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Loading Data from Attio to The Local Filesystem with dlt in Python

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Loading data from Attio to The Local Filesystem using dlt is a straightforward process. Attio is a collaborative workspace for teams to manage relationships, track deals, and organize their work. This documentation will guide you through the steps to transfer your data from Attio to The Local Filesystem using the open-source Python library, dlt. The local filesystem destination stores data in a local folder, enabling you to easily create data lakes. You can store data in various formats such as JSONL, Parquet, or CSV. For more information about the source, visit Attio.

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 about lineage.
  • Schema Enforcement and Curation: dlt empowers users to enforce and curate schemas, ensuring data consistency and quality. Read more about adjusting a schema.
  • Schema Evolution: dlt enables proactive governance by alerting users to schema changes in the source data. Learn more about schema changes.
  • Scaling and Finetuning: dlt offers several mechanisms and configuration options to scale up and finetune pipelines, including parallel processing and memory buffer adjustments. Read more about performance.
  • Filesystem & Buckets: dlt supports storing data in remote file systems and bucket storages like S3, Google Storage, or Azure Blob Storage. Learn more about the filesystem destination.

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 attio --url https://raw.githubusercontent.com/dlt-hub/openapi-specs/main/open_api_specs/Business/attio_api.yaml --global-limit 2
cd attio_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:

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

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

Click to view full file (399 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="attio_source", max_table_nesting=2)
def attio_source(
base_url: str = dlt.config.value,
) -> List[DltResource]:

# source configuration
source_config: RESTAPIConfig = {
"client": {
"base_url": base_url,
"paginator": {
"type":
"offset",
"limit":
20,
"offset_param":
"offset",
"limit_param":
"limit",
"total_path":
"",
"maximum_offset":
20,
},
},
"resources":
[
# Lists all attributes defined on a specific object or list. Attributes are returned in the order that they are sorted by in the UI. Required scopes: `object_configuration:read`.
{
"name": "get_v_2_targetidentifierattributes",
"table_name": "attribute",
"endpoint": {
"data_selector": "data",
"path": "/v2/{target}/{identifier}/attributes",
"params": {
"target": "FILL_ME_IN", # TODO: fill in required path parameter
"identifier": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "show_archived": "OPTIONAL_CONFIG",

},
}
},
# Gets information about a single attribute on either an object or a list. Required scopes: `object_configuration:read`.
{
"name": "get_v_2_targetidentifierattributesattribute",
"table_name": "attribute",
"endpoint": {
"data_selector": "data",
"path": "/v2/{target}/{identifier}/attributes/{attribute}",
"params": {
"target": "FILL_ME_IN", # TODO: fill in required path parameter
"identifier": "FILL_ME_IN", # TODO: fill in required path parameter
"attribute": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
# Get a single comment by ID. To view comments on records, you will need the `object_configuration:read` and `record_permission:read` scopes. To view comments on list entries, you will need the `list_configuration:read` and `list_entry:read` scopes. Required scopes: `comment:read`.
{
"name": "get_v_2_commentscomment_id",
"table_name": "comment",
"primary_key": "thread_id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "data",
"path": "/v2/comments/{comment_id}",
"params": {
"comment_id": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
# List all entries, across all lists, for which this record is the parent. Required scopes: `record_permission:read`, `object_configuration:read`, `list_entry:read`.
{
"name": "get_v_2_objectsobjectrecordsrecord_identries",
"table_name": "entry",
"primary_key": "entry_id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "data",
"path": "/v2/objects/{object}/records/{record_id}/entries",
"params": {
"object": "FILL_ME_IN", # TODO: fill in required path parameter
"record_id": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
# Gets a single list entry by its `entry_id`. Required scopes: `list_entry:read`, `list_configuration:read`.
{
"name": "get_v_2_listslistentriesentry_id",
"table_name": "entry",
"primary_key": "parent_record_id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "data",
"path": "/v2/lists/{list}/entries/{entry_id}",
"params": {
"list": "FILL_ME_IN", # TODO: fill in required path parameter
"entry_id": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
# List all lists that your access token has access to. lists are returned in the order that they are sorted in the sidebar. Required scopes: `list_configuration:read`.
{
"name": "get_v_2_lists",
"table_name": "list",
"endpoint": {
"data_selector": "data",
"path": "/v2/lists",
}
},
# Gets a single list in your workspace that your access token has access to. Required scopes: `list_configuration:read`.
{
"name": "get_v_2_listslist",
"table_name": "list",
"endpoint": {
"data_selector": "data",
"path": "/v2/lists/{list}",
"params": {
"list": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
# List notes for all records or for a specific record. Required scopes: `note:read`, `object_configuration:read`, `record_permission:read`.
{
"name": "get_v_2_notes",
"table_name": "note",
"primary_key": "parent_record_id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "data",
"path": "/v2/notes",
"params": {
# the parameters below can optionally be configured
# "parent_object": "OPTIONAL_CONFIG",
# "parent_record_id": "OPTIONAL_CONFIG",

