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Loading Data from Capsule CRM to EDB BigAnimal with dlt in Python

tip

We will be using the dlt PostgreSQL destination to connect to EDB BigAnimal. You can get the connection string for your EDB BigAnimal database as described in the EDB BigAnimal Docs.

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Capsule CRM is a user-friendly customer relationship management (CRM) platform designed to help businesses manage their customer interactions and sales pipeline effectively. It offers features like contact management, task tracking, sales analytics, and workflow automation. Capsule CRM enables businesses to streamline their sales processes, improve customer relationships, and boost overall productivity with a simple and intuitive interface. EDB BigAnimal is a fully managed database-as-a-service that runs in your cloud account or BigAnimal's cloud account, operated by one of the builders of Postgres. BigAnimal simplifies setting up, managing, and scaling databases, supporting PostgreSQL or EDB Postgres Advanced Server with Oracle compatibility. You can also choose distributed high-availability cluster types for geographically distributed databases. Using the open-source python library dlt, you can load data from Capsule CRM into EDB BigAnimal seamlessly. Further information about Capsule CRM is available at capsulecrm.com.

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. Learn more.
  • Schema Enforcement and Curation: dlt empowers users to enforce and curate schemas, ensuring data consistency and quality. Learn more.
  • Schema Evolution: dlt enables proactive governance by alerting users to schema changes, allowing stakeholders to take necessary actions. Learn more.
  • Scaling and Finetuning: dlt offers several mechanisms and configuration options to scale up and finetune pipelines, including parallel processing and memory buffer adjustments. Learn more.
  • Advanced Features: dlt is a constantly growing library that supports many features and use cases needed by the community. Join our Slack.

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

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

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

Click to view full file (275 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="capsule_crm_source", max_table_nesting=2)
def capsule_crm_source(
token: str = dlt.secrets.value,
base_url: str = dlt.config.value,
) -> List[DltResource]:

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

"type": "bearer",
"token": token,

},
"paginator": {
"type":
"page_number",
"page_param":
"page",
"total_path":
"",
"maximum_page":
20,
},
},
"resources":
[
# https://developer.capsulecrm.com/v2/operations/Case#listCases
{
"name": "list_cases",
"table_name": "case",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "kases",
"path": "/api/v2/kases",
"params": {
# the parameters below can optionally be configured
# "since": "OPTIONAL_CONFIG",
# "perPage": "OPTIONAL_CONFIG",
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Case#searchCases
{
"name": "search_cases",
"table_name": "case",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "kases",
"path": "/api/v2/kases/search",
"params": {
# the parameters below can optionally be configured
# "q": "OPTIONAL_CONFIG",
# "perPage": "OPTIONAL_CONFIG",
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Case#showCase
{
"name": "show_case",
"table_name": "case",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "kase",
"path": "/api/v2/kases/{caseId}",
"params": {
"caseId": {
"type": "resolve",
"resource": "list_cases",
"field": "id",
},
# the parameters below can optionally be configured
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Case#listCasesByParty
{
"name": "list_cases_by_party",
"table_name": "case",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "kases",
"path": "/api/v2/parties/{partyId}/kases",
"params": {
"partyId": {
"type": "resolve",
"resource": "list_parties",
"field": "id",
},
# the parameters below can optionally be configured
# "perPage": "OPTIONAL_CONFIG",
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Opportunity#listOpportunities
{
"name": "list_opportunities",
"table_name": "opportunity",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "opportunities",
"path": "/api/v2/opportunities",
"params": {
# the parameters below can optionally be configured
# "since": "OPTIONAL_CONFIG",
# "perPage": "OPTIONAL_CONFIG",
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Opportunity#searchOpportunities
{
"name": "search_opportunities",
"table_name": "opportunity",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "opportunities",
"path": "/api/v2/opportunities/search",
"params": {
# the parameters below can optionally be configured
# "q": "OPTIONAL_CONFIG",
# "perPage": "OPTIONAL_CONFIG",
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Opportunity#showOpportunity
{
"name": "show_opportunity",
"table_name": "opportunity",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "opportunity",
"path": "/api/v2/opportunities/{opportunityId}",
"params": {
"opportunityId": {
"type": "resolve",
"resource": "list_opportunities",
"field": "id",
},
# the parameters below can optionally be configured
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Opportunity#listOpportunitiesByParty
{
"name": "list_opportunities_by_party",
"table_name": "opportunity",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "opportunities",
"path": "/api/v2/parties/{partyId}/opportunities",
"params": {
"partyId": {
"type": "resolve",
"resource": "list_parties",
"field": "id",
},
# the parameters below can optionally be configured
# "perPage": "OPTIONAL_CONFIG",
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Party#listParties
{
"name": "list_parties",
"table_name": "party",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "parties",
"path": "/api/v2/parties",
"params": {
# the parameters below can optionally be configured
# "since": "OPTIONAL_CONFIG",
# "perPage": "OPTIONAL_CONFIG",
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Party#searchParties
{
"name": "search_parties",
"table_name": "party",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "parties",
"path": "/api/v2/parties/search",
"params": {
# the parameters below can optionally be configured
# "q": "OPTIONAL_CONFIG",
# "perPage": "OPTIONAL_CONFIG",
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Party#showParty
{
"name": "show_party",
"table_name": "party",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "party",
"path": "/api/v2/parties/{partyId}",
"params": {
"partyId": {
"type": "resolve",
"resource": "list_parties",
"field": "id",
},
# the parameters below can optionally be configured
# "embed": "OPTIONAL_CONFIG",

