snowflakedb/snowpark-python v0.2.0 on GitHub

0.2.0 (2021-12-02)

Updated the Session.createDataFrame() method for creating a DataFrame from a Pandas DataFrame.
Added the Session.write_pandas() method for writing a Pandas DataFrame to a table in Snowflake and getting a Snowpark DataFrame object back.
Added new classes and methods for calling window functions.
Added the new functions cume_dist(), to find the cumulative distribution of a value with regard to other values within a window partition,
and row_number(), which returns a unique row number for each row within a window partition.
Added functions for computing statistics for DataFrames in the DataFrameStatFunctions class.
Added functions for handling missing values in a DataFrame in the DataFrameNaFunctions class.
Added new methods rollup(), cube(), and pivot() to the DataFrame class.
Added the GroupingSets class, which you can use with the DataFrame groupByGroupingSets method to perform a SQL GROUP BY GROUPING SETS.
Added the new FileOperation(session)
class that you can use to upload and download files to and from a stage.
Added the DataFrame.copy_into_table()
method for loading data from files in a stage into a table.
In CASE expressions, the functions when() and otherwise()
now accept Python types in addition to Column objects.
When you register a UDF you can now optionally set the replace parameter to True to overwrite an existing UDF with the same name.

UDFs are now compressed before they are uploaded to the server. This makes them about 10 times smaller, which can help
when you are using large ML model files.
When the size of a UDF is less than 8196 bytes, it will be uploaded as in-line code instead of uploaded to a stage.

Fixed an issue where the statement df.select(when(col("a") == 1, 4).otherwise(col("a"))), [Row(4), Row(2), Row(3)] raised an exception.
Fixed an issue where df.toPandas() raised an exception when a DataFrame was created from large local data.