},
}
},
# Get a single note by ID. Required scopes: `note:read`, `object_configuration:read`, `record_permission:read`.
{
"name": "get_v_2_notesnote_id",
"table_name": "note",
"primary_key": "parent_record_id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "data",
"path": "/v2/notes/{note_id}",
"params": {
"note_id": {
"type": "resolve",
"resource": "get_v_2_notes",
"field": "parent_record_id",
},

},
}
},
# Lists all system-defined and user-defined objects in your workspace. Required scopes: `object_configuration:read`.
{
"name": "get_v_2_objects",
"table_name": "object",
"endpoint": {
"data_selector": "data",
"path": "/v2/objects",
}
},
# Gets a single object by its `object_id` or slug. Required scopes: `object_configuration:read`.
{
"name": "get_v_2_objectsobject",
"table_name": "object",
"endpoint": {
"data_selector": "data",
"path": "/v2/objects/{object}",
"params": {
"object": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
# Gets a single person, company or other record by its `record_id`. Required scopes: `record_permission:read`, `object_configuration:read`.
{
"name": "get_v_2_objectsobjectrecordsrecord_id",
"table_name": "record",
"endpoint": {
"data_selector": "data",
"path": "/v2/objects/{object}/records/{record_id}",
"params": {
"object": "FILL_ME_IN", # TODO: fill in required path parameter
"record_id": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
# Lists all select options for a particular attribute on either an object or a list. Required scopes: `object_configuration:read`.
{
"name": "get_v_2_targetidentifierattributesattributeoptions",
"table_name": "select_option",
"endpoint": {
"data_selector": "data",
"path": "/v2/{target}/{identifier}/attributes/{attribute}/options",
"params": {
"target": "FILL_ME_IN", # TODO: fill in required path parameter
"identifier": "FILL_ME_IN", # TODO: fill in required path parameter
"attribute": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "show_archived": "OPTIONAL_CONFIG",

},
}
},
# Identify the current access token, the workspace it is linked to, and any permissions it has.
{
"name": "get_v_2_self",
"table_name": "self",
"primary_key": "sub",
"write_disposition": "merge",
"endpoint": {
"data_selector": "$",
"path": "/v2/self",
}
},
# Lists all statuses for a particular status attribute on either an object or a list. Required scopes: `object_configuration:read`.
{
"name": "get_v_2_targetidentifierattributesattributestatuses",
"table_name": "status",
"endpoint": {
"data_selector": "data",
"path": "/v2/{target}/{identifier}/attributes/{attribute}/statuses",
"params": {
"target": "FILL_ME_IN", # TODO: fill in required path parameter
"identifier": "FILL_ME_IN", # TODO: fill in required path parameter
"attribute": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "show_archived": "false",

},
}
},
# List all tasks. Results are sorted by creation date, from oldest to newest. Required scopes: `task:read`, `object_configuration:read`, `record_permission:read`, `user_management:read`.
{
"name": "get_v_2_tasks",
"table_name": "task",
"endpoint": {
"data_selector": "data",
"path": "/v2/tasks",
"params": {
# the parameters below can optionally be configured
# "sort": "OPTIONAL_CONFIG",
# "linked_object": "OPTIONAL_CONFIG",
# "linked_record_id": "OPTIONAL_CONFIG",
# "assignee": "OPTIONAL_CONFIG",
# "is_completed": "OPTIONAL_CONFIG",

},
}
},
# Get a single task by ID. Required scopes: `task:read`, `object_configuration:read`, `record_permission:read`, `user_management:read`.
{
"name": "get_v_2_taskstask_id",
"table_name": "task",
"endpoint": {
"data_selector": "data",
"path": "/v2/tasks/{task_id}",
"params": {
"task_id": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
# List threads of comments on a record or list entry. To view threads on records, you will need the `object_configuration:read` and `record_permission:read` scopes. To view threads on list entries, you will need the `list_configuration:read` and `list_entry:read` scopes. Required scopes: `comment:read`.
{
"name": "get_v_2_threads",
"table_name": "thread",
"endpoint": {
"data_selector": "data",
"path": "/v2/threads",
"params": {
# the parameters below can optionally be configured
# "record_id": "OPTIONAL_CONFIG",
# "object": "OPTIONAL_CONFIG",
# "entry_id": "OPTIONAL_CONFIG",
# "list": "OPTIONAL_CONFIG",

