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Author: hussein-awala

mkdocs/docs/configuration.md

@@ -388,6 +388,23 @@ catalog:
 | echo          | true                                                         | false   | SQLAlchemy engine [echo param](https://docs.sqlalchemy.org/en/20/core/engines.html#sqlalchemy.create_engine.params.echo) to log all statements to the default log handler                      |
 | pool_pre_ping | true                                                         | false   | SQLAlchemy engine [pool_pre_ping param](https://docs.sqlalchemy.org/en/20/core/engines.html#sqlalchemy.create_engine.params.pool_pre_ping) to test connections for liveness upon each checkout |
 
+### In Memory Catalog
+
+The in-memory catalog is built on top of `SqlCatalog` and uses SQLite in-memory database for its backend.
+
+It is useful for test, demo, and playground but not in production as it does not support concurrent access.
+
+```yaml
+catalog:
+  default:
+    type: in-memory
+    warehouse: /tmp/pyiceberg/warehouse
+```
+
+| Key       | Example                  | Default                       | Description                                                          |
+| --------- |--------------------------|-------------------------------|----------------------------------------------------------------------|
+| warehouse | /tmp/pyiceberg/warehouse | file:///tmp/iceberg/warehouse | The directory where the in-memory catalog will store its data files. |
+
 ### Hive Catalog
 
 ```yaml

pyiceberg/catalog/__init__.py

@@ -116,6 +116,7 @@ class CatalogType(Enum):
     GLUE = "glue"
     DYNAMODB = "dynamodb"
     SQL = "sql"
+    IN_MEMORY = "in-memory"
 
 
 def load_rest(name: str, conf: Properties) -> Catalog:
@@ -162,12 +163,22 @@ def load_sql(name: str, conf: Properties) -> Catalog:
         ) from exc
 
 
+def load_in_memory(name: str, conf: Properties) -> Catalog:
+    try:
+        from pyiceberg.catalog.memory import InMemoryCatalog
+
+        return InMemoryCatalog(name, **conf)
+    except ImportError as exc:
+        raise NotInstalledError("SQLAlchemy support not installed: pip install 'pyiceberg[sql-sqlite]'") from exc
+
+
 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/memory.py

@@ -22,10 +22,10 @@ class InMemoryCatalog(SqlCatalog):
     """
     An in-memory catalog implementation that uses SqlCatalog with SQLite in-memory database.
 
-    This is useful for test, demo, and playground but not in production as data is not persisted.
+    This is useful for test, demo, and playground but not in production as it does not support concurrent access.
     """
 
-    def __init__(self, name: str, warehouse: str = "file:///tmp/warehouse", **kwargs: str) -> None:
+    def __init__(self, name: str, warehouse: str = "file:///tmp/iceberg/warehouse", **kwargs: str) -> None:
         self._warehouse_location = warehouse
         if "uri" not in kwargs:
             kwargs["uri"] = "sqlite:///:memory:"

tests/catalog/test_memory.py tests/catalog/test_base.pytests/catalog/test_memory.py renamed to tests/catalog/test_base.py

@@ -829,9 +829,9 @@ def test_json_properties_get_table_does_not_exist(catalog: InMemoryCatalog) -> N
     # pylint: disable=unused-argument
 
     runner = CliRunner()
-    result = runner.invoke(run, ["--output=json", "properties", "get", "table", "doesnotexist"])
+    result = runner.invoke(run, ["--output=json", "properties", "get", "table", "default.doesnotexist"])
     assert result.exit_code == 1
-    assert result.output == """{"type": "ValueError", "message": "Empty namespace identifier"}\n"""
+    assert result.output == """{"type": "NoSuchTableError", "message": "Table does not exist: default.doesnotexist"}\n"""
 
 
 def test_json_properties_get_namespace(catalog: InMemoryCatalog, namespace_properties: Properties) -> None: