feat(ux): include basename of path in generated table names in read_*()

ibis/backends/clickhouse/__init__.py

@@ -581,7 +581,7 @@ def read_parquet(
         paths = list(glob.glob(str(path)))
         schema = PyArrowSchema.to_ibis(ds.dataset(paths, format="parquet").schema)
 
-        name = table_name or util.gen_name("read_parquet")
+        name = table_name or util.gen_name_from_path(paths[0])
         table = self.create_table(name, engine=engine, schema=schema, temp=True)
 
         for file_path in paths:
@@ -609,7 +609,7 @@ def read_csv(
         paths = list(glob.glob(str(path)))
         schema = PyArrowSchema.to_ibis(ds.dataset(paths, format="csv").schema)
 
-        name = table_name or util.gen_name("read_csv")
+        name = table_name or util.gen_name_from_path(paths[0])
         table = self.create_table(name, engine=engine, schema=schema, temp=True)
 
         for file_path in paths:

ibis/backends/datafusion/__init__.py

@@ -28,7 +28,6 @@
 from ibis.common.dispatch import lazy_singledispatch
 from ibis.expr.operations.udf import InputType
 from ibis.formats.pyarrow import PyArrowSchema, PyArrowType
-from ibis.util import deprecated, gen_name, normalize_filename, normalize_filenames
 
 try:
     from datafusion import ExecutionContext as SessionContext
@@ -160,7 +159,7 @@
         yield self.raw_sql(sql).collect()
 
     def _get_schema_using_query(self, query: str) -> sch.Schema:
-        name = gen_name("datafusion_metadata_view")
+        name = util.gen_name("datafusion_metadata_view")
         table = sg.table(name, quoted=self.compiler.quoted)
         src = sge.Create(
             this=table,
@@ -345,7 +344,7 @@
         table = database.table(table_name)
         return sch.schema(table.schema)
 
-    @deprecated(
+    @util.deprecated(
         as_of="9.1",
         instead="use the explicit `read_*` method for the filetype you are trying to read, e.g., read_parquet, read_csv, etc.",
     )
@@ -437,11 +436,11 @@
             The just-registered table
 
         """
-        path = normalize_filenames(source_list)
-        table_name = table_name or gen_name("read_csv")
+        paths = util.normalize_filenames(source_list)
+        table_name = table_name or util.gen_name_from_path(paths[0])
         # Our other backends support overwriting views / tables when re-registering
         self.con.deregister_table(table_name)
-        self.con.register_csv(table_name, path, **kwargs)
+        self.con.register_csv(table_name, paths, **kwargs)
         return self.table(table_name)
 
     def read_parquet(
@@ -465,8 +464,8 @@
             The just-registered table
 
         """
-        path = normalize_filename(path)
-        table_name = table_name or gen_name("read_parquet")
+        path = util.normalize_filename(path)
+        table_name = table_name or util.gen_name_from_path(path)
         # Our other backends support overwriting views / tables when reregistering
         self.con.deregister_table(table_name)
         self.con.register_parquet(table_name, path, **kwargs)
@@ -494,9 +493,9 @@
             The just-registered table
 
         """
-        source_table = normalize_filename(source_table)
+        source_table = util.normalize_filename(source_table)
 
-        table_name = table_name or gen_name("read_delta")
+        table_name = table_name or util.gen_name_from_path(source_table)
 
         # Our other backends support overwriting views / tables when reregistering
         self.con.deregister_table(table_name)
@@ -730,55 +729,55 @@
 
 @_read_in_memory.register(dict)
 def _pydict(source, table_name, _conn, overwrite: bool = False):
-    tmp_name = gen_name("pydict")
+    tmp_name = util.gen_name("pydict")
     with _create_and_drop_memtable(_conn, table_name, tmp_name, overwrite):
         _conn.con.from_pydict(source, name=tmp_name)
 
 
 @_read_in_memory.register("polars.DataFrame")
 def _polars(source, table_name, _conn, overwrite: bool = False):
-    tmp_name = gen_name("polars")
+    tmp_name = util.gen_name("polars")
     with _create_and_drop_memtable(_conn, table_name, tmp_name, overwrite):
         _conn.con.from_polars(source, name=tmp_name)
 
