- Added support for
Series.str.ljust
andSeries.str.rjust
. - Added support for
Series.str.center
. - Added support for
Series.str.pad
.
- Added support for property
version
and class methodget_active_session
forSession
class. - Added new methods and variables to enhance data type handling and JSON serialization/deserialization:
- To
DataType
, its derived classes, andStructField
:type_name
: Returns the type name of the data.simple_string
: Provides a simple string representation of the data.json_value
: Returns the data as a JSON-compatible value.json
: Converts the data to a JSON string.
- To
ArrayType
,MapType
,StructField
,PandasSeriesType
,PandasDataFrameType
andStructType
:from_json
: Enables these types to be created from JSON data.
- To
MapType
:keyType
: keys of the mapvalueType
: values of the map
- To
- Added support for method
appName
inSessionBuilder
. - Added support for
include_nulls
argument inDataFrame.unpivot
. - Added support for following functions in
functions.py
:size
to get size of array, object, or map columns.collect_list
an alias ofarray_agg
.substring
makeslen
argument optional.
- Added parameter
ast_enabled
to session for internal usage (default:False
).
- Added support for specifying the following to
DataFrame.create_or_replace_dynamic_table
:iceberg_config
A dictionary that can hold the following iceberg configuration options:external_volume
catalog
base_location
catalog_sync
storage_serialization_policy
- Added support for nested data types to
DataFrame.print_schema
- Added support for
level
parameter toDataFrame.print_schema
- Improved flexibility of
DataFrameReader
andDataFrameWriter
API by adding support for the following:- Added
format
method toDataFrameReader
andDataFrameWriter
to specify file format when loading or unloading results. - Added
load
method toDataFrameReader
to work in conjunction withformat
. - Added
save
method toDataFrameWriter
to work in conjunction withformat
. - Added support to read keyword arguments to
options
method forDataFrameReader
andDataFrameWriter
.
- Added
- Relaxed the cloudpickle dependency for Python 3.11 to simplify build requirements. However, for Python 3.11,
cloudpickle==2.2.1
remains the only supported version.
- Removed warnings that dynamic pivot features were in private preview, because dynamic pivot is now generally available.
- Fixed a bug in
session.read.options
whereFalse
Boolean values were incorrectly parsed asTrue
in the generated file format.
- Added a runtime dependency on
python-dateutil
.
- Added partial support for
Series.map
whenarg
is a pandasSeries
or acollections.abc.Mapping
. No support for instances ofdict
that implement__missing__
but are not instances ofcollections.defaultdict
. - Added support for
DataFrame.align
andSeries.align
foraxis=1
andaxis=None
. - Added support for
pd.json_normalize
. - Added support for
GroupBy.pct_change
withaxis=0
,freq=None
, andlimit=None
. - Added support for
DataFrameGroupBy.__iter__
andSeriesGroupBy.__iter__
. - Added support for
np.sqrt
,np.trunc
,np.floor
, numpy trig functions,np.exp
,np.abs
,np.positive
andnp.negative
. - Added partial support for the dataframe interchange protocol method
DataFrame.__dataframe__()
.
- Fixed a bug in
df.loc
where setting a single column from a series results in unexpectedNone
values.
- Use UNPIVOT INCLUDE NULLS for unpivot operations in pandas instead of sentinel values.
- Improved documentation for pd.read_excel.
- Added the following new functions in
snowflake.snowpark.dataframe
:map
- Added support for passing parameter
include_error
toSession.query_history
to record queries that have error during execution.
- When target stage is not set in profiler, a default stage from
Session.get_session_stage
is used instead of raisingSnowparkSQLException
. - Allowed lower case or mixed case input when calling
Session.stored_procedure_profiler.set_active_profiler
. - Added distributed tracing using open telemetry APIs for action function in
DataFrame
:cache_result
- Removed opentelemetry warning from logging.
- Fixed the pre-action and post-action query propagation when
In
expression were used in selects. - Fixed a bug that raised error
AttributeError
while callingSession.stored_procedure_profiler.get_output
whenSession.stored_procedure_profiler
is disabled.
- Added a dependency on
protobuf>=5.28
andtzlocal
at runtime. - Added a dependency on
protoc-wheel-0
for the development profile. - Require
snowflake-connector-python>=3.12.0, <4.0.0
(was>=3.10.0
).
- Updated
modin
from 0.28.1 to 0.30.1. - Added support for all
pandas
2.2.x versions.
- Added support for
Index.to_numpy
. - Added support for
DataFrame.align
andSeries.align
foraxis=0
. - Added support for
size
inGroupBy.aggregate
,DataFrame.aggregate
, andSeries.aggregate
. - Added support for
snowflake.snowpark.functions.window
- Added support for
pd.read_pickle
(Uses native pandas for processing). - Added support for
pd.read_html
(Uses native pandas for processing). - Added support for
pd.read_xml
(Uses native pandas for processing). - Added support for aggregation functions
"size"
andlen
inGroupBy.aggregate
,DataFrame.aggregate
, andSeries.aggregate
. - Added support for list values in
Series.str.len
.
