Loading Data from `Crypt API` to `Databricks` with `dlt` in Python

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Crypt API is a versatile cryptocurrency payments API that allows businesses to accept payments in various cryptocurrencies with ease. It provides a secure and simple interface for integrating cryptocurrency transactions into your platform. With features such as real-time exchange rates, automated payment processing, and support for multiple cryptocurrencies, Crypt API helps businesses expand their payment options and reach a broader audience in the crypto space. This documentation will guide you through the process of loading data from Crypt API to Databricks using the open-source Python library dlt. Databricks is a unified data analytics platform, from the original creators of Apache Spark™, that accelerates innovation by unifying data science, engineering, and business. For more information on Crypt API, visit their website.

`dlt` Key Features

Automated Maintenance: With schema inference, evolution, and alerts, maintenance becomes simple. Learn more
Run Anywhere Python Runs: dlt can run on Airflow, serverless functions, and notebooks without needing external APIs, backends, or containers. Learn more
User-Friendly Interface: The declarative interface is designed to be accessible for beginners while empowering senior professionals. Learn more
Scalability: dlt offers mechanisms like parallel extraction, normalization, and loading to handle large datasets efficiently. Learn more
Governance Support: Robust governance through pipeline metadata, schema enforcement, and schema change alerts. Learn more

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

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

1.1. Tweak crypt_api/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 crypt_api source will look like this:

Click to view full file (148 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="crypt_api_source", max_table_nesting=2)
def crypt_api_source(
        base_url: str = dlt.config.value,
) -> List[DltResource]:

    # source configuration
    source_config: RESTAPIConfig = {
        "client": {
            "base_url": base_url,
        },
        "resources": 
        [
        # This method allows for seamless conversion of prices between FIAT currencies and cryptocurrencies, as well as between different cryptocurrencies. **Note:**   * Prices are fetched every 5 minutes from CoinMarketCap.
        {
            "name": "convert",
            "table_name": "convert",
            "endpoint": {
                "data_selector": "$",
                "path": "/{ticker}/convert/",
                "params": {
                    "ticker": "FILL_ME_IN", # TODO: fill in required path parameter
                    "value": "FILL_ME_IN", # TODO: fill in required query parameter
                    "from": "FILL_ME_IN", # TODO: fill in required query parameter

                },
                "paginator": "auto",
            }
        },
        # This method is used to generate a new address to give your clients, where they can send payments.  **Please make sure when sending a transaction you <a href="https://cryptapi.io/cryptocurrencies/" target="_blank">consult the minimum transfer value</a> for the crypto/token you wish to use. If the value you send is bellow our minimums, CryptAPI will ignore the transaction.**  Before delving into the documentation, why not check if the <a href="https://cryptapi.io/libraries/" target="_blank">libraries</a> already have the functionality you need? It could save you time and effort in the long run!  **Notice:** The length of this request can't surpass the ```8192``` characters! 
        {
            "name": "create",
            "table_name": "create",
            "endpoint": {
                "data_selector": "$",
                "path": "/{ticker}/create/",
                "params": {
                    "ticker": "FILL_ME_IN", # TODO: fill in required path parameter
                    "callback": "FILL_ME_IN", # TODO: fill in required query parameter
                    "address": "FILL_ME_IN", # TODO: fill in required query parameter
                    # the parameters below can optionally be configured
                    # "pending": "0",
                    # "confirmations": "1",
                    # "email": "OPTIONAL_CONFIG",
                    # "post": "0",
                    # "json": "0",
                    # "priority": "default",
                    # "multi_token": "0",
                    # "multi_chain": "0",
                    # "convert": "0",

                },
                "paginator": "auto",
            }
        },
        # Endpoint that provides information regarding CryptAPI Service (e.g supported blockchains, cryptocurrencies and tokens). 
        {
            "name": "cryptapi_info",
            "table_name": "cryptapi_info",
            "endpoint": {
                "data_selector": "$",
                "path": "/info/",
                "params": {
                    # the parameters below can optionally be configured
                    # "prices": "0",

                },
                "paginator": "auto",
            }
        },
        # <br/> This method allows you to estimate blockchain fees to process a transaction.  **Notes:**   * This is an **estimation** only, and might change significantly when the transaction is processed. CryptAPI   is not responsible if blockchain fees when forwarding the funds differ from this estimation.   * These not include CryptAPI's fees. 
        {
            "name": "estimate",
            "table_name": "estimate",
            "endpoint": {
                "data_selector": "$",
                "path": "/{ticker}/estimate/",
                "params": {
                    "ticker": "FILL_ME_IN", # TODO: fill in required path parameter
                    # the parameters below can optionally be configured
                    # "addresses": "1",
                    # "priority": "default",

                },
                "paginator": "auto",
            }
        },
        # This endpoint is used to fetch information of the cryptocurrency/token you provided in the <a href="#operation/info!in=path&path=ticker&t=request"><code>ticker</code></a> parameter. 
        {
            "name": "info",
            "table_name": "info",
            "endpoint": {
                "data_selector": "$",
                "path": "/{ticker}/info/",
                "params": {
                    "ticker": "FILL_ME_IN", # TODO: fill in required path parameter
                    # the parameters below can optionally be configured
                    # "prices": "1",

