[FLINK-40187][python] Introduce DataType class in DataFrame API

[auroflow]

What is the purpose of the change

This pull request completes the DataType API for the PyFlink DataFrame API. It provides the scalar, temporal, and composite data types required by subsequent DataFrame operations.

Brief change log

• Add scalar, temporal, and composite DataType factory methods.
• Add nullability modifiers and a readable representation for DataType.
• Add internal helpers for inferring data types from Python type hints and parsing SQL type strings.
• Preserve timestamp precision and support NULL when converting Java data types to Python data types.
• Extend the DataFrame API reference documentation.
• Add focused tests for factories, nullability, nested types, type inference, SQL parsing, equality, hashing, and representation.

Verifying this change

This change added tests and can be verified as follows:

• Ran the complete DataFrame test suite:
  • .venv/bin/python -m pytest -q flink-python/pyflink/dataframe/tests
  • Result: 94 passed
• Ran flake8 checks for all changed Python files.
• Compiled all changed Python files with py_compile.
• Ran mvn -T 12 spotless:check through the pre-push hook.

Does this pull request potentially affect one of the following parts:

• Dependencies (does it add or upgrade a dependency): no
• The public API, i.e., is any changed class annotated with @Public(Evolving): yes
• The serializers: no
• The runtime per-record code paths (performance sensitive): no
• Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Kubernetes/Yarn, ZooKeeper: no
• The S3 file system connector: no

Documentation

• Does this pull request introduce a new feature? yes
• If yes, how is the feature documented? docs and Python API docstrings

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Was generative AI tooling used to co-author this PR?

• Yes (OpenAI Codex)

Generated-by: OpenAI Codex (GPT-5.6 Sol)

[flinkbot]

CI report:

• d8682e9 Azure: SUCCESS

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