- Fixed a bug where aggregating a single-column dataframe with a single callable function (e.g.
pd.DataFrame([0]).agg(np.mean)
) would fail to transpose the result. - Fixed bugs where
DataFrame.dropna()
would:- Treat an empty
subset
(e.g.[]
) as if it specified all columns instead of no columns. - Raise a
TypeError
for a scalarsubset
instead of filtering on just that column. - Raise a
ValueError
for asubset
of typepandas.Index
instead of filtering on the columns in the index.
- Treat an empty
- Disable creation of scoped read only table to mitigate Disable creation of scoped read only table to mitigate
TableNotFoundError
when using dynamic pivot in notebook environment. - Fixed a bug when concat dataframe or series objects are coming from the same dataframe when axis = 1.
- Improve np.where with scalar x value by eliminating unnecessary join and temp table creation.
- Improve get_dummies performance by flattening the pivot with join.
- Improve align performance when aligning on row position column by removing unnecessary window functions.
- Added support for patching functions that are unavailable in the
snowflake.snowpark.functions
module. - Added support for
snowflake.snowpark.functions.any_value
- Fixed a bug where
Table.update
could not handleVariantType
,MapType
, andArrayType
data types. - Fixed a bug where column aliases were incorrectly resolved in
DataFrame.join
, causing errors when selecting columns from a joined DataFrame. - Fixed a bug where
Table.update
andTable.merge
could fail if the target table's index was not the defaultRangeIndex
.
- Updated
Session
class to be thread-safe. This allows concurrent DataFrame transformations, DataFrame actions, UDF and stored procedure registration, and concurrent file uploads when using the sameSession
object.- The feature is disabled by default and can be enabled by setting
FEATURE_THREAD_SAFE_PYTHON_SESSION
toTrue
for account. - Updating session configurations, like changing database or schema, when multiple threads are using the session may lead to unexpected behavior.
- When enabled, some internally created temporary table names returned from
DataFrame.queries
API are not deterministic, and may be different when DataFrame actions are executed. This does not affect explicit user-created temporary tables.
- The feature is disabled by default and can be enabled by setting
- Added support for 'Service' domain to
session.lineage.trace
API. - Added support for
copy_grants
parameter when registering UDxF and stored procedures. - Added support for the following methods in
DataFrameWriter
to support daisy-chaining:option
options
partition_by
- Added support for
snowflake_cortex_summarize
.
- Improved the following new capability for function
snowflake.snowpark.functions.array_remove
it is now possible to use in python. - Disables sql simplification when sort is performed after limit.
- Previously,
df.sort().limit()
anddf.limit().sort()
generates the same query with sort in front of limit. Now,df.limit().sort()
will generate query that readsdf.limit().sort()
. - Improve performance of generated query for
df.limit().sort()
, because limit stops table scanning as soon as the number of records is satisfied.
- Previously,
- Added a client side error message for when an invalid stage location is passed to DataFrame read functions.
- Fixed a bug where the automatic cleanup of temporary tables could interfere with the results of async query execution.
- Fixed a bug in
DataFrame.analytics.time_series_agg
function to handle multiple data points in same sliding interval. - Fixed a bug that created inconsistent casing in field names of structured objects in iceberg schemas.
- Deprecated warnings will be triggered when using snowpark-python with Python 3.8. For more details, please refer to https://docs.snowflake.com/en/developer-guide/python-runtime-support-policy.
- Added support for
np.subtract
,np.multiply
,np.divide
, andnp.true_divide
. - Added support for tracking usages of
__array_ufunc__
. - Added numpy compatibility support for
np.float_power
,np.mod
,np.remainder
,np.greater
,np.greater_equal
,np.less
,np.less_equal
,np.not_equal
, andnp.equal
. - Added numpy compatibility support for
np.log
,np.log2
, andnp.log10
- Added support for
DataFrameGroupBy.bfill
,SeriesGroupBy.bfill
,DataFrameGroupBy.ffill
, andSeriesGroupBy.ffill
. - Added support for
on
parameter withResampler
. - Added support for timedelta inputs in
value_counts()
. - Added support for applying Snowpark Python function
snowflake_cortex_summarize
. - Added support for
DataFrame.attrs
andSeries.attrs
. - Added support for
DataFrame.style
. - Added numpy compatibility support for
np.full_like
- Improved generated SQL query for
head
andiloc
when the row key is a slice. - Improved error message when passing an unknown timezone to
tz_convert
andtz_localize
inSeries
,DataFrame
,Series.dt
, andDatetimeIndex
. - Improved documentation for
tz_convert
andtz_localize
inSeries
,DataFrame
,Series.dt
, andDatetimeIndex
to specify the supported timezone formats. - Added additional kwargs support for
df.apply
andseries.apply
( as well asmap
andapplymap
) when using snowpark functions. This allows for some position independent compatibility between apply and functions where the first argument is not a pandas object. - Improved generated SQL query for
iloc
andiat
when the row key is a scalar. - Removed all joins in
iterrows
. - Improved documentation for
Series.map
to reflect the unsupported features. - Added support for
np.may_share_memory
which is used internally by many scikit-learn functions. This method will always return false when called with a Snowpark pandas object.
