Stream Your Data Using Nothing But Python’s Requests Library

The Forgotten Streaming Library Hidden In Python

When you think of building streaming data pipelines you likely think of using a library like Apache Kafka that is tailor-made for streaming.

Cloud platforms like Google Cloud Platforms (GCP) and Amazon Web Services (AWS) support the streaming of data into their respective SQL environments. GCP, in particular, even provides services like the Billing API or Google Analytics connections that stream source data on a recurring basis.

On top of the infrastructure giants countless third-party “code-less” platforms have taken on the heavy lifting of setting up, maintaining and scaling streaming infrastructure.

Even though third parties sell platforms that will alleviate the “challenging” builds like streaming pipelines, as a data engineer, it is still important to know how to configure a streaming pipeline.

But going from creating relatively simple batch load jobs to configuring dynamic streaming pipelines can be, understandably, intimidating.

Aside from not understanding the concept of streaming data, it can be difficult to even know where to begin when creating such pipelines.

Enter your Fisher-Price “My First Streaming Pipeline”: Requests.

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