 
 @_read_in_memory.register("polars.LazyFrame")
 def _polars(source, table_name, _conn, overwrite: bool = False):
-    tmp_name = gen_name("polars")
+    tmp_name = util.gen_name("polars")
     with _create_and_drop_memtable(_conn, table_name, tmp_name, overwrite):
         _conn.con.from_polars(source.collect(), name=tmp_name)
 
 
 @_read_in_memory.register("pyarrow.Table")
 def _pyarrow_table(source, table_name, _conn, overwrite: bool = False):
-    tmp_name = gen_name("pyarrow")
+    tmp_name = util.gen_name("pyarrow")
     with _create_and_drop_memtable(_conn, table_name, tmp_name, overwrite):
         _conn.con.from_arrow(source, name=tmp_name)
 
 
 @_read_in_memory.register("pyarrow.RecordBatchReader")
 def _pyarrow_rbr(source, table_name, _conn, overwrite: bool = False):
-    tmp_name = gen_name("pyarrow")
+    tmp_name = util.gen_name("pyarrow")
     with _create_and_drop_memtable(_conn, table_name, tmp_name, overwrite):
         _conn.con.from_arrow(source.read_all(), name=tmp_name)
 
 
 @_read_in_memory.register("pyarrow.RecordBatch")
 def _pyarrow_rb(source, table_name, _conn, overwrite: bool = False):
-    tmp_name = gen_name("pyarrow")
+    tmp_name = util.gen_name("pyarrow")
     with _create_and_drop_memtable(_conn, table_name, tmp_name, overwrite):
         _conn.con.register_record_batches(tmp_name, [[source]])
 
 
 @_read_in_memory.register("pyarrow.dataset.Dataset")
 def _pyarrow_rb(source, table_name, _conn, overwrite: bool = False):
-    tmp_name = gen_name("pyarrow")
+    tmp_name = util.gen_name("pyarrow")
     with _create_and_drop_memtable(_conn, table_name, tmp_name, overwrite):
         _conn.con.register_dataset(tmp_name, source)
 
 
 @_read_in_memory.register("pandas.DataFrame")
 def _pandas(source: pd.DataFrame, table_name, _conn, overwrite: bool = False):
-    tmp_name = gen_name("pandas")
+    tmp_name = util.gen_name("pandas")
     with _create_and_drop_memtable(_conn, table_name, tmp_name, overwrite):
         _conn.con.from_pandas(source, name=tmp_name)

ibis/backends/duckdb/__init__.py

@@ -588,8 +588,9 @@ def read_json(
             An ibis table expression
 
         """
+        filenames = util.normalize_filenames(source_list)
         if not table_name:
-            table_name = util.gen_name("read_json")
+            table_name = util.gen_name_from_path(filenames[0])
 
         options = [
             sg.to_identifier(key).eq(sge.convert(val)) for key, val in kwargs.items()
@@ -612,11 +613,7 @@ def read_json(
 
         self._create_temp_view(
             table_name,
-            sg.select(STAR).from_(
-                self.compiler.f.read_json_auto(
-                    util.normalize_filenames(source_list), *options
-                )
-            ),
+            sg.select(STAR).from_(self.compiler.f.read_json_auto(filenames, *options)),
         )
 
         return self.table(table_name)
@@ -703,7 +700,7 @@ def read_csv(
         source_list = util.normalize_filenames(source_list)
 
         if not table_name:
-            table_name = util.gen_name("read_csv")
+            table_name = util.gen_name_from_path(source_list[0])
 
         # auto_detect and columns collide, so we set auto_detect=True
         # unless COLUMNS has been specified
@@ -779,17 +776,16 @@ def read_geo(
             The just-registered table
 
         """
-
-        if not table_name:
-            table_name = util.gen_name("read_geo")
-
         # load geospatial extension
         self.load_extension("spatial")
 
         source = util.normalize_filename(source)
         if source.startswith(("http://", "https://", "s3://")):
             self._load_extensions(["httpfs"])
 
