Load Data from Capsule CRM
to YugabyteDB
using dlt
in Python
We will be using the dlt PostgreSQL destination to connect to YugabyteDB. You can get the connection string for your YugabyteDB database as described in the YugabyteDB Docs.
Join our Slack community or book a call with our support engineer Violetta.
This page provides technical documentation on loading data from Capsule CRM
into YugabyteDB
using the open-source Python library dlt
. Capsule CRM
is a user-friendly customer relationship management platform designed to help businesses manage customer interactions and sales pipelines effectively. It offers features like contact management, task tracking, sales analytics, and workflow automation. YugabyteDB
is a distributed PostgreSQL database for modern applications, offering built-in resilience, seamless scalability, and flexible geo-distribution. By leveraging dlt
, users can streamline the process of extracting and loading data from Capsule CRM
into YugabyteDB
, ensuring efficient data management and enhanced productivity. Further information about Capsule CRM
can be found at Capsule CRM.
dlt
Key Features
- Pipeline Metadata:
dlt
pipelines leverage metadata such as load IDs to enable incremental transformations, data vaulting, and data lineage and traceability. Read more - Schema Enforcement and Curation:
dlt
empowers users to enforce and curate schemas, ensuring data consistency and quality. Learn more - Scalability via Iterators, Chunking, and Parallelization:
dlt
offers scalable data extraction by leveraging iterators, chunking, and parallelization techniques. Learn more - Schema Evolution:
dlt
alerts users to schema changes, allowing them to review and validate changes, update downstream processes, or perform impact analysis. Read more - Databricks Integration:
dlt
supports Databricks as a destination, facilitating seamless data loading into Databricks. Learn 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 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
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.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
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.
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 YugabyteDB
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 set up continuous integration and deployment for your
dlt
pipelines using GitHub Actions. - Deploy with Airflow and Google Composer: Follow this guide to deploy your
dlt
pipelines using Airflow and Google Composer. - Deploy with Google Cloud Functions: Discover how to deploy your
dlt
pipelines using Google Cloud Functions. - Explore Other Deployment Options: Check out additional methods to deploy 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 in production to ensure smooth operation. How to Monitor your pipeline - Set up alerts: Set up alerts to get notified of any issues or anomalies in your
dlt
pipeline. Set up alerts - Set up tracing: Implement tracing to get detailed insights and diagnostics about your
dlt
pipeline's execution. And set up tracing
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 Name | Write Disposition | Description |
---|---|---|
party | append | Refers to contacts or organizations that interact with the business |
task | append | Used to track and manage activities and to-dos within the CRM |
opportunity | append | Represents potential sales or deals that are tracked through various stages |
case | append | Used for managing customer support issues or service requests |
Additional pipeline guides
- Load data from Imgur to Azure Cloud Storage in python with dlt
- Load data from Jira to Snowflake in python with dlt
- Load data from Pinterest to Databricks in python with dlt
- Load data from CircleCI to BigQuery in python with dlt
- Load data from Chargebee to AWS Athena in python with dlt
- Load data from Star Trek to PostgreSQL in python with dlt
- Load data from Keap to Google Cloud Storage in python with dlt
- Load data from MongoDB to CockroachDB in python with dlt
- Load data from Mux to Google Cloud Storage in python with dlt
- Load data from Shopify to Databricks in python with dlt