Loading Data from Attio
to Azure Cloud Storage
using dlt
in Python
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This documentation provides a guide for loading data from Attio
to Azure Cloud Storage
using the open-source Python library dlt
. Attio
is a collaborative workspace designed for teams to manage relationships, track deals, and organize their work efficiently. Azure Cloud Storage
serves as a destination to store this data, allowing you to create data lakes with ease. The data can be uploaded in various formats including JSONL, Parquet, or CSV. This guide will walk you through the process of setting up and using dlt
to facilitate the data transfer. For further information on Attio
, visit their website.
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: Enforce and curate schemas to ensure data consistency and quality. Schemas define the structure of normalized data and guide the processing and loading of data. Read more
- Schema Evolution Alerts:
dlt
proactively alerts users to schema changes, enabling them to review and validate changes, update downstream processes, or perform impact analysis. Read more - Scaling and Finetuning: Offers several mechanisms and configuration options to scale up and finetune pipelines, such as running extraction, normalization, and load in parallel. Read more
- Filesystem & Buckets: Use remote file systems and bucket storages like S3, Google Storage, or Azure Blob Storage for staging or building a data lake. Read more
Getting started with your pipeline locally
dlt-init-openapi
0. Prerequisites
dlt
and dlt-init-openapi
requires Python 3.9 or higher. Additionally, you need to have the pip
package manager installed, and we recommend using a virtual environment to manage your dependencies. You can learn more about preparing your computer for dlt in our installation reference.
1. Install dlt and dlt-init-openapi
First you need to install the dlt-init-openapi
cli tool.
pip install dlt-init-openapi
The dlt-init-openapi
cli is a powerful generator which you can use to turn any OpenAPI spec into a dlt
source to ingest data from that api. The quality of the generator source is dependent on how well the API is designed and how accurate the OpenAPI spec you are using is. You may need to make tweaks to the generated code, you can learn more about this here.
# generate pipeline
# NOTE: add_limit adds a global limit, you can remove this later
# NOTE: you will need to select which endpoints to render, you
# can just hit Enter and all will be rendered.
dlt-init-openapi 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
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.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
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.
The default filesystem destination is configured to connect to AWS S3. To load to Azure Cloud Storage, update the [destination.filesystem.credentials]
section in your secrets.toml
.
[destination.filesystem.credentials]
azure_storage_account_name="Please set me up!"
azure_storage_account_key="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 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 Azure Cloud Storage
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 set up and deploy your pipeline using GitHub Actions for CI/CD. Follow the step-by-step guide here.
- Deploy with Airflow and Google Composer: Discover how to use Airflow and Google Composer to manage and deploy your
dlt
pipelines. Detailed instructions can be found here. - Deploy with Google Cloud Functions: Get guidance on deploying your
dlt
pipeline using Google Cloud Functions. Check out the guide here. - Explore other deployment options: Find more methods and detailed walkthroughs for deploying 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 to ensure smooth operations and quick issue detection. How to Monitor your pipeline - Set up alerts: Configure alerts to stay informed about your pipeline's status and promptly address any issues that arise. Set up alerts
- Set up tracing: Implement tracing to gain deeper insights into your pipeline's performance and troubleshoot problems efficiently. 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 Name | Write Disposition | Description |
---|---|---|
workspace_member | append | Details of members in the workspace |
attribute | append | Various attributes associated with records |
comment | append | Comments added by users |
self | append | Information about the authenticated user |
select_option | append | Options for select fields |
status | append | Status updates for records |
list | append | Lists of records |
thread | append | Threads of conversations or activities |
record | append | Individual records in the workspace |
value | append | Values assigned to attributes |
object | append | Various objects in the workspace |
webhook | append | Webhooks configured for the workspace |
entry | append | Entries in the workspace |
note | append | Notes added to records |
task | append | Tasks assigned to users |
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