+        if not table_name:
+            table_name = util.gen_name_from_path(source)
+
         source_expr = sg.select(STAR).from_(
             self.compiler.f.st_read(
                 source,
@@ -835,7 +831,7 @@ def read_parquet(
         """
         source_list = util.normalize_filenames(source_list)
 
-        table_name = table_name or util.gen_name("read_parquet")
+        table_name = table_name or util.gen_name_from_path(source_list[0])
 
         # Default to using the native duckdb parquet reader
         # If that fails because of auth issues, fall back to ingesting via
@@ -944,7 +940,7 @@ def read_delta(
         """
         source_table = util.normalize_filenames(source_table)[0]
 
-        table_name = table_name or util.gen_name("read_delta")
+        table_name = table_name or util.gen_name_from_path(source_table)
 
         try:
             from deltalake import DeltaTable

ibis/backends/flink/__init__.py

@@ -27,7 +27,6 @@
 from ibis.backends.sql import SQLBackend
 from ibis.backends.tests.errors import Py4JJavaError
 from ibis.expr.operations.udf import InputType
-from ibis.util import gen_name
 
 if TYPE_CHECKING:
     from collections.abc import Mapping
@@ -767,7 +766,7 @@ def _read_file(
                 f"`schema` must be explicitly provided when calling `read_{file_type}`"
             )
 
-        table_name = table_name or gen_name(f"read_{file_type}")
+        table_name = table_name or util.gen_name_from_path(path)
         tbl_properties = {
             "connector": "filesystem",
             "path": path,

ibis/backends/polars/__init__.py

@@ -12,14 +12,14 @@
 import ibis.expr.operations as ops
 import ibis.expr.schema as sch
 import ibis.expr.types as ir
+from ibis import util
 from ibis.backends import BaseBackend, NoUrl
 from ibis.backends.polars.compiler import translate
 from ibis.backends.polars.rewrites import bind_unbound_table, rewrite_join
 from ibis.backends.sql.dialects import Polars
 from ibis.common.dispatch import lazy_singledispatch
 from ibis.expr.rewrites import lower_stringslice, replace_parameter
 from ibis.formats.polars import PolarsSchema
-from ibis.util import deprecated, gen_name, normalize_filename, normalize_filenames
 
 if TYPE_CHECKING:
     from collections.abc import Iterable
@@ -100,7 +100,7 @@ def _register_in_memory_table(self, op: ops.InMemoryTable) -> None:
     def _finalize_memtable(self, name: str) -> None:
         self.drop_table(name, force=True)
 
-    @deprecated(
+    @util.deprecated(
         as_of="9.1",
         instead="use the explicit `read_*` method for the filetype you are trying to read, e.g., read_parquet, read_csv, etc.",
     )
@@ -209,12 +209,12 @@ def read_csv(
             The just-registered table
 
         """
-        source_list = normalize_filenames(path)
+        source_list = util.normalize_filenames(path)
+        table_name = table_name or util.gen_name_from_path(source_list[0])
         # Flatten the list if there's only one element because Polars
         # can't handle glob strings, or compressed CSVs in a single-element list
         if len(source_list) == 1:
             source_list = source_list[0]
-        table_name = table_name or gen_name("read_csv")
         try:
             table = pl.scan_csv(source_list, **kwargs)
             # triggers a schema computation to handle compressed csv inference
@@ -250,8 +250,8 @@ def read_json(
             The just-registered table
 
         """
-        path = normalize_filename(path)
-        table_name = table_name or gen_name("read_json")
+        path = util.normalize_filename(path)
+        table_name = table_name or util.gen_name_from_path(path)
         try:
             self._add_table(table_name, pl.scan_ndjson(path, **kwargs))
         except pl.exceptions.ComputeError:
@@ -290,8 +290,8 @@ def read_delta(
                 "read_delta method. You can install it using pip:\n\n"
                 "pip install 'ibis-framework[polars,deltalake]'\n"
             )
-        path = normalize_filename(path)
-        table_name = table_name or gen_name("read_delta")
+        path = util.normalize_filename(path)
+        table_name = table_name or util.gen_name_from_path(path)
         self._add_table(table_name, pl.scan_delta(path, **kwargs))
         return self.table(table_name)
 