- Fixed a bug where
DataFrame
andSeries
pct_change()
would raiseTypeError
when input contained timedelta columns. - Fixed a bug where
replace()
would sometimes propagateTimedelta
types incorrectly throughreplace()
. Instead raiseNotImplementedError
forreplace()
onTimedelta
. - Fixed a bug where
DataFrame
andSeries
round()
would raiseAssertionError
forTimedelta
columns. Instead raiseNotImplementedError
forround()
onTimedelta
. - Fixed a bug where
reindex
fails when the new index is a Series with non-overlapping types from the original index. - Fixed a bug where calling
__getitem__
on a DataFrameGroupBy object always returned a DataFrameGroupBy object ifas_index=False
. - Fixed a bug where inserting timedelta values into an existing column would silently convert the values to integers instead of raising
NotImplementedError
. - Fixed a bug where
DataFrame.shift()
on axis=0 and axis=1 would fail to propagate timedelta types. DataFrame.abs()
,DataFrame.__neg__()
,DataFrame.stack()
, andDataFrame.unstack()
now raiseNotImplementedError
for timedelta inputs instead of failing to propagate timedelta types.
- Fixed a bug where
DataFrame.alias
raisesKeyError
for input column name. - Fixed a bug where
to_csv
on Snowflake stage fails when data contains empty strings.
- Added the following new functions in
snowflake.snowpark.functions
:make_interval
- Added support for using Snowflake Interval constants with
Window.range_between()
when the order by column is TIMESTAMP or DATE type. - Added support for file writes. This feature is currently in private preview.
- Added
thread_id
toQueryRecord
to track the thread id submitting the query history. - Added support for
Session.stored_procedure_profiler
.
- Fixed a bug where registering a stored procedure or UDxF with type hints would give a warning
'NoneType' has no len() when trying to read default values from function
.
- Added support for
TimedeltaIndex.mean
method. - Added support for some cases of aggregating
Timedelta
columns onaxis=0
withagg
oraggregate
. - Added support for
by
,left_by
,right_by
,left_index
, andright_index
forpd.merge_asof
. - Added support for passing parameter
include_describe
toSession.query_history
. - Added support for
DatetimeIndex.mean
andDatetimeIndex.std
methods. - Added support for
Resampler.asfreq
,Resampler.indices
,Resampler.nunique
, andResampler.quantile
. - Added support for
resample
frequencyW
,ME
,YE
withclosed = "left"
. - Added support for
DataFrame.rolling.corr
andSeries.rolling.corr
forpairwise = False
and intwindow
. - Added support for string time-based
window
andmin_periods = None
forRolling
. - Added support for
DataFrameGroupBy.fillna
andSeriesGroupBy.fillna
. - Added support for constructing
Series
andDataFrame
objects with the lazyIndex
object asdata
,index
, andcolumns
arguments. - Added support for constructing
Series
andDataFrame
objects withindex
andcolumn
values not present inDataFrame
/Series
data
. - Added support for
pd.read_sas
(Uses native pandas for processing). - Added support for applying
rolling().count()
andexpanding().count()
toTimedelta
series and columns. - Added support for
tz
in bothpd.date_range
andpd.bdate_range
. - Added support for
Series.items
. - Added support for
errors="ignore"
inpd.to_datetime
. - Added support for
DataFrame.tz_localize
andSeries.tz_localize
. - Added support for
DataFrame.tz_convert
andSeries.tz_convert
. - Added support for applying Snowpark Python functions (e.g.,
sin
) inSeries.map
,Series.apply
,DataFrame.apply
andDataFrame.applymap
.
- Improved
to_pandas
to persist the original timezone offset for TIMESTAMP_TZ type. - Improved
dtype
results for TIMESTAMP_TZ type to show correct timezone offset. - Improved
dtype
results for TIMESTAMP_LTZ type to show correct timezone. - Improved error message when passing non-bool value to
numeric_only
for groupby aggregations. - Removed unnecessary warning about sort algorithm in
sort_values
. - Use SCOPED object for internal create temp tables. The SCOPED objects will be stored sproc scoped if created within stored sproc, otherwise will be session scoped, and the object will be automatically cleaned at the end of the scope.
- Improved warning messages for operations that lead to materialization with inadvertent slowness.
- Removed unnecessary warning message about
convert_dtype
inSeries.apply
.
- Fixed a bug where an
Index
object created from aSeries
/DataFrame
incorrectly updates theSeries
/DataFrame
's index name after an inplace update has been applied to the originalSeries
/DataFrame
. - Suppressed an unhelpful
SettingWithCopyWarning
that sometimes appeared when printingTimedelta
columns. - Fixed
inplace
argument forSeries
objects derived from otherSeries
objects. - Fixed a bug where
Series.sort_values
failed if series name overlapped with index column name. - Fixed a bug where transposing a dataframe would map
Timedelta
index levels to integer column levels. - Fixed a bug where
Resampler
methods on timedelta columns would produce integer results. - Fixed a bug where
pd.to_numeric()
would leaveTimedelta
inputs asTimedelta
instead of converting them to integers. - Fixed
loc
set when setting a single row, or multiple rows, of a DataFrame with a Series value.
- Fixed a bug where nullable columns were annotated wrongly.
- Fixed a bug where the
date_add
anddate_sub
functions failed forNULL
values. - Fixed a bug where
equal_null
could fail inside a merge statement. - Fixed a bug where
row_number
could fail inside a Window function. - Fixed a bug where updates could fail when the source is the result of a join.
This is a re-release of 1.22.0. Please refer to the 1.22.0 release notes for detailed release content.
