_all_users_in_group",
"table_name": "user",
"endpoint": {
"data_selector": "$",
"path": "/v1/groups/{groupId}/users",
"params": {
"groupId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# Returns a list of users and their roles within a team in your Fivetran account
{
"name": "list_users_in_team",
"table_name": "user",
"endpoint": {
"data_selector": "$",
"path": "/v1/teams/{teamId}/users",
"params": {
"teamId": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
# This endpoint allows you to retrieve details of the existing webhook for a given identifier
{
"name": "webhook_details",
"table_name": "webhook",
"endpoint": {
"data_selector": "$",
"path": "/v1/webhooks/{webhookId}",
"params": {
"webhookId": "FILL_ME_IN", # TODO: fill in required path parameter

},
"paginator": "auto",
}
},
# The endpoint allows you to retrieve the list of existing webhooks available for the current account
{
"name": "list_all_webhooks",
"table_name": "webhook",
"endpoint": {
"data_selector": "$",
"path": "/v1/webhooks",
"params": {
# the parameters below can optionally be configured
# "cursor": "OPTIONAL_CONFIG",
# "limit": "OPTIONAL_CONFIG",

},
"paginator": "auto",
}
},
]
}

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.fivetran]
# Base URL for the API
base_url = "https://api.fivetran.com"

generated secrets.toml


[sources.fivetran]
# secrets for your fivetran source
username = "FILL ME OUT" # TODO: fill in your credentials
password = "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 fivetran_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 AWS S3 destination in our docs.

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 fivetran_pipeline.py, as well as a folder fivetran 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 fivetran import fivetran_source


if __name__ == "__main__":
pipeline = dlt.pipeline(
pipeline_name="fivetran_pipeline",
destination='duckdb',
dataset_name="fivetran_data",
progress="log",
export_schema_path="schemas/export"
)
source = fivetran_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 fivetran_pipeline.py

4. Inspecting your load result

You can now inspect the state of your pipeline with the dlt cli:

dlt pipeline fivetran_pipeline info

You can also use streamlit to inspect the contents of your AWS S3 destination for this:

# install streamlit
pip install streamlit
# run the streamlit app for your pipeline with the dlt cli:
dlt pipeline fivetran_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 your dlt pipeline using GitHub Actions for CI/CD. Follow the guide here.
  • Deploy with Airflow and Google Composer: Discover the steps to deploy your dlt pipeline using Airflow and Google Composer. Detailed instructions can be found here.
  • Deploy with Google Cloud Functions: Find out how to deploy your dlt pipeline with Google Cloud Functions. Check the guide here.
  • Explore Other Deployment Options: Explore various other methods to deploy your dlt pipeline. Learn more 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. Read more
  • Set up alerts: Discover how to set up alerts for your dlt pipeline to get notified of any issues or significant events that require your attention. Read more
  • And set up tracing: Understand how to set up tracing for your dlt pipeline to track the flow of data and debug any problems that arise during execution. Read more

Available Sources and Resources

For this verified source the following sources and resources are available

Source Fivetran

Fivetran source for syncing connectors, configurations, and user data efficiently.

Resource NameWrite DispositionDescription
stateappendRepresents the state of a Fivetran connector.
connectorappendContains data about the connectors used in Fivetran.
columnappendDetails about the columns in the tables managed by Fivetran.
webhookappendInformation on webhooks configured in Fivetran.
proxy_agent_responseappendResponses from proxy agents used in Fivetran.
proxyappendData regarding the proxies configured in Fivetran.
modelappendInformation about the models used in Fivetran transformations.
connector_typeappendTypes of connectors available in Fivetran.
transformationappendData about the transformations applied to the data in Fivetran.
service_accountappendDetails about the service accounts used in Fivetran.
connectionappendInformation on the connections established in Fivetran.
local_processing_agentappendData about local processing agents in Fivetran.
private_linkappendInformation on private links configured in Fivetran.
projectappendData regarding the projects managed within Fivetran.
teamappendInformation about the teams using Fivetran.
destinationappendDetails about the data destinations configured in Fivetran.
infoappendGeneral information about the Fivetran setup.
userappendData about the users in the Fivetran system.
certificateappendInformation on the certificates used in Fivetran.
schemaappendDetails about the schemas used in Fivetran.
groupappendInformation on the groups configured in Fivetran.
roleappendData about the roles assigned to users in Fivetran.
public_keyappendDetails about the public keys used in Fivetran.
external_loggingappendInformation on external logging configurations in Fivetran.
fingerprintappendData about the fingerprints used for security and authentication in Fivetran.

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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