                },
                "paginator": "auto",
            }
        },
        # <br/> This method provides valuable information and callbacks for addresses that are created through the <a href="#operation/create"><code>create</code></a> endpoint.  It allows users to retrieve a list of callbacks made at the specified <a href="#operation/logs!c=200&path=callbacks&t=response"><code>callbacks</code></a> parameter, allows to track payment activity and troubleshoot any issues that may arise. 
        {
            "name": "log_items",
            "table_name": "log_items",
            "endpoint": {
                "data_selector": "callbacks",
                "path": "/{ticker}/logs/",
                "params": {
                    "ticker": "FILL_ME_IN", # TODO: fill in required path parameter
                    "callback": "FILL_ME_IN", # TODO: fill in required query parameter

                },
                "paginator": "auto",
            }
        },
        # This method generates a base64-encoded QR Code image for payments. 
        {
            "name": "qrcode",
            "table_name": "qrcode",
            "endpoint": {
                "data_selector": "$",
                "path": "/{ticker}/qrcode/",
                "params": {
                    "ticker": "FILL_ME_IN", # TODO: fill in required path parameter
                    "address": "FILL_ME_IN", # TODO: fill in required query parameter
                    # the parameters below can optionally be configured
                    # "value": "OPTIONAL_CONFIG",
                    # "size": "512",

                },
                "paginator": "auto",
            }
        },
        ]
    }

    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.crypt_api]
# Base URL for the API
base_url = "https://api.cryptapi.io"

generated secrets.toml

[sources.crypt_api]
# secrets for your crypt_api source
# example_api_key = "example value"

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 crypt_api_pipeline.py to databricks 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 Databricks 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 crypt_api_pipeline.py, as well as a folder crypt_api 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 crypt_api import crypt_api_source


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

4. Inspecting your load result

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

dlt pipeline crypt_api_pipeline info

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

# install streamlit
pip install streamlit
# run the streamlit app for your pipeline with the dlt cli:
dlt pipeline crypt_api_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 dlt pipeline using GitHub Actions for CI/CD automation. Follow the guide here.
Deploy with Airflow: Use Google Composer or any Airflow instance to deploy your dlt pipeline. Detailed instructions can be found here.
Deploy with Google Cloud Functions: Set up serverless deployment of your dlt pipeline using Google Cloud Functions by following this guide here.
Explore other deployment options: Discover various other methods to deploy your dlt pipelines, including AWS Lambda and more, by exploring the resources here.

The running in production section will teach you about:

How to Monitor your pipeline: Learn how to effectively monitor your dlt pipelines to ensure they are running smoothly and efficiently. How to Monitor your pipeline
Set up alerts: Set up alerts to get notified about any issues or important events in your dlt pipelines. Set up alerts
And set up tracing: Implement tracing to track the flow and performance of your dlt pipelines for better debugging and optimization. And set up tracing

Available Sources and Resources

For this verified source the following sources and resources are available

Source `Crypt API`

Provides cryptocurrency information, conversion estimates, QR codes, and transaction logs.

Resource Name	Write Disposition	Description
`cryptapi_info`	`append`	Provides general information about the Crypt API service.
`estimate`	`append`	Estimates the value of a cryptocurrency transaction based on real-time exchange rates.
`convert`	`append`	Converts amounts between different cryptocurrencies using real-time exchange rates.
`qrcode`	`append`	Generates QR codes for cryptocurrency payment addresses to facilitate easy payments.
`create`	`append`	Creates new cryptocurrency payment addresses for transactions.
`info`	`append`	Retrieves detailed information about specific cryptocurrency transactions.
`log_items`	`append`	Logs transaction details and activities for tracking and auditing purposes.

Loading Data from `Crypt API` to `Databricks` with `dlt` in Python

`dlt` Key Features

Getting started with your pipeline locally

0. Prerequisites

1. Install dlt and dlt-init-openapi

1.1. Tweak crypt_api/init.py

2. Configuring your source and destination credentials

generated config.toml

generated secrets.toml

2.1. Adjust the generated code to your usecase

3. Running your pipeline for the first time

4. Inspecting your load result

5. Next steps to get your pipeline running in production

The Deploy section will show you how to deploy your pipeline to

The running in production section will teach you about:

Available Sources and Resources

Source `Crypt API`

Additional pipeline guides

DHelp

Ask a question

Loading Data from Crypt API to Databricks with dlt in Python

dlt Key Features​

Getting started with your pipeline locally​

0. Prerequisites​

1. Install dlt and dlt-init-openapi​

1.1. Tweak crypt_api/__init__.py​

2. Configuring your source and destination credentials​

generated config.toml​

generated secrets.toml​

2.1. Adjust the generated code to your usecase​

3. Running your pipeline for the first time​

4. Inspecting your load result​

5. Next steps to get your pipeline running in production​

The Deploy section will show you how to deploy your pipeline to​

The running in production section will teach you about:​

Available Sources and Resources​

Source Crypt API​

Additional pipeline guides​

DHelp

Ask a question

Loading Data from `Crypt API` to `Databricks` with `dlt` in Python

`dlt` Key Features

Getting started with your pipeline locally

0. Prerequisites

1. Install dlt and dlt-init-openapi

1.1. Tweak crypt_api/init.py

2. Configuring your source and destination credentials

generated config.toml

generated secrets.toml

2.1. Adjust the generated code to your usecase

3. Running your pipeline for the first time

4. Inspecting your load result

5. Next steps to get your pipeline running in production

The Deploy section will show you how to deploy your pipeline to

The running in production section will teach you about:

Available Sources and Resources

Source `Crypt API`

Additional pipeline guides