Releases: snowflakedb/snowpark-python
Releases · snowflakedb/snowpark-python
v0.8.0
0.8.0 (2022-07-22)
New Features:
- Added keyword only argument
statement_params
to the following methods to allow for specifying statement level parameters:collect
,to_local_iterator
,to_pandas
,to_pandas_batches
,
count
,copy_into_table
,show
,create_or_replace_view
,create_or_replace_temp_view
,first
,cache_result
andrandom_split
on classsnowflake.snowpark.Dateframe
.update
,delete
andmerge
on classsnowflake.snowpark.Table
.save_as_table
andcopy_into_location
on classsnowflake.snowpark.DataFrameWriter
.approx_quantile
,statement_params
,cov
andcrosstab
on classsnowflake.snowpark.DataFrameStatFunctions
.register
andregister_from_file
on classsnowflake.snowpark.udf.UDFRegistration
.register
andregister_from_file
on classsnowflake.snowpark.udtf.UDTFRegistration
.register
andregister_from_file
on classsnowflake.snowpark.stored_procedure.StoredProcedureRegistration
.udf
,udtf
andsproc
insnowflake.snowpark.functions
.
- Added support for
Column
as an input argument tosession.call()
. - Added support for
table_type
indf.write.save_as_table()
. You can now choose from thesetable_type
options:"temporary"
,"temp"
, and"transient"
.
Improvements:
- Added validation of object name in
session.use_*
methods. - Updated the query tag in SQL to escape it when it has special characters.
- Added a check to see if Anaconda terms are acknowledged when adding missing packages.
Bug Fixes:
- Fixed the limited length of the string column in
session.create_dataframe()
. - Fixed a bug in which
session.create_dataframe()
mistakenly converted 0 andFalse
toNone
when the input data was only a list. - Fixed a bug in which calling
session.create_dataframe()
using a large local dataset sometimes created a temp table twice. - Aligned the definition of
function.trim()
with the SQL function definition. - Fixed an issue where snowpark-python would hang when using the Python system-defined (built-in function)
sum
vs. the Snowparkfunction.sum()
.
v0.7.0
0.7.0
New Features:
- Added support for user-defined table functions (UDTFs).
- Use function
snowflake.snowpark.functions.udtf()
to register a UDTF, or use it as a decorator to register the UDTF.- You can also use
Session.udtf.register()
to register a UDTF.
- You can also use
- Use
Session.udtf.register_from_file()
to register a UDTF from a Python file.
- Use function
- Updated APIs to query a table function, including both Snowflake built-in table functions and UDTFs.
- Use function
snowflake.snowpark.functions.table_function()
to create a callable representing a table function and use it to call the table function in a query. - Alternatively, use function
snowflake.snowpark.functions.call_table_function()
to call a table function. - Added support for
over
clause that specifiespartition by
andorder by
when lateral joining a table function. - Updated
Session.table_function()
andDataFrame.join_table_function()
to acceptTableFunctionCall
instances.
- Use function
Breaking Changes:
- When creating a function with
functions.udf()
andfunctions.sproc()
, you can now specify an empty list for theimports
orpackages
argument to indicate that no import or package is used for this UDF or stored procedure. Previously, specifying an empty list meant that the function would use session-level imports or packages. - Improved the
__repr__
implementation of data types intypes.py
. The unusedtype_name
property has been removed. - Added a Snowpark-specific exception class for SQL errors. This replaces the previous
ProgrammingError
from the Python connector.
Improvements:
- Added a lock to a UDF or UDTF when it is called for the first time per thread.
- Improved the error message for pickling errors that occurred during UDF creation.
- Included the query ID when logging the failed query.
Bug Fixes:
- Fixed a bug in which non-integral data (such as timestamps) was occasionally converted to integer when calling
DataFrame.to_pandas()
. - Fixed a bug in which
DataFrameReader.parquet()
failed to read a parquet file when its column contained spaces. - Fixed a bug in which
DataFrame.copy_into_table()
failed when the dataframe is created by reading a file with inferred schemas.
Deprecations
Session.flatten()
and DataFrame.flatten()
.
Dependency Updates:
- Restricted the version of
cloudpickle
<=2.0.0
.
v0.6.0
0.6.0
New Features:
- Added support for vectorized UDFs with the input as a Pandas DataFrame or Pandas Series and the output as a Pandas Series. This improves the performance of UDFs in Snowpark.
- Added support for inferring the schema of a DataFrame by default when it is created by reading a Parquet, Avro, or ORC file in the stage.
