Loading Data from Crypt API
to Google Cloud Storage
with dlt
Join our Slack community or book a call with our support engineer Violetta.
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. This documentation will guide you on how to load data from Crypt API
to Google Cloud Storage
using the open-source Python library dlt
. The Google Cloud Storage
destination stores data on the Google Cloud Platform, enabling you to easily create data lakes. You can upload data as JSONL, Parquet, or CSV. With features like real-time exchange rates, automated payment processing, and support for multiple cryptocurrencies, Crypt API
helps businesses expand their payment options. For more information about Crypt API
, visit cryptapi.io.
dlt
Key Features
- Pipeline Metadata:
dlt
pipelines utilize metadata to provide governance capabilities, including load IDs for data lineage and traceability. Read more - Schema Enforcement and Curation: Ensure data consistency and quality by enforcing and curating schemas within
dlt
pipelines. Read more - Schema Evolution Alerts: Get notified of schema changes in source data, allowing for proactive governance and impact analysis. Read more
- Scaling and Finetuning:
dlt
offers various mechanisms to scale up and finetune your pipelines, including parallel processing and memory buffer adjustments. Read more - Filesystem & Buckets: Store data in remote file systems and bucket storages like S3, Google Storage, or Azure Blob Storage using
dlt
. 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 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
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
.
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
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 filesystem and supply the credentials as outlined in the destination doc linked below.
The default filesystem destination is configured to connect to AWS S3. To load to Google Cloud Storage, update the [destination.filesystem.credentials]
section in your secrets.toml
.
[destination.filesystem.credentials]
client_email="Please set me up!"
private_key="Please set me up!"
project_id="Please set me up!"
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 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 Google Cloud Storage
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 set up continuous deployment using GitHub Actions with
dlt
. Follow the guide here. - Deploy with Airflow and Google Composer: Use Airflow and Google Composer to manage and schedule your
dlt
pipelines. Detailed instructions can be found here. - Deploy with Google Cloud Functions: Leverage Google Cloud Functions for serverless deployment of your
dlt
pipelines. Follow the steps here. - Explore other deployment methods: Discover various other methods to deploy your
dlt
pipelines by checking out the comprehensive guides here.
The running in production section will teach you about:
- How to Monitor your pipeline: Learn how to effectively monitor your
dlt
pipeline to ensure smooth operations and quickly identify any issues. How to Monitor your pipeline - Set up alerts: Set up alerts to get notified about the status and performance of your
dlt
pipelines. Set up alerts - Set up tracing: Implement tracing to get detailed insights into the execution of your
dlt
pipelines. 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. |
Additional pipeline guides
- Load data from Box Platform API to Snowflake in python with dlt
- Load data from Bitbucket to ClickHouse in python with dlt
- Load data from Keap to MotherDuck in python with dlt
- Load data from Microsoft SQL Server to Google Cloud Storage in python with dlt
- Load data from GitLab to Timescale in python with dlt
- Load data from Airtable to Supabase in python with dlt
- Load data from Trello to CockroachDB in python with dlt
- Load data from Jira to Databricks in python with dlt
- Load data from Adobe Analytics to BigQuery in python with dlt
- Load data from MongoDB to EDB BigAnimal in python with dlt