add pyairbyte blog

docs/website/blog/2024-02-28-what-is-pyairbyte.md

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+---
+slug: what-is-pyairbyte
+title: "PyAirbyte - what it is and what it’s not"
+image:  https://storage.googleapis.com/dlt-blog-images/pysquid.png
+authors:
+  name: Adrian Brudaru
+  title: Open source Data Engineer
+  url: https://github.com/adrianbr
+  image_url: https://avatars.githubusercontent.com/u/5762770?v=4
+tags: [data observability, data pipeline observability]
+---
+
+## Intro
+
+Here at dltHub, we work on the python library for data ingestion. So when I heard from Airbyte that they are building a library, I was intrigued and decided to investigate.
+
+# What is PyAirbyte?
+
+PyAirbyte is an interesting Airbyte’s initiative - similar to the one that Meltano had undertook 3 years ago. It provides a convenient way to download and install Airbyte sources and run them locally storing the data in a cache dataset. Users are allowed to then read the data from this cache.
+
+A Python wrapper on the Airbyte source is quite nice and has a feeling close to [Alto]. The whole process of cloning/pip installing the repository, spawning a separate process to run Airbyte connector and read the data via UNIX pipe is hidden behind Pythonic interface.
+
+Note that this library is not an Airbyte replacement - the loaders of Airbyte and the library are very different. The library loader uses pandas.to_sql and sql alchemy and is not a replacement for Airbyte destinations that are available in Open Source Airbyte
+
+# Questions I had, answered
+
+- Can I run Airbyte sources with PyAirbyte? A subset of them.
+- Can I use PyAirbyte to run a demo pipeline in a colab notebook? Yes.
+- Would my colab demo have a compatible schema with Airbyte? No.
+- Is PyAirbyte a replacement for Airbyte? No.
+- Can I use PyAirbyte to develop or test during development Airbyte sources? No.
+- Can I develop pipelines with PyAirbyte? no
+
+# In conclusion
+
+In wrapping up, it's clear that PyAirbyte is a neat little addition to the toolkit for those of us who enjoy tinkering with data in more casual or exploratory settings. I think this is an interesting initiative from Airbyte that will enable new usage patterns.
+
+### Want to discuss?
+
+[Join our slack community](https://dlthub.com/community) to take part in the conversation.