Load Capsule CRM Data to Azure Cloud Storage Using Python dlt
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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. This documentation provides a guide on how to load data from Capsule CRM
to Azure Cloud Storage
using the open-source python library dlt
. Azure Cloud Storage
allows you to store data in various formats such as JSONL, Parquet, or CSV, making it easy to create data lakes. This guide will help you streamline your sales processes, improve customer relationships, and boost overall productivity with a simple and intuitive interface. For more details on Capsule CRM
, visit here.
dlt
Key Features
- Governance Support:
dlt
pipelines offer robust governance through metadata utilization, schema enforcement, and schema change alerts. Read more - Schema Enforcement and Curation: Ensure data consistency and quality by enforcing and curating schemas. Read more
- Scaling and Finetuning: Configure and scale up pipelines with parallel processing and memory optimization options. Read more
- Databricks Integration: Set up and use
dlt
with Databricks, including workspace and Unity Catalog configuration. Read more - Tutorial: Learn how to build a data pipeline using
dlt
with practical examples and foundational concepts. 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 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