Getting started with PyIceberg PyIceberg is a Python implementation for accessing Iceberg tables, without the need of a JVM. Installation Before installing PyIceberg, make sure that you're on an up-to …

PyIceberg supports full schema evolution through the Python API. It takes care of setting the field-IDs and makes sure that only non-breaking changes are done (can be overridden).

PyIceberg uses multiple threads to parallelize operations. The number of workers can be configured by supplying a max-workers entry in the configuration file, or by setting the …

Pyiceberg comes with a CLI that's available after installing the pyiceberg package. You can pass the path to the Catalog using the --uri and --credential argument, but it is recommended to setup a …

Load the table's metadata and returns the table instance. You can also use this method to check for table existence using 'try catalog.table () except NoSuchTableError'. Note: This method doesn't scan …

commit_transaction() ¶ Commit the changes to the catalog. In the case of a CreateTableTransaction, the only requirement is AssertCreate. Returns: The table with the updates applied. Source code in …

Return the equivalent struct field by name or id in the partner struct. Source code in pyiceberg/schema.py 633 634 635

Bases: PrimitiveType A Date data type in Iceberg can be represented using an instance of this class. Dates in Iceberg are calendar dates without a timezone or time. Example column_foo = DateType () …

Validate that a partition field name doesn't conflict with schema field names. Source code in pyiceberg/partitioning.py

This for method chaining Source code in pyiceberg/table/update/schema.py 134 135 136 137 138 139 140 141 142 143 144