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Correct typing and an impl error
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jmao-denver committed Jul 1, 2024
1 parent ac8ffd3 commit f298bc7
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Showing 2 changed files with 2 additions and 3 deletions.
1 change: 0 additions & 1 deletion py/server/deephaven/_table_reader.py
Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,6 @@ def _table_reader_chunks(table: Table, *, cols: Optional[Union[str, Sequence[str

row_sequence_iterator = row_set.getRowSequenceIterator()
col_sources = [table.j_table.getColumnSource(col_def.name) for col_def in col_defs]
chunk_size = row_set.size() if not chunk_size else chunk_size
j_reader_context = _JTableUpdateDataReader.makeContext(chunk_size, *col_sources)
with update_graph.auto_locking_ctx(table):
try:
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4 changes: 2 additions & 2 deletions py/server/deephaven/table.py
Original file line number Diff line number Diff line change
Expand Up @@ -527,7 +527,7 @@ def iter_dict(self, cols: Optional[Union[str, Sequence[str]]] = None) -> Generat

return _table_reader_rows(self, cols)

def iter_tuple(self, cols: Optional[Union[str, Sequence[str]]] = None, name: str = 'Deephaven') -> Generator[Tuple[str, Any], None, None]:
def iter_tuple(self, cols: Optional[Union[str, Sequence[str]]] = None, name: str = 'Deephaven') -> Generator[Tuple[Any], None, None]:
""" Returns a generator that reads one row at a time from the table into a named tuple. The named tuple is made
up of fields with their names being the column names and their values being of the column data types.
Expand Down Expand Up @@ -580,7 +580,7 @@ def iter_chunk_dict(self, cols: Optional[Union[str, Sequence[str]]] = None, *, c
prev=False, to_numpy=True)

def iter_chunk_tuple(self, cols: Optional[Union[str, Sequence[str]]] = None, *, chunk_size: Optional[int] = 4096,
name: str = 'Deephaven')-> Generator[Tuple[str, np.ndarray], None, None]:
name: str = 'Deephaven')-> Generator[Tuple[np.ndarray], None, None]:
""" Returns a generator that reads one chunk of rows at a time from the table into a named tuple. The named
tuple is made up of fields with their names being the column names and their values being numpy arrays of the
column data types.
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