feat: Add dy.infer_schema

[gab23r]

Fixes: #232

• Add dy.infer_schema() function to generate dataframely schema code from a Polars DataFrame
• Supports three output modes via return_type parameter:
  • None (default): prints schema to stdout for quick exploration
  • "string": returns schema code as a string
  • "schema": returns an actual Schema class for direct use
• Handles all Polars types including nested types (List, Array, Struct) with proper inner nullability detection
• Automatically handles invalid Python identifiers and keywords using aliases

This add the

>>> import polars as pl
>>> import dataframely as dy
>>> df = pl.DataFrame({
...     "name": ["Alice", "Bob"],
...     "age": [25, 30],
...     "score": [95.5, None],
... })
>>> dy.infer_schema(df, "PersonSchema")
class PersonSchema(dy.Schema):
    name = dy.String()
    age = dy.Int64()
    score = dy.Float64(nullable=True)
>>> schema = dy.infer_schema(df, "PersonSchema", return_type="schema")
>>> schema.is_valid(df)
True

Not supported (potential future enhancements)

• Assess min/max length of string values to suggest min_length/max_length constraints
• Suggest Enum if there are fewer than 10-20 distinct string values in a column
• Suggest Categorical if there are 50-100 distinct string values in a dataframe with >100k rows

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 100.00%. Comparing base (b3edd6a) to head (7ee32cf).
⚠️ Report is 1 commits behind head on main.

Additional details and impacted files

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  Coverage   100.00%   100.00%            
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  Files           54        55     +1     
  Lines         3121      3250   +129     
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+ Hits          3121      3250   +129     

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[Copilot]

Pull request overview

This PR adds a new dy.infer_schema() function (addressing Issue #232) that generates dataframely schema code from a Polars DataFrame. The function inspects a DataFrame's column types and null counts to produce schema class definitions with appropriate column types and nullable annotations.

Changes:

• New dataframely/_generate_schema.py module implementing infer_schema() with three return modes (print to stdout, return as string, or return as an executable Schema class), plus supporting helper functions for code generation.
• Public API export of infer_schema in dataframely/__init__.py.
• New test file tests/test_infer_schema.py covering basic types, nullable detection, datetime types, nested types, invalid identifiers, and round-trip validation.

Reviewed changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 6 comments.

File	Description
dataframely/_generate_schema.py	New module with infer_schema() function and helpers for inferring schema from DataFrame columns, handling type mapping, identifier sanitization, and code generation.
dataframely/__init__.py	Exports infer_schema in the public API (import and __all__).
tests/test_infer_schema.py	Tests for string output mode across all supported types and round-trip validation via schema return mode.

[gab23r]

hello @borchero, does this implementation is close to something mergable ?