},
}
},
# Get all comments in a thread. To view threads on records, you will need the `object_configuration:read` and `record_permission:read` scopes. To view threads on list entries, you will need the `list_configuration:read` and `list_entry:read` scopes. Required scopes: `comment:read`.
{
"name": "get_v_2_threadsthread_id",
"table_name": "thread",
"endpoint": {
"data_selector": "data",
"path": "/v2/threads/{thread_id}",
"params": {
"thread_id": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
# Gets all values for a given attribute on a record. If the attribute is historic, this endpoint has the ability to return all historic values using the `show_historic` query param. Required scopes: `record_permission:read`, `object_configuration:read`.
{
"name": "get_v_2_objectsobjectrecordsrecord_idattributesattributevalues",
"table_name": "value",
"primary_key": "referenced_actor_id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "data",
"path": "/v2/objects/{object}/records/{record_id}/attributes/{attribute}/values",
"params": {
"object": "FILL_ME_IN", # TODO: fill in required path parameter
"record_id": "FILL_ME_IN", # TODO: fill in required path parameter
"attribute": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "show_historic": "false",

},
}
},
# Gets all values for a given attribute on a list entry. If the attribute is historic, this endpoint has the ability to return all historic values using the `show_historic` query param. Required scopes: `list_entry:read`, `list_configuration:read`.
{
"name": "get_v_2_listslistentriesentry_idattributesattributevalues",
"table_name": "value",
"primary_key": "referenced_actor_id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "data",
"path": "/v2/lists/{list}/entries/{entry_id}/attributes/{attribute}/values",
"params": {
"list": "FILL_ME_IN", # TODO: fill in required path parameter
"entry_id": "FILL_ME_IN", # TODO: fill in required path parameter
"attribute": "FILL_ME_IN", # TODO: fill in required path parameter
# the parameters below can optionally be configured
# "show_historic": "false",

},
}
},
# Get all of the webhooks in your workspace. Required scopes: `webhook:read`.
{
"name": "get_v_2_webhooks",
"table_name": "webhook",
"endpoint": {
"data_selector": "data",
"path": "/v2/webhooks",
}
},
# Get a single webhook. Required scopes: `webhook:read`.
{
"name": "get_v_2_webhookswebhook_id",
"table_name": "webhook",
"endpoint": {
"data_selector": "data",
"path": "/v2/webhooks/{webhook_id}",
"params": {
"webhook_id": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
# Lists all workspace members in the workspace. Required scopes: `user_management:read`.
{
"name": "get_v_2_workspace_members",
"table_name": "workspace_member",
"endpoint": {
"data_selector": "data",
"path": "/v2/workspace_members",
}
},
# Gets a single workspace member by ID. Required scopes: `user_management:read`.
{
"name": "get_v_2_workspace_membersworkspace_member_id",
"table_name": "workspace_member",
"endpoint": {
"data_selector": "data",
"path": "/v2/workspace_members/{workspace_member_id}",
"params": {
"workspace_member_id": "FILL_ME_IN", # TODO: fill in required path parameter

},
}
},
]
}

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

generated secrets.toml


[sources.attio]
# secrets for your attio source
# example_api_key = "example value"

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 attio_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 The Local Filesystem destination in our docs.

The default filesystem destination is configured to connect to AWS S3. To load to a local directory, remove the [destination.filesystem.credentials] section from your secrets.toml and provide a local filepath as the bucket_url.

[destination.filesystem] # in ./dlt/secrets.toml
bucket_url="file://path/to/my/output"

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 attio_pipeline.py, as well as a folder attio 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 attio import attio_source


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

4. Inspecting your load result

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

dlt pipeline attio_pipeline info

You can also use streamlit to inspect the contents of your The Local Filesystem destination for this:

# install streamlit
pip install streamlit
# run the streamlit app for your pipeline with the dlt cli:
dlt pipeline attio_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 pipeline using Github Actions.
  • Deploy with Airflow: Discover the steps to deploy a pipeline with Airflow and Google Composer.
  • Deploy with Google Cloud Functions: Follow the guide to deploy your pipeline using Google Cloud Functions.
  • Explore more deployment options: Check out other methods to deploy a pipeline here.

The running in production section will teach you about:

  • How to Monitor your pipeline: Learn how to effectively monitor your dlt pipeline to ensure it runs smoothly in production. How to Monitor your pipeline
  • Set up alerts: Set up alerts to get notified about any issues or anomalies in your dlt pipeline. Set up alerts
  • And set up tracing: Implement tracing to get detailed insights into the execution of your dlt pipeline. And set up tracing

Available Sources and Resources

For this verified source the following sources and resources are available

Source Attio

Attio source provides CRM data including workspace members, attributes, comments, statuses, and tasks.

Resource NameWrite DispositionDescription
workspace_memberappendDetails of members in the workspace
attributeappendVarious attributes associated with records
commentappendComments added by users
selfappendInformation about the authenticated user
select_optionappendOptions for select fields
statusappendStatus updates for records
listappendLists of records
threadappendThreads of conversations or activities
recordappendIndividual records in the workspace
valueappendValues assigned to attributes
objectappendVarious objects in the workspace
webhookappendWebhooks configured for the workspace
entryappendEntries in the workspace
noteappendNotes added to records
taskappendTasks assigned to users

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!

DHelp

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