Implement JSON type support #330
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…Frame, dict, and PyReader - Implemented support for querying JSON columns across various data sources including pyarrow Table, DataFrame, dictionary, and PyReader. - Added corresponding test cases to validate the querying functionality for each data type. - Enhanced the display format of run_all.py.
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Changelog entry (a user-readable short description of the changes that goes to CHANGELOG.md):
This PR introduces support for mapping Python objects to ClickHouse JSON type.
Pandas DataFrame: Columns of object type are automatically sampled. If all sampled values are of type dict, the column is mapped to JSON type.
Python Dict: If the first row of a column is a dict, the column is mapped to JSON type.
PyArrow Table: If a column is of struct type in PyArrow, it will be mapped to JSON type.
Custom PyReader: Users can explicitly specify a schema name of JSON for a given column, which will be used accordingly.
Numpy: JSON type is currently not supported for Numpy arrays.
Output Formats: When using output formats such as Arrow, Protobuf, or Parquet, JSON type is temporarily disabled due to ClickHouse limitations.
Additionally, this PR supports SQL queries that involve multiple Python objects within the same query.
The detection of Pandas DataFrame objects is now done via an import-based check, improving compatibility and reliability.
Documentation entry for user-facing changes
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