},
}
},
# https://developer.capsulecrm.com/v2/operations/Task#listTasks
{
"name": "list_tasks",
"table_name": "task",
"primary_key": "id",
"write_disposition": "merge",
"endpoint": {
"data_selector": "tasks",
"path": "/api/v2/tasks",
"params": {
# the parameters below can optionally be configured
# "perPage": "OPTIONAL_CONFIG",
# "embed": "OPTIONAL_CONFIG",
# "status": "OPTIONAL_CONFIG",

},
}
},
]
}

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

generated secrets.toml


[sources.capsule_crm]
# secrets for your capsule_crm source
token = "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 capsule_crm_pipeline.py to postgres 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 EDB BigAnimal destination in our docs.

3. Running your pipeline for the first time

The dlt cli has also created a main pipeline script for you at capsule_crm_pipeline.py, as well as a folder capsule_crm 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 capsule_crm import capsule_crm_source


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

4. Inspecting your load result

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

dlt pipeline capsule_crm_pipeline info

You can also use streamlit to inspect the contents of your EDB BigAnimal destination for this:

# install streamlit
pip install streamlit
# run the streamlit app for your pipeline with the dlt cli:
dlt pipeline capsule_crm_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, a free CI/CD runner. Follow the step-by-step guide to set up your deployment. Github Actions
  • Deploy with Airflow and Google Composer: Discover how to deploy a pipeline using Airflow and Google Composer, a managed Airflow environment by Google. Airflow
  • Deploy with Google Cloud Functions: Explore the process of deploying a pipeline with Google Cloud Functions for a serverless deployment solution. Google cloud functions
  • Other Deployment Options: Check out additional deployment guides and options available for deploying your dlt pipelines. and others...

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 timely detection of issues. Read more
  • Set up alerts: Configure alerts to stay informed about the status and performance of your dlt pipeline, enabling proactive management and quick response to any problems. Read more
  • Set up tracing: Implement tracing to gather detailed information about the execution of your dlt pipeline, which helps in debugging and performance optimization. Read more

Available Sources and Resources

For this verified source the following sources and resources are available

Source Capsule CRM

Capsule CRM: Manage contacts, tasks, sales opportunities, and customer cases.

Resource NameWrite DispositionDescription
partyappendRefers to contacts or organizations that interact with the business
taskappendUsed to track and manage activities and to-dos within the CRM
opportunityappendRepresents potential sales or deals that are tracked through various stages
caseappendUsed for managing customer support issues or service requests

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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