- Added functions
current_session()
,current_statement()
,current_user()
,current_version()
,current_warehouse()
,date_from_parts()
,date_trunc()
,dayname()
,dayofmonth()
,dayofweek()
,dayofyear()
,grouping()
,grouping_id()
,hour()
,last_day()
,minute()
,next_day()
,previous_day()
,second()
,month()
,monthname()
,quarter()
,year()
,current_database()
,current_role()
,current_schema()
,current_schemas()
,current_region()
,current_avaliable_roles()
,add_months()
,any_value()
,bitnot()
,bitshiftleft()
,bitshiftright()
,convert_timezone()
,uniform()
,strtok_to_array()
,sysdate()
,time_from_parts()
,timestamp_from_parts()
,timestamp_ltz_from_parts()
,timestamp_ntz_from_parts()
,timestamp_tz_from_parts()
,weekofyear()
,percentile_cont()
tosnowflake.snowflake.functions
.
Breaking Changes:
- Expired deprecations:
- Removed the following APIs that were deprecated in 0.4.0:
DataFrame.groupByGroupingSets()
,DataFrame.naturalJoin()
,DataFrame.joinTableFunction
,DataFrame.withColumns()
,Session.getImports()
,Session.addImport()
,Session.removeImport()
,Session.clearImports()
,Session.getSessionStage()
,Session.getDefaultDatabase()
,Session.getDefaultSchema()
,Session.getCurrentDatabase()
,Session.getCurrentSchema()
,Session.getFullyQualifiedCurrentSchema()
.
- Removed the following APIs that were deprecated in 0.4.0:
Improvements:
- Added support for creating an empty
DataFrame
with a specific schema using theSession.create_dataframe()
method. - Changed the logging level from
INFO
toDEBUG
for several logs (e.g., the executed query) when evaluating a dataframe. - Improved the error message when failing to create a UDF due to pickle errors.
Bug Fixes:
- Removed pandas hard dependencies in the
Session.create_dataframe()
method.
Dependency Updates:
- Added
typing-extension
as a new dependency with the version >=4.1.0
.
v0.5.0
New Features
- Added stored procedures API.
- Added
Session.sproc
property andsproc()
tosnowflake.snowpark.functions
, so you can register stored procedures. - Added
Session.call
to call stored procedures by name.
- Added
- Added
UDFRegistration.register_from_file()
to allow registering UDFs from Python source files or zip files directly. - Added
UDFRegistration.describe()
to describe a UDF. - Added
DataFrame.random_split()
to provide a way to randomly split a dataframe. - Added functions
md5()
,sha1()
,sha2()
,ascii()
,initcap()
,length()
,lower()
,lpad()
,ltrim()
,rpad()
,rtrim()
,repeat()
,soundex()
,regexp_count()
,replace()
,charindex()
,collate()
,collation()
,insert()
,left()
,right()
,endswith()
tosnowflake.snowpark.functions
. - Allowed
call_udf()
to accept literal values. - Provided a
distinct
keyword inarray_agg()
.
Bug Fixes:
- Fixed an issue that caused
DataFrame.to_pandas()
to have a string column ifColumn.cast(IntegerType())
was used. - Fixed a bug in
DataFrame.describe()
when there is more than one string column.
v0.4.1
0.4.1 (2022-02-25)
Bug Fixes
- Fixed a bug in
DataFrame.describe()
that raised an error when theDataFrame
has more than one string columns.
v0.4.0
0.4.0 (2022-02-15)
New Features
- You can now specify which Anaconda packages to use when defining UDFs.
- Added
add_packages()
,get_packages()
,clear_packages()
, andremove_package()
, to classSession
. - Added
add_requirements()
toSession
so you can use a requirements file to specify which packages this session will use. - Added parameter
packages
to functionsnowflake.snowpark.functions.udf()
and methodUserDefinedFunction.register()
to indicate UDF-level Anaconda package dependencies when creating a UDF. - Added parameter
imports
tosnowflake.snowpark.functions.udf()
andUserDefinedFunction.register()
to specify UDF-level code imports.
- Added
- Added a parameter
session
to functionudf()
andUserDefinedFunction.register()
so you can specify which session to use to create a UDF if you have multiple sessions. - Added types
Geography
andVariant
tosnowflake.snowpark.types
to be used as type hints for Geography and Variant data when defining a UDF. - Added support for Geography geoJSON data.
- Added
Table
, a subclass ofDataFrame
for table operations:- Methods
update
anddelete
update and delete rows of a table in Snowflake. - Method
merge
merges data from aDataFrame
to aTable
. - Override method
DataFrame.sample()
with an additional parameterseed
, which works on tables but not on view and sub-queries.
- Methods
- Added
DataFrame.to_local_iterator()
andDataFrame.to_pandas_batches()
to allow getting results from an iterator when the result set returned from the Snowflake database is too large. - Added
DataFrame.cache_result()
for caching the operations performed on aDataFrame
in a temporary table.
