mirror of
https://github.com/lancedb/lancedb.git
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@@ -89,3 +89,6 @@ class RemoteTable(Table):
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def _execute_query(self, query: Query) -> pa.Table:
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result = self._conn._client.query(self._name, query)
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return self._conn._loop.run_until_complete(result).to_arrow()
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def delete(self, predicate: str):
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raise NotImplementedError
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@@ -202,6 +202,51 @@ class Table(ABC):
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def _execute_query(self, query: Query) -> pa.Table:
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pass
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@abstractmethod
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def delete(self, where: str):
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"""Delete rows from the table.
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This can be used to delete a single row, many rows, all rows, or
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sometimes no rows (if your predicate matches nothing).
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Parameters
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----------
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where: str
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The SQL where clause to use when deleting rows. For example, 'x = 2'
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or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
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Examples
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--------
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>>> import lancedb
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>>> import pandas as pd
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>>> data = pd.DataFrame({"x": [1, 2, 3], "vector": [[1, 2], [3, 4], [5, 6]]})
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>>> db = lancedb.connect("./.lancedb")
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>>> table = db.create_table("my_table", data)
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>>> table.to_pandas()
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x vector
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0 1 [1.0, 2.0]
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1 2 [3.0, 4.0]
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2 3 [5.0, 6.0]
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>>> table.delete("x = 2")
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>>> table.to_pandas()
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x vector
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0 1 [1.0, 2.0]
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1 3 [5.0, 6.0]
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If you have a list of values to delete, you can combine them into a
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stringified list and use the `IN` operator:
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>>> to_remove = [1, 5]
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>>> to_remove = ", ".join([str(v) for v in to_remove])
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>>> to_remove
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'1, 5'
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>>> table.delete(f"x IN ({to_remove})")
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>>> table.to_pandas()
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x vector
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0 3 [5.0, 6.0]
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"""
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raise NotImplementedError
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class LanceTable(Table):
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"""
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@@ -496,31 +541,6 @@ class LanceTable(Table):
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return tbl
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def delete(self, where: str):
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"""Delete rows from the table.
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Parameters
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----------
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where: str
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The SQL where clause to use when deleting rows.
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Examples
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--------
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>>> import lancedb
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>>> import pandas as pd
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>>> data = pd.DataFrame({"x": [1, 2, 3], "vector": [[1, 2], [3, 4], [5, 6]]})
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>>> db = lancedb.connect("./.lancedb")
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>>> table = db.create_table("my_table", data)
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>>> table.to_pandas()
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x vector
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0 1 [1.0, 2.0]
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1 2 [3.0, 4.0]
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2 3 [5.0, 6.0]
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>>> table.delete("x = 2")
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>>> table.to_pandas()
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x vector
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0 1 [1.0, 2.0]
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1 3 [5.0, 6.0]
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"""
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self._dataset.delete(where)
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def _execute_query(self, query: Query) -> pa.Table:
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