- Added the following new functions in
snowflake.snowpark.functions
:array_remove
ln
- Improved documentation for
Session.write_pandas
by makinguse_logical_type
option more explicit. - Added support for specifying the following to
DataFrameWriter.save_as_table
:enable_schema_evolution
data_retention_time
max_data_extension_time
change_tracking
copy_grants
iceberg_config
A dicitionary that can hold the following iceberg configuration options:external_volume
catalog
base_location
catalog_sync
storage_serialization_policy
- Added support for specifying the following to
DataFrameWriter.copy_into_table
:iceberg_config
A dicitionary that can hold the following iceberg configuration options:external_volume
catalog
base_location
catalog_sync
storage_serialization_policy
- Added support for specifying the following parameters to
DataFrame.create_or_replace_dynamic_table
:mode
refresh_mode
initialize
clustering_keys
is_transient
data_retention_time
max_data_extension_time
- Fixed a bug in
session.read.csv
that caused an error when settingPARSE_HEADER = True
in an externally defined file format. - Fixed a bug in query generation from set operations that allowed generation of duplicate queries when children have common subqueries.
- Fixed a bug in
session.get_session_stage
that referenced a non-existing stage after switching database or schema. - Fixed a bug where calling
DataFrame.to_snowpark_pandas
without explicitly initializing the Snowpark pandas plugin caused an error. - Fixed a bug where using the
explode
function in dynamic table creation caused a SQL compilation error due to improper boolean type casting on theouter
parameter.
- Added support for type coercion when passing columns as input to UDF calls.
- Added support for
Index.identical
.
- Fixed a bug where the truncate mode in
DataFrameWriter.save_as_table
incorrectly handled DataFrames containing only a subset of columns from the existing table. - Fixed a bug where function
to_timestamp
does not set the default timezone of the column datatype.
- Added limited support for the
Timedelta
type, including the following features. Snowpark pandas will raiseNotImplementedError
for unsupportedTimedelta
use cases.- supporting tracking the Timedelta type through
copy
,cache_result
,shift
,sort_index
,assign
,bfill
,ffill
,fillna
,compare
,diff
,drop
,dropna
,duplicated
,empty
,equals
,insert
,isin
,isna
,items
,iterrows
,join
,len
,mask
,melt
,merge
,nlargest
,nsmallest
,to_pandas
. - converting non-timedelta to timedelta via
astype
. NotImplementedError
will be raised for the rest of methods that do not supportTimedelta
.- support for subtracting two timestamps to get a Timedelta.
- support indexing with Timedelta data columns.
- support for adding or subtracting timestamps and
Timedelta
. - support for binary arithmetic between two
Timedelta
values. - support for binary arithmetic and comparisons between
Timedelta
values and numeric values. - support for lazy
TimedeltaIndex
. - support for
pd.to_timedelta
. - support for
GroupBy
aggregationsmin
,max
,mean
,idxmax
,idxmin
,std
,sum
,median
,count
,any
,all
,size
,nunique
,head
,tail
,aggregate
. - support for
GroupBy
filtrationsfirst
andlast
. - support for
TimedeltaIndex
attributes:days
,seconds
,microseconds
andnanoseconds
. - support for
diff
with timestamp columns onaxis=0
andaxis=1
- support for
TimedeltaIndex
methods:ceil
,floor
andround
. - support for
TimedeltaIndex.total_seconds
method.
- supporting tracking the Timedelta type through
- Added support for index's arithmetic and comparison operators.
- Added support for
Series.dt.round
. - Added documentation pages for
DatetimeIndex
. - Added support for
Index.name
,Index.names
,Index.rename
, andIndex.set_names
. - Added support for
Index.__repr__
. - Added support for
DatetimeIndex.month_name
andDatetimeIndex.day_name
. - Added support for
Series.dt.weekday
,Series.dt.time
, andDatetimeIndex.time
. - Added support for
Index.min
andIndex.max
. - Added support for
pd.merge_asof
. - Added support for
Series.dt.normalize
andDatetimeIndex.normalize
. - Added support for
Index.is_boolean
,Index.is_integer
,Index.is_floating
,Index.is_numeric
, andIndex.is_object
. - Added support for
DatetimeIndex.round
,DatetimeIndex.floor
andDatetimeIndex.ceil
. - Added support for
Series.dt.days_in_month
andSeries.dt.daysinmonth
. - Added support for
DataFrameGroupBy.value_counts
andSeriesGroupBy.value_counts
. - Added support for
Series.is_monotonic_increasing
andSeries.is_monotonic_decreasing
. - Added support for
Index.is_monotonic_increasing
andIndex.is_monotonic_decreasing
. - Added support for
pd.crosstab
. - Added support for
pd.bdate_range
and included business frequency support (B, BME, BMS, BQE, BQS, BYE, BYS) for bothpd.date_range
andpd.bdate_range
. - Added support for lazy
Index
objects aslabels
inDataFrame.reindex
andSeries.reindex
. - Added support for
Series.dt.days
,Series.dt.seconds
,Series.dt.microseconds
, andSeries.dt.nanoseconds
. - Added support for creating a
DatetimeIndex
from anIndex
of numeric or string type. - Added support for string indexing with
Timedelta
objects. - Added support for
Series.dt.total_seconds
method. - Added support for
DataFrame.apply(axis=0)
. - Added support for
Series.dt.tz_convert
andSeries.dt.tz_localize
. - Added support for
DatetimeIndex.tz_convert
andDatetimeIndex.tz_localize
.