Subsequent operations on the originalDataFrame
have no effect on the cached resultDataFrame
. - Added property
DataFrame.queries
to get SQL queries that will be executed to evaluate theDataFrame
. - Added
Session.query_history()
as a context manager to track SQL queries executed on a session, including all SQL queries to evaluateDataFrame
s created from a session. Both query ID and query text are recorded. - You can now create a
Session
instance from an existing establishedsnowflake.connector.SnowflakeConnection
. Use parameterconnection
inSession.builder.configs()
. - Added
use_database()
,use_schema()
,use_warehouse()
, anduse_role()
to classSession
to switch database/schema/warehouse/role after a session is created. - Added
DataFrameWriter.copy_into_table()
to unload aDataFrame
to stage files. - Added
DataFrame.unpivot()
. - Added
Column.within_group()
for sorting the rows by columns with some aggregation functions. - Added functions
listagg()
,mode()
,div0()
,acos()
,asin()
,atan()
,atan2()
,cos()
,cosh()
,sin()
,sinh()
,tan()
,tanh()
,degrees()
,radians()
,round()
,trunc()
, andfactorial()
tosnowflake.snowflake.functions
. - Added an optional argument
ignore_nulls
in functionlead()
andlag()
. - The
condition
parameter of functionwhen()
andiff()
now accepts SQL expressions.
Improvements
- All function and method names have been renamed to use the snake case naming style, which is more Pythonic. For convenience, some camel case names are kept as aliases to the snake case APIs. It is recommended to use the snake case APIs.
- Deprecated these methods on class
Session
and replaced them with their snake case equivalents:getImports()
,addImports()
,removeImport()
,clearImports()
,getSessionStage()
,getDefaultSchema()
,getDefaultSchema()
,getCurrentDatabase()
,getFullyQualifiedCurrentSchema()
. - Deprecated these methods on class
DataFrame
and replaced them with their snake case equivalents:groupingByGroupingSets()
,naturalJoin()
,withColumns()
,joinTableFunction()
.
- Deprecated these methods on class
- Property
DataFrame.columns
is now consistent withDataFrame.schema.names
and the Snowflake databaseIdentifier Requirements
. Column.__bool__()
now raises aTypeError
. This will ban the use of logical operatorsand
,or
,not
onColumn
object, for instancecol("a") > 1 and col("b") > 2
will raise theTypeError
. Use(col("a") > 1) & (col("b") > 2)
instead.- Changed
PutResult
andGetResult
to subclassNamedTuple
. - Fixed a bug which raised an error when the local path or stage location has a space or other special characters.
- Changed
DataFrame.describe()
so that non-numeric and non-string columns are ignored instead of raising an exception.
Dependency updates
- Updated
snowflake-connector-python
to 2.7.4.
v0.3.0
0.3.0 (2022-01-09)
New Features
- Added
Column.isin()
, with an aliasColumn.in_()
. - Added
Column.try_cast()
, which is a special version ofcast()
. It tries to cast a string expression to other types and returnsnull
if the cast is not possible. - Added
Column.startswith()
andColumn.substr()
to process string columns. Column.cast()
now also accepts astr
value to indicate the cast type in addition to aDataType
instance.- Added
DataFrame.describe()
to summarize stats of aDataFrame
. - Added
DataFrame.explain()
to print the query plan of aDataFrame
. DataFrame.filter()
andDataFrame.select_expr()
now accepts a sql expression.- Added a new
bool
parametercreate_temp_table
to methodsDataFrame.saveAsTable()
andSession.write_pandas()
to optionally create a temp table. - Added
DataFrame.minus()
andDataFrame.subtract()
as aliases toDataFrame.except_()
. - Added
regexp_replace()
,concat()
,concat_ws()
,to_char()
,current_timestamp()
,current_date()
,current_time()
,months_between()
,cast()
,try_cast()
,greatest()
,least()
, andhash()
to modulesnowflake.snowpark.functions
.
Bug Fixes
- Fixed an issue where
Session.createDataFrame(pandas_df)
andSession.write_pandas(pandas_df)
raise an exception when thePandas DataFrame
has spaces in the column name. DataFrame.copy_into_table()
sometimes prints anerror
level log entry while it actually works. It's fixed now.- Fixed an API docs issue where some
DataFrame
APIs are missing from the docs.
Dependency updates
- Update
snowflake-connector-python
to 2.7.2, which upgradespyarrow
dependency to 6.0.x. Refer to the python connector 2.7.2 release notes for more details.
v0.2.0
0.2.0 (2021-12-02)
New Features
- Updated the
Session.createDataFrame()
method for creating aDataFrame
from a Pandas DataFrame. - Added the
Session.write_pandas()
method for writing aPandas DataFrame
to a table in Snowflake and getting aSnowpark 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,
androw_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()
, andpivot()
to theDataFrame
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()
andotherwise()
now accept Python types in addition toColumn
objects. - When you register a UDF you can now optionally set the
replace
parameter toTrue
to overwrite an existing UDF with the same name.
Improvements
- 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.
Bug Fixes
- 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.
Private Preview Release
Initial private preview release of snowflake-snowpark-python