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Loading Data from Notion to Neon Serverless Postgres with dlt in Python

tip

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

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Loading data from Notion to Neon Serverless Postgres using the open-source Python library dlt allows you to seamlessly integrate your workspace with a powerful, scalable database. Notion is a versatile platform where you can capture thoughts, manage projects, and run entire operations. Neon Serverless Postgres offers the reliability and scalability of PostgreSQL on a serverless platform, helping you build robust applications faster. By leveraging dlt, you can efficiently extract data from Notion and load it into Neon Serverless Postgres, ensuring data consistency and integrity. For more details about Notion, visit here.

dlt Key Features​

  • Governance Support: dlt pipelines offer robust governance support through metadata utilization, schema enforcement, and schema change alerts. Learn more
  • Schema Evolution: dlt enables proactive governance by alerting users to schema changes, ensuring data consistency and quality. Read more
  • Scalability: dlt offers mechanisms and configuration options to scale up and finetune pipelines, including parallel execution and memory management. Read more about performance
  • Data Types: dlt supports a variety of data types, ensuring compatibility with different data sources and destinations. Explore supported data types
  • Data Extraction: dlt provides scalable data extraction through iterators, chunking, and parallelization, along with implicit extraction DAGs for efficient data processing. Learn how to extract data

Getting started with your pipeline locally​

0. Prerequisites​

dlt requires Python 3.8 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​

First you need to install the dlt library with the correct extras for Neon Serverless Postgres:

pip install "dlt[postgres]"

The dlt cli has a useful command to get you started with any combination of source and destination. For this example, we want to load data from Notion to Neon Serverless Postgres. You can run the following commands to create a starting point for loading data from Notion to Neon Serverless Postgres:

# create a new directory
mkdir notion_pipeline
cd notion_pipeline
# initialize a new pipeline with your source and destination
dlt init notion postgres
# install the required dependencies
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[postgres]>=0.3.5

You now have the following folder structure in your project:

notion_pipeline/
├── .dlt/
│   ├── config.toml          # configs for your pipeline
│   └── secrets.toml         # secrets for your pipeline
├── notion/                   # folder with source specific files
│   └── ...
├── notion_pipeline.py        # your main pipeline script
├── requirements.txt         # dependencies for your pipeline
└── .gitignore               # ignore files for git (not required)

2. Configuring your source and destination credentials​

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​

# put your configuration values here

[runtime]
log_level="WARNING"  # the system log level of dlt
# use the dlthub_telemetry setting to enable/disable anonymous usage data reporting, see https://dlthub.com/docs/telemetry
dlthub_telemetry = true

generated secrets.toml​

# put your secret values and credentials here. do not share this file and do not push it to github

[sources.notion]
api_key = "api_key" # please set me up!

[destination.postgres]
dataset_name = "dataset_name" # please set me up!

[destination.postgres.credentials]
database = "database" # please set me up!
password = "password" # please set me up!
username = "username" # please set me up!
host = "host" # please set me up!
port = 5432
connect_timeout = 15

2.1. Adjust the generated code to your usecase​

Further help setting up your source and destinations
  • Read more about setting up the Notion source in our docs.
  • Read more about setting up the Neon Serverless Postgres 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 notion_pipeline.py, as well as a folder notion 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 notion import notion_databases


def load_databases() -> None:
    """Loads all databases from a Notion workspace which have been shared with
    an integration.
    """
    pipeline = dlt.pipeline(
        pipeline_name="notion",
        destination='postgres',
        dataset_name="notion_data",
    )

    data = notion_databases()

    info = pipeline.run(data)
    print(info)


if __name__ == "__main__":
    load_databases()

Provided you have set up your credentials, you can run your pipeline like a regular python script with the following command:

python notion_pipeline.py

4. Inspecting your load result​

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

dlt pipeline notion info

You can also use streamlit to inspect the contents of your Neon Serverless Postgres destination for this:

# install streamlit
pip install streamlit
# run the streamlit app for your pipeline with the dlt cli:
dlt pipeline notion 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 your dlt pipeline using GitHub Actions for automated workflows. Follow the guide here.
  • Deploy with Airflow and Google Composer: Set up your dlt pipeline to run on Airflow using Google Composer. Detailed instructions can be found here.
  • Deploy with Google Cloud Functions: Use Google Cloud Functions to deploy your dlt pipeline. The step-by-step process is available here.
  • Explore other deployment options: Discover additional methods to deploy your dlt pipeline by checking out the comprehensive list here.

The running in production section will teach you about:​

  • How to Monitor your pipeline: Learn how to keep track of your pipeline's performance and health by following the guide on How to Monitor your pipeline.
  • Set up alerts: Ensure you are notified of any critical issues or important events in your pipeline by setting up alerts. Follow the instructions in the Set up alerts guide.
  • Set up tracing: Understand the flow and execution of your pipeline by enabling tracing. Detailed steps can be found in the And set up tracing guide.

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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