- Improve concat, join performance when operations are performed on series coming from the same dataframe by avoiding unnecessary joins.
- Refactored
quoted_identifier_to_snowflake_type
to avoid making metadata queries if the types have been cached locally. - Improved
pd.to_datetime
to handle all local input cases. - Create a lazy index from another lazy index without pulling data to client.
- Raised
NotImplementedError
for Index bitwise operators. - Display a more clear error message when
Index.names
is set to a non-like-like object. - Raise a warning whenever MultiIndex values are pulled in locally.
- Improve warning message for
pd.read_snowflake
include the creation reason when temp table creation is triggered. - Improve performance for
DataFrame.set_index
, or settingDataFrame.index
orSeries.index
by avoiding checks require eager evaluation. As a consequence, when the new index that does not match the currentSeries
/DataFrame
object length, aValueError
is no longer raised. Instead, when theSeries
/DataFrame
object is longer than the provided index, theSeries
/DataFrame
's new index is filled withNaN
values for the "extra" elements. Otherwise, the extra values in the provided index are ignored. - Properly raise
NotImplementedError
when ambiguous/nonexistent are non-string inceil
/floor
/round
.
- Stopped ignoring nanoseconds in
pd.Timedelta
scalars. - Fixed AssertionError in tree of binary operations.
- Fixed bug in
Series.dt.isocalendar
using a named Series - Fixed
inplace
argument for Series objects derived from DataFrame columns. - Fixed a bug where
Series.reindex
andDataFrame.reindex
did not update the result index's name correctly. - Fixed a bug where
Series.take
did not error whenaxis=1
was specified.
- Fixed a bug where using
to_pandas_batches
with async jobs caused an error due to improper handling of waiting for asynchronous query completion.
- Added support for
snowflake.snowpark.testing.assert_dataframe_equal
that is a utility function to check the equality of two Snowpark DataFrames.
- Added support server side string size limitations.
- Added support to create and invoke stored procedures, UDFs and UDTFs with optional arguments.
- Added support for column lineage in the DataFrame.lineage.trace API.
- Added support for passing
INFER_SCHEMA
options toDataFrameReader
viaINFER_SCHEMA_OPTIONS
. - Added support for passing
parameters
parameter toColumn.rlike
andColumn.regexp
. - Added support for automatically cleaning up temporary tables created by
df.cache_result()
in the current session, when the DataFrame is no longer referenced (i.e., gets garbage collected). It is still an experimental feature not enabled by default, and can be enabled by settingsession.auto_clean_up_temp_table_enabled
toTrue
. - Added support for string literals to the
fmt
parameter ofsnowflake.snowpark.functions.to_date
. - Added support for system$reference function.
- Fixed a bug where SQL generated for selecting
*
column has an incorrect subquery. - Fixed a bug in
DataFrame.to_pandas_batches
where the iterator could throw an error if certain transformation is made to the pandas dataframe due to wrong isolation level. - Fixed a bug in
DataFrame.lineage.trace
to split the quoted feature view's name and version correctly. - Fixed a bug in
Column.isin
that caused invalid sql generation when passed an empty list. - Fixed a bug that fails to raise NotImplementedError while setting cell with list like item.
- Added support for the following APIs:
- snowflake.snowpark.functions
rank
dense_rank
percent_rank
cume_dist
ntile
datediff
array_agg
- snowflake.snowpark.column.Column.within_group
- snowflake.snowpark.functions
- Added support for parsing flags in regex statements for mocked plans. This maintains parity with the
rlike
andregexp
changes above.
- Fixed a bug where Window Functions LEAD and LAG do not handle option
ignore_nulls
properly. - Fixed a bug where values were not populated into the result DataFrame during the insertion of table merge operation.
- Fix pandas FutureWarning about integer indexing.
- Added support for
DataFrame.backfill
,DataFrame.bfill
,Series.backfill
, andSeries.bfill
. - Added support for
DataFrame.compare
andSeries.compare
with default parameters. - Added support for
Series.dt.microsecond
andSeries.dt.nanosecond
. - Added support for
Index.is_unique
andIndex.has_duplicates
. - Added support for
Index.equals
. - Added support for
Index.value_counts
. - Added support for
Series.dt.day_name
andSeries.dt.month_name
. - Added support for indexing on Index, e.g.,
df.index[:10]
. - Added support for
DataFrame.unstack
andSeries.unstack
. - Added support for
DataFrame.asfreq
andSeries.asfreq
. - Added support for
Series.dt.is_month_start
andSeries.dt.is_month_end
. - Added support for
Index.all
andIndex.any
. - Added support for
Series.dt.is_year_start
andSeries.dt.is_year_end
. - Added support for
Series.dt.is_quarter_start
andSeries.dt.is_quarter_end
. - Added support for lazy
DatetimeIndex
. - Added support for
Series.argmax
andSeries.argmin
. - Added support for
Series.dt.is_leap_year
. - Added support for
DataFrame.items
. - Added support for
Series.dt.floor
andSeries.dt.ceil
. - Added support for
Index.reindex
. - Added support for
DatetimeIndex
properties:year
,month
,day
,hour
,minute
,second
,microsecond
,nanosecond
,date
,dayofyear
,day_of_year
,dayofweek
,day_of_week
,weekday
,quarter
,is_month_start
,is_month_end
,is_quarter_start
,is_quarter_end
,is_year_start
,is_year_end
andis_leap_year
. - Added support for
Resampler.fillna
andResampler.bfill
. - Added limited support for the
Timedelta
type, including creatingTimedelta
columns andto_pandas
. - Added support for
Index.argmax
andIndex.argmin
.
- Removed the public preview warning message when importing Snowpark pandas.
- Removed unnecessary count query from
SnowflakeQueryCompiler.is_series_like
method. Dataframe.columns
now returns native pandas Index object instead of Snowpark Index object.- Refactor and introduce
query_compiler
argument inIndex
constructor to createIndex
from query compiler. pd.to_datetime
now returns a DatetimeIndex object instead of a Series object.pd.date_range
now returns a DatetimeIndex object instead of a Series object.
- Made passing an unsupported aggregation function to
pivot_table
raiseNotImplementedError
instead ofKeyError
. - Removed axis labels and callable names from error messages and telemetry about unsupported aggregations.
- Fixed AssertionError in
Series.drop_duplicates
andDataFrame.drop_duplicates
when called aftersort_values
. - Fixed a bug in
Index.to_frame
where the result frame's column name may be wrong where name is unspecified. - Fixed a bug where some Index docstrings are ignored.
- Fixed a bug in
Series.reset_index(drop=True)
where the result name may be wrong. - Fixed a bug in
Groupby.first/last
ordering by the correct columns in the underlying window expression.
- Added distributed tracing using open telemetry APIs for table stored procedure function in
DataFrame
:_execute_and_get_query_id
- Added support for the
arrays_zip
function. - Improves performance for binary column expression and
df._in
by avoiding unnecessary cast for numeric values. You can enable this optimization by settingsession.eliminate_numeric_sql_value_cast_enabled = True
. - Improved error message for
write_pandas
when the target table does not exist andauto_create_table=False
. - Added open telemetry tracing on UDxF functions in Snowpark.
- Added open telemetry tracing on stored procedure registration in Snowpark.
- Added a new optional parameter called
format_json
to theSession.SessionBuilder.app_name
function that sets the app name in theSession.query_tag
in JSON format. By default, this parameter is set toFalse
.
- Fixed a bug where SQL generated for
lag(x, 0)
was incorrect and failed with error messageargument 1 to function LAG needs to be constant, found 'SYSTEM$NULL_TO_FIXED(null)'
.
- Added support for the following APIs:
- snowflake.snowpark.functions
- random
- snowflake.snowpark.functions
- Added new parameters to
patch
function when registering a mocked function:distinct
allows an alternate function to be specified for when a sql function should be distinct.pass_column_index
passes a named parametercolumn_index
to the mocked function that contains the pandas.Index for the input data.pass_row_index
passes a named parameterrow_index
to the mocked function that is the 0 indexed row number the function is currently operating on.pass_input_data
passes a named parameterinput_data
to the mocked function that contains the entire input dataframe for the current expression.- Added support for the
column_order
parameter to methodDataFrameWriter.save_as_table
.
- Fixed a bug that caused DecimalType columns to be incorrectly truncated to integer precision when used in BinaryExpressions.
- Added support for
DataFrameGroupBy.all
,SeriesGroupBy.all
,DataFrameGroupBy.any
, andSeriesGroupBy.any
. - Added support for
DataFrame.nlargest
,DataFrame.nsmallest
,Series.nlargest
andSeries.nsmallest
. - Added support for
replace
andfrac > 1
inDataFrame.sample
andSeries.sample
. - Added support for
read_excel
(Uses local pandas for processing) - Added support for
Series.at
,Series.iat
,DataFrame.at
, andDataFrame.iat
. - Added support for
Series.dt.isocalendar
. - Added support for
Series.case_when
except when condition or replacement is callable. - Added documentation pages for
Index
and its APIs. - Added support for
DataFrame.assign
. - Added support for
DataFrame.stack
. - Added support for
DataFrame.pivot
andpd.pivot
. - Added support for
DataFrame.to_csv
andSeries.to_csv
. - Added partial support for
Series.str.translate
where the values in thetable
are single-codepoint strings. - Added support for
DataFrame.corr
. - Allow
df.plot()
andseries.plot()
to be called, materializing the data into the local client - Added support for
DataFrameGroupBy
andSeriesGroupBy
aggregationsfirst
andlast
- Added support for
DataFrameGroupBy.get_group
. - Added support for
limit
parameter whenmethod
parameter is used infillna
. - Added partial support for
Series.str.translate
where the values in thetable
are single-codepoint strings. - Added support for
DataFrame.corr
. - Added support for
DataFrame.equals
andSeries.equals
. - Added support for
DataFrame.reindex
andSeries.reindex
. - Added support for
Index.astype
. - Added support for
Index.unique
andIndex.nunique
. - Added support for
Index.sort_values
.
- Fixed an issue when using np.where and df.where when the scalar 'other' is the literal 0.
- Fixed a bug regarding precision loss when converting to Snowpark pandas
DataFrame
orSeries
withdtype=np.uint64
. - Fixed bug where
values
is set toindex
whenindex
andcolumns
contain all columns in DataFrame duringpivot_table
.
- Added support for
Index.copy()
- Added support for Index APIs:
dtype
,values
,item()
,tolist()
,to_series()
andto_frame()
- Expand support for DataFrames with no rows in
pd.pivot_table
andDataFrame.pivot_table
. - Added support for
inplace
parameter inDataFrame.sort_index
andSeries.sort_index
.
- Added support for
to_boolean
function. - Added documentation pages for Index and its APIs.
- Fixed a bug where python stored procedure with table return type fails when run in a task.
- Fixed a bug where df.dropna fails due to
RecursionError: maximum recursion depth exceeded
when the DataFrame has more than 500 columns. - Fixed a bug where
AsyncJob.result("no_result")
doesn't wait for the query to finish execution.
- Added support for the
strict
parameter when registering UDFs and Stored Procedures.
- Fixed a bug in convert_timezone that made the setting the source_timezone parameter return an error.
- Fixed a bug where creating DataFrame with empty data of type
DateType
raisesAttributeError
. - Fixed a bug that table merge fails when update clause exists but no update takes place.
- Fixed a bug in mock implementation of
to_char
that raisesIndexError
when incoming column has nonconsecutive row index. - Fixed a bug in handling of
CaseExpr
expressions that raisesIndexError
when incoming column has nonconsecutive row index. - Fixed a bug in implementation of
Column.like
that raisesIndexError
when incoming column has nonconsecutive row index.
- Added support for type coercion in the implementation of DataFrame.replace, DataFrame.dropna and the mock function
iff
.
- Added partial support for
DataFrame.pct_change
andSeries.pct_change
without thefreq
andlimit
parameters. - Added support for
Series.str.get
. - Added support for
Series.dt.dayofweek
,Series.dt.day_of_week
,Series.dt.dayofyear
, andSeries.dt.day_of_year
. - Added support for
Series.str.__getitem__
(Series.str[...]
). - Added support for
Series.str.lstrip
andSeries.str.rstrip
. - Added support for
DataFrameGroupBy.size
andSeriesGroupBy.size
. - Added support for
DataFrame.expanding
andSeries.expanding
for aggregationscount
,sum
,min
,max
,mean
,std
,var
, andsem
withaxis=0
. - Added support for
DataFrame.rolling
andSeries.rolling
for aggregationcount
withaxis=0
. - Added support for
Series.str.match
. - Added support for
DataFrame.resample
andSeries.resample
for aggregationssize
,first
, andlast
. - Added support for
DataFrameGroupBy.all
,SeriesGroupBy.all
,DataFrameGroupBy.any
, andSeriesGroupBy.any
. - Added support for
DataFrame.nlargest
,DataFrame.nsmallest
,Series.nlargest
andSeries.nsmallest
. - Added support for
replace
andfrac > 1
inDataFrame.sample
andSeries.sample
. - Added support for
read_excel
(Uses local pandas for processing) - Added support for
Series.at
,Series.iat
,DataFrame.at
, andDataFrame.iat
. - Added support for
Series.dt.isocalendar
. - Added support for
Series.case_when
except when condition or replacement is callable. - Added documentation pages for
Index
and its APIs. - Added support for
DataFrame.assign
. - Added support for
DataFrame.stack
. - Added support for
DataFrame.pivot
andpd.pivot
. - Added support for
DataFrame.to_csv
andSeries.to_csv
. - Added support for
Index.T
.
- Fixed a bug that causes output of GroupBy.aggregate's columns to be ordered incorrectly.
- Fixed a bug where
DataFrame.describe
on a frame with duplicate columns of differing dtypes could cause an error or incorrect results. - Fixed a bug in
DataFrame.rolling
andSeries.rolling
sowindow=0
now throwsNotImplementedError
instead ofValueError
- Added support for named aggregations in
DataFrame.aggregate
andSeries.aggregate
withaxis=0
. pd.read_csv
reads using the native pandas CSV parser, then uploads data to snowflake using parquet. This enables most of the parameters supported byread_csv
including date parsing and numeric conversions. Uploading via parquet is roughly twice as fast as uploading via CSV.- Initial work to support an
pd.Index
directly in Snowpark pandas. Support forpd.Index
as a first-class component of Snowpark pandas is coming soon. - Added a lazy index constructor and support for
len
,shape
,size
,empty
,to_pandas()
andnames
. Fordf.index
, Snowpark pandas creates a lazy index object. - For
df.columns
, Snowpark pandas supports a non-lazy version of anIndex
since the data is already stored locally.
- Improved error message to remind users set
{"infer_schema": True}
when reading csv file without specifying its schema. - Improved error handling for
Session.create_dataframe
when called with more than 512 rows and usingformat
orpyformat
paramstyle
.
- Added
DataFrame.cache_result
andSeries.cache_result
methods for users to persist DataFrames and Series to a temporary table lasting the duration of the session to improve latency of subsequent operations.
- Added partial support for
DataFrame.pivot_table
with noindex
parameter, as well as formargins
parameter. - Updated the signature of
DataFrame.shift
/Series.shift
/DataFrameGroupBy.shift
/SeriesGroupBy.shift
to match pandas 2.2.1. Snowpark pandas does not yet support the newly-addedsuffix
argument, or sequence values ofperiods
. - Re-added support for
Series.str.split
.
