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Data pipelines

Collect, validate, store, and transform data into repeatable results.

By the end of this path

Set data-quality rules and build a pipeline that can be rerun and verified safely.

Before you start

Basic SQL and the flow of reading and writing data from a program are helpful.

Learning sequence

  1. 1

    Getting Started with a Dev Environment

    Beginner

    From turning on the computer to running your first code. A 5-step climb for beginners.

    5 stepsStart →
  2. 2

    Python · FastAPI · Data Pipelines

    Intermediate

    One language, end-to-end: API, scheduling, external data, observability, practical patterns.

    8 stepsStart →
  3. 3

    Building public-data crawlers

    Intermediate

    Build an ethical crawler in six steps with Playwright, http_utils, and APScheduler.

    6 stepsStart →
  4. 4

    PostgreSQL in depth + Redis · Kafka

    Advanced

    Ten steps to a real data platform — indexes, caching, event streams.

    10 stepsStart →
Start with Getting Started with a Dev Environment →