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Loading Data from Crypt API to CockroachDB Using dlt in Python

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

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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 loading data from Crypt API to CockroachDB using the open-source python library dlt. CockroachDB offers a simple, reliable SQL API and is distributed, cloud-native, Kubernetes compatible, and free up to 5GB and 1vCPU. Further information about Crypt API can be found at cryptapi.io.

dlt Key Features

  • Fetching data from the GitHub API: Learn how to efficiently fetch data from the GitHub API using dlt. Read more
  • Understanding and managing data loading behaviors: Understand how to manage data loading behaviors, including appending or replacing data. Read more
  • Incrementally loading new data and deduplicating existing data: Learn how to incrementally load new data and deduplicate existing data. Read more
  • Making our data fetch more dynamic and reducing code redundancy: Discover ways to make data fetching more dynamic and reduce code redundancy. Read more
  • Securely handling secrets: Understand how to securely handle secrets within your data pipeline. Read 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 postgres 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 CockroachDB 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 CockroachDB 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 your dlt pipeline using Github Actions.
  • Deploy with Airflow: Follow this guide to deploy your dlt pipeline with Airflow.
  • Deploy with Google Cloud Functions: Check out how to deploy your dlt pipeline using Google Cloud Functions.
  • Explore other deployment options: Discover various ways to deploy your dlt pipeline by visiting this page.

The running in production section will teach you about:

  • How to Monitor your pipeline: Learn how to effectively monitor your dlt pipelines to ensure smooth operations and quick troubleshooting. Read more
  • Set up alerts: Configure alerts to stay informed about the status and health of your dlt pipelines. Read more
  • Set up tracing: Implement tracing to track the flow and performance of your data through dlt pipelines. Read more

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 NameWrite DispositionDescription
cryptapi_infoappendProvides general information about the Crypt API service.
estimateappendEstimates the value of a cryptocurrency transaction based on real-time exchange rates.
convertappendConverts amounts between different cryptocurrencies using real-time exchange rates.
qrcodeappendGenerates QR codes for cryptocurrency payment addresses to facilitate easy payments.
createappendCreates new cryptocurrency payment addresses for transactions.
infoappendRetrieves detailed information about specific cryptocurrency transactions.
log_itemsappendLogs transaction details and activities for tracking and auditing purposes.

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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