Merge branch 'kevinliu/test' into kevinjqliu/fix-schema-comparison

Author: kevinjqliu

mkdocs/docs/configuration.md

@@ -265,15 +265,6 @@ catalog:
 The In-Memory catalog uses in-memory data-structures to store information.
 This is useful for test, demo, and playground. Do not use in production as the data is not persisted.
 
-While you can specify In-Memory catalog in the configuration file like this, it is not recommended since information is only persisted for the duration of the function call.
-
-```yaml
-catalog:
-  default:
-    type: in_memory
-    warehouse: /tmp/warehouse # default warehouse location
-```
-
 # Concurrency
 
 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_MAX_WORKERS` environment variable. The default value depends on the system hardware and Python version. See [the Python documentation](https://docs.python.org/3/library/concurrent.futures.html#threadpoolexecutor) for more details.

pyiceberg/catalog/__init__.py

@@ -97,7 +97,6 @@ class CatalogType(Enum):
     GLUE = "glue"
     DYNAMODB = "dynamodb"
     SQL = "sql"
-    IN_MEMORY = "in_memory"
 
 
 def load_rest(name: str, conf: Properties) -> Catalog:
@@ -144,19 +143,12 @@ def load_sql(name: str, conf: Properties) -> Catalog:
         ) from exc
 
 
-def load_in_memory(name: str, conf: Properties) -> Catalog:
-    from pyiceberg.catalog.in_memory import InMemoryCatalog
-
-    return InMemoryCatalog(name, **conf)
-
-
 AVAILABLE_CATALOGS: dict[CatalogType, Callable[[str, Properties], Catalog]] = {
     CatalogType.REST: load_rest,
     CatalogType.HIVE: load_hive,
     CatalogType.GLUE: load_glue,
     CatalogType.DYNAMODB: load_dynamodb,
     CatalogType.SQL: load_sql,
-    CatalogType.IN_MEMORY: load_in_memory,
 }
 
 

pyiceberg/catalog/in_memory.py

@@ -157,7 +157,7 @@ def describe_properties(self, properties: Properties) -> None:
         Console().print(output_table)
 
     def text(self, response: str) -> None:
-        Console().print(response)
+        Console(soft_wrap=True).print(response)
 
     def schema(self, schema: Schema) -> None:
         output_table = self._table