Week 3 - Ingesting and Validating Data

Introduction to Data Ingestion

Ingesting from APIs

Reading Multiple File Formats

Pydantic for Data Validation

Writing to Databases

Error Handling and Logging

Practice

Assignment

Gotchas & Pitfalls

• Teachers

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5. Data Validation with Pydantic

Content coming soon...

Suggested Topics

• What is Pydantic and why it's powerful for data validation
• Defining models: fields, types, constraints
• Built-in validators: email, URL, integer ranges, string patterns
• Custom validators: implementing business logic checks
• Type coercion: automatic conversion (str → int, etc.)
• Error reporting: getting detailed validation failure information
• Normalization: using validators to clean and standardize data
• Handling optional fields: defaults, required vs optional, nullable
• Rejecting invalid records: strategies for reporting bad data
• Integration: using Pydantic models in your ingestion pipeline

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