How to Build an ETL App for Alchemy Data in Python with CData

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python and the petl framework, you can build Alchemy-connected applications and pipelines for extracting, transforming, and loading Alchemy data. This article shows how to connect to Alchemy with the CData Python Connector and use petl and pandas to extract, transform, and load Alchemy data.

With built-in, optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Alchemy data in Python. When you issue complex SQL queries from Alchemy, the driver pushes supported SQL operations, like filters and aggregations, directly to Alchemy and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to Alchemy Data

Connecting to Alchemy data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Start by setting the Profile connection property to the location of the Alchemy Profile on disk (e.g. C:\profiles\Alchemy.apip). Next, set the ProfileSettings connection property to the connection string for Alchemy (see below).

Alchemy API Profile Settings

Alchemy uses API key authentication. The API key is supplied in the request URL path. To obtain an API key:

1. Sign in to your Alchemy account at https://dashboard.alchemy.com.
2. Open an existing app or create a new one.
3. Copy the app's API key from the API Key dialog.

After obtaining your API key, set the following connection properties:

• AuthScheme: Set this to APIKey.
• Network: Optional. The blockchain network slug for NFT API requests (for example, eth-mainnet, base-mainnet, polygon-mainnet). Defaults to eth-mainnet.

Set the following in the ProfileSettings connection property:

• APIKey: Set this to your Alchemy app API key.

After installing the CData Alchemy Connector, follow the procedure below to install the other required modules and start accessing Alchemy through Python objects.

Install Required Modules

Use the pip utility to install the required modules and frameworks:

pip install petl
pip install pandas

Build an ETL App for Alchemy Data in Python

Once the required modules and frameworks are installed, we are ready to build our ETL app. Code snippets follow, but the full source code is available at the end of the article.

First, be sure to import the modules (including the CData Connector) with the following:

import petl as etl
import pandas as pd
import cdata.api as mod

You can now connect with a connection string. Use the connect function for the CData Alchemy Connector to create a connection for working with Alchemy data.

cnxn = mod.connect("Profile=C:\profiles\Alchemy.apip;AuthScheme=APIKey;Network=eth-mainnet;ProfileSettings='APIKey=your_api_key';")

Create a SQL Statement to Query Alchemy

Use SQL to create a statement for querying Alchemy. In this article, we read data from the ContractsForOwner entity.

sql = "SELECT Address, Name FROM ContractsForOwner WHERE Owner = '0xd8dA6BF26964aF9D7eEd9e03E53415D37aA96045'"

Extract, Transform, and Load the Alchemy Data

With the query results stored in a DataFrame, we can use petl to extract, transform, and load the Alchemy data. In this example, we extract Alchemy data, sort the data by the Name column, and load the data into a CSV file.

Loading Alchemy Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Name')

etl.tocsv(table2,'contractsforowner_data.csv')

With the CData API Driver for Python, you can work with Alchemy data just like you would with any database, including direct access to data in ETL packages like petl.

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to Alchemy data. Reach out to our Support Team if you have any questions.

Full Source Code

import petl as etl
import pandas as pd
import cdata.api as mod

cnxn = mod.connect("Profile=C:\profiles\Alchemy.apip;AuthScheme=APIKey;Network=eth-mainnet;ProfileSettings='APIKey=your_api_key';")

sql = "SELECT Address, Name FROM ContractsForOwner WHERE Owner = '0xd8dA6BF26964aF9D7eEd9e03E53415D37aA96045'"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'Name')

etl.tocsv(table2,'contractsforowner_data.csv')