How to Build an ETL App for Hacker News 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 Hacker News-connected applications and pipelines for extracting, transforming, and loading Hacker News data. This article shows how to connect to Hacker News with the CData Python Connector and use petl and pandas to extract, transform, and load Hacker News data.

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

Connecting to Hacker News Data

Connecting to Hacker News 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.

Connecting to HackerNews

The HackerNews API (powered by Firebase) is a public API that requires no authentication. You can connect and query data immediately without any credentials.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to None.

Example connection string:

Profile=C:\profiles\HackerNews.apip;AuthScheme=None

After installing the CData Hacker News Connector, follow the procedure below to install the other required modules and start accessing Hacker News 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 Hacker News 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 Hacker News Connector to create a connection for working with Hacker News data.

cnxn = mod.connect("Profile=C:\profiles\HackerNews.apip;AuthScheme=None")

Create a SQL Statement to Query Hacker News

Use SQL to create a statement for querying Hacker News. In this article, we read data from the TopStories entity.

sql = "SELECT , FROM TopStories WHERE = ''"

Extract, Transform, and Load the Hacker News Data

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

Loading Hacker News Data into a CSV File

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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

With the CData API Driver for Python, you can work with Hacker News 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 Hacker News data. Reach out to our Support Team if you have any questions.

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Full Source Code

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

cnxn = mod.connect("Profile=C:\profiles\HackerNews.apip;AuthScheme=None")

sql = "SELECT , FROM TopStories WHERE = ''"

table1 = etl.fromdb(cnxn,sql)

table2 = etl.sort(table1,'')

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