- Fixed how we support mixed columns for string methods (
Series.str.*
).
- Added support for the following DataFrameReader read options to file formats
csv
andjson
:- PURGE
- PATTERN
- INFER_SCHEMA with value being
False
- ENCODING with value being
UTF8
- Added support for
DataFrame.analytics.moving_agg
andDataFrame.analytics.cumulative_agg_agg
. - Added support for
if_not_exists
parameter during UDF and stored procedure registration.
- Fixed a bug that when processing time format, fractional second part is not handled properly.
- Fixed a bug that caused function calls on
*
to fail. - Fixed a bug that prevented creation of map and struct type objects.
- Fixed a bug that function
date_add
was unable to handle some numeric types. - Fixed a bug that
TimestampType
casting resulted in incorrect data. - Fixed a bug that caused
DecimalType
data to have incorrect precision in some cases. - Fixed a bug where referencing missing table or view raises confusing
IndexError
. - Fixed a bug that mocked function
to_timestamp_ntz
can not handle None data. - Fixed a bug that mocked UDFs handles output data of None improperly.
- Fixed a bug where
DataFrame.with_column_renamed
ignores attributes from parent DataFrames after join operations. - Fixed a bug that integer precision of large value gets lost when converted to pandas DataFrame.
- Fixed a bug that the schema of datetime object is wrong when create DataFrame from a pandas DataFrame.
- Fixed a bug in the implementation of
Column.equal_nan
where null data is handled incorrectly. - Fixed a bug where
DataFrame.drop
ignore attributes from parent DataFrames after join operations. - Fixed a bug in mocked function
date_part
where Column type is set wrong. - Fixed a bug where
DataFrameWriter.save_as_table
does not raise exceptions when inserting null data into non-nullable columns. - Fixed a bug in the implementation of
DataFrameWriter.save_as_table
where- Append or Truncate fails when incoming data has different schema than existing table.
- Truncate fails when incoming data does not specify columns that are nullable.
- Removed dependency check for
pyarrow
as it is not used. - Improved target type coverage of
Column.cast
, adding support for casting to boolean and all integral types. - Aligned error experience when calling UDFs and stored procedures.
- Added appropriate error messages for
is_permanent
andanonymous
options in UDFs and stored procedures registration to make it more clear that those features are not yet supported. - File read operation with unsupported options and values now raises
NotImplementedError
instead of warnings and unclear error information.
- Added support to add a comment on tables and views using the functions listed below:
DataFrameWriter.save_as_table
DataFrame.create_or_replace_view
DataFrame.create_or_replace_temp_view
DataFrame.create_or_replace_dynamic_table
- Improved error message to remind users to set
{"infer_schema": True}
when reading CSV file without specifying its schema.
- Start of Public Preview of Snowpark pandas API. Refer to the Snowpark pandas API Docs for more details.
- Added support for NumericType and VariantType data conversion in the mocked function
to_timestamp_ltz
,to_timestamp_ntz
,to_timestamp_tz
andto_timestamp
. - Added support for DecimalType, BinaryType, ArrayType, MapType, TimestampType, DateType and TimeType data conversion in the mocked function
to_char
. - Added support for the following APIs:
- snowflake.snowpark.functions:
- to_varchar
- snowflake.snowpark.DataFrame:
- pivot
- snowflake.snowpark.Session:
- cancel_all
- snowflake.snowpark.functions:
- Introduced a new exception class
snowflake.snowpark.mock.exceptions.SnowparkLocalTestingException
. - Added support for casting to FloatType
- Fixed a bug that stored procedure and UDF should not remove imports already in the
sys.path
during the clean-up step. - Fixed a bug that when processing datetime format, the fractional second part is not handled properly.
- Fixed a bug that on Windows platform that file operations was unable to properly handle file separator in directory name.
- Fixed a bug that on Windows platform that when reading a pandas dataframe, IntervalType column with integer data can not be processed.
- Fixed a bug that prevented users from being able to select multiple columns with the same alias.
- Fixed a bug that
Session.get_current_[schema|database|role|user|account|warehouse]
returns upper-cased identifiers when identifiers are quoted. - Fixed a bug that function
substr
andsubstring
can not handle 0-basedstart_expr
.
- Standardized the error experience by raising
SnowparkLocalTestingException
in error cases which is on par withSnowparkSQLException
raised in non-local execution. - Improved error experience of
Session.write_pandas
method thatNotImplementError
will be raised when called. - Aligned error experience with reusing a closed session in non-local execution.
- Support stored procedure register with packages given as Python modules.
- Added snowflake.snowpark.Session.lineage.trace to explore data lineage of snowfake objects.
- Added support for structured type schema parsing.
- Fixed a bug when inferring schema, single quotes are added to stage files already have single quotes.
- Added support for StringType, TimestampType and VariantType data conversion in the mocked function
to_date
. - Added support for the following APIs:
- snowflake.snowpark.functions
- get
- concat
- concat_ws
- snowflake.snowpark.functions
- Fixed a bug that caused
NaT
andNaN
values to not be recognized. - Fixed a bug where, when inferring a schema, single quotes were added to stage files that already had single quotes.
- Fixed a bug where
DataFrameReader.csv
was unable to