@@ -318,7 +318,7 @@ def read_pandas(
             The just-registered table
 
         """
-        table_name = table_name or gen_name("read_in_memory")
+        table_name = table_name or util.gen_name("read_in_memory")
 
         self._add_table(table_name, pl.from_pandas(source, **kwargs).lazy())
         return self.table(table_name)
@@ -351,24 +351,21 @@ def read_parquet(
             The just-registered table
 
         """
-        table_name = table_name or gen_name("read_parquet")
-        if not isinstance(path, (str, Path)) and len(path) == 1:
-            path = path[0]
+        paths = util.normalize_filenames(path)
+        table_name = table_name or util.gen_name_from_path(paths[0])
 
-        if not isinstance(path, (str, Path)) and len(path) > 1:
+        if len(paths) > 1:
             self._import_pyarrow()
             import pyarrow.dataset as ds
 
-            paths = [normalize_filename(p) for p in path]
             obj = pl.scan_pyarrow_dataset(
                 source=ds.dataset(paths, format="parquet"),
                 **kwargs,
             )
-            self._add_table(table_name, obj)
         else:
-            path = normalize_filename(path)
-            self._add_table(table_name, pl.scan_parquet(path, **kwargs))
+            obj = pl.scan_parquet(paths[0], **kwargs)
 
+        self._add_table(table_name, obj)
         return self.table(table_name)
 
     def create_table(

ibis/backends/pyspark/__init__.py

@@ -790,7 +790,7 @@
             )
         path = util.normalize_filename(path)
         spark_df = self._session.read.format("delta").load(path, **kwargs)
-        table_name = table_name or util.gen_name("read_delta")
+        table_name = table_name or util.gen_name_from_path(path)
 
         spark_df.createOrReplaceTempView(table_name)
         return self.table(table_name)
@@ -827,7 +827,7 @@
             )
         path = util.normalize_filename(path)
         spark_df = self._session.read.parquet(path, **kwargs)
-        table_name = table_name or util.gen_name("read_parquet")
+        table_name = table_name or util.gen_name_from_path(path)
 
         spark_df.createOrReplaceTempView(table_name)
         return self.table(table_name)
@@ -869,7 +869,7 @@
         spark_df = self._session.read.csv(
             source_list, inferSchema=inferSchema, header=header, **kwargs
         )
-        table_name = table_name or util.gen_name("read_csv")
+        table_name = table_name or util.gen_name_from_path(source_list[0])
 
         spark_df.createOrReplaceTempView(table_name)
         return self.table(table_name)
@@ -907,7 +907,7 @@
             )
         source_list = util.normalize_filenames(source_list)
         spark_df = self._session.read.json(source_list, **kwargs)
-        table_name = table_name or util.gen_name("read_json")
+        table_name = table_name or util.gen_name_from_path(source_list[0])
 
         spark_df.createOrReplaceTempView(table_name)
         return self.table(table_name)
@@ -1217,7 +1217,7 @@
                     watermark.time_col,
                     _interval_to_string(watermark.allowed_delay),
                 )
-        table_name = table_name or util.gen_name("read_csv_dir")
+        table_name = table_name or util.gen_name_from_path(path)
 
         spark_df.createOrReplaceTempView(table_name)
         return self.table(table_name)
@@ -1272,7 +1272,7 @@
                     watermark.time_col,
                     _interval_to_string(watermark.allowed_delay),
                 )
-        table_name = table_name or util.gen_name("read_parquet_dir")
+        table_name = table_name or util.gen_name_from_path(path)
 
         spark_df.createOrReplaceTempView(table_name)
         return self.table(table_name)
@@ -1318,7 +1318,7 @@
                     watermark.time_col,
                     _interval_to_string(watermark.allowed_delay),
                 )
-        table_name = table_name or util.gen_name("read_json_dir")
+        table_name = table_name or util.gen_name_from_path(path)
 
         spark_df.createOrReplaceTempView(table_name)
         return self.table(table_name)