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async Table.load_async(data, /)
Load data into the table asynchronously.
This is a non-blocking operation allowing to load data into one or more tables concurrently.
Example
>>> table = session.create_table(
... "Example",
... data_types={"key": "int", "value": "int"},
... keys={"key"},
... )
>>> df_1 = pd.DataFrame({"key": [1, 2], "value": [10, 20]})
>>> df_2 = pd.DataFrame({"key": [3, 4], "value": [30, 40]})
>>> df_3 = pd.DataFrame({"key": [2, 5], "value": [200, 500]})
>>> import asyncio
>>> async def load_df_1_and_2_concurrently(table):
... await asyncio.gather(
... table.load_async(df_1),
... table.load_async(df_2),
... )
>>> asyncio.run(load_df_1_and_2_concurrently(table))
>>> table.head().sort_index()
value
key
1 10
2 20
3 30
4 40
>>> table.drop()
>>> async def load_df_1_and_3_sequentially(table):
... await table.load_async(df_1)
... assert table.row_count == 2
... await table.load_async(df_3)
... assert table.row_count == 3, (
... "df_3 should have overrode key `1` of df_1"
... )
>>> asyncio.run(load_df_1_and_3_sequentially(table))
>>> table.head().sort_index()
value
key
1 10
2 200
5 500
>>> table.drop()
>>> async def load_df_1_and_3_sequentially_bis(table):
... await table.load_async(df_1)
... assert table.row_count >= 2
... await table.load_async(df_3)
... assert table.row_count >= 3
>>> async def load_df_2(table):
... await table.load_async(df_2)
... assert table.row_count >= 2
>>> async def load_all(table):
... await asyncio.gather(
... load_df_1_and_3_sequentially_bis(table),
... load_df_2(table),
... )
... assert table.row_count == 5
>>> asyncio.run(load_all(table))
>>> table.head().sort_index()
value
key
1 10
2 200
3 30
4 40
5 500
