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Loading Data from Capsule CRM to The Local Filesystem Using dlt in Python

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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. This documentation will guide you through loading data from Capsule CRM to The Local Filesystem using the open-source python library called dlt. The Local Filesystem destination stores data in a local folder, allowing you to create data lakes easily. You can store data in formats such as JSONL, Parquet, or CSV. Further information about Capsule CRM is available at https://capsulecrm.com.

dlt Key Features​

  • Pipeline Metadata: dlt pipelines leverage metadata to provide governance capabilities. This metadata includes load IDs, which consist of a timestamp and pipeline name. Load IDs enable incremental transformations and data vaulting by 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. Schemas define the structure of normalized data and guide the processing and loading of data. By adhering to predefined schemas, pipelines maintain data integrity and facilitate standardized data handling practices. Read more: Adjust a schema docs.
  • Schema Evolution: dlt enables proactive governance by alerting users to schema changes. When modifications occur in the source data’s schema, such as table or column alterations, dlt notifies stakeholders, allowing them to take necessary actions, such as reviewing and validating the changes, updating downstream processes, or performing impact analysis.
  • Scaling and Finetuning: dlt offers several mechanisms and configuration options to scale up and finetune pipelines: running extraction, normalization, and load in parallel; writing sources and resources that are run in parallel via thread pools and async execution; finetuning the memory buffers, intermediary file sizes, and compression options. Read more about performance.
  • Advanced Topics: dlt is a constantly growing library that supports many features and use cases needed by the community. Join our Slack to find recent releases or discuss what you can build with dlt. Learn more: build-a-pipeline-tutorial.

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 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 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 The Local Filesystem 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 use GitHub Actions to deploy your dlt pipelines effortlessly. Follow the guide here.
  • Deploy with Airflow: Utilize Airflow and Google Composer for managing your dlt pipelines. Detailed instructions can be found here.
  • Deploy with Google Cloud Functions: Discover how to deploy your dlt pipelines using Google Cloud Functions by following the guide here.
  • Explore other deployment methods: Check out additional ways 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 and quick identification of issues. Read more
  • Set up alerts: Setting up alerts can help you stay informed about the status of your dlt pipeline, enabling you to take immediate action when something goes wrong. Read more
  • And set up tracing: Implement tracing to capture detailed information about the execution of your dlt pipeline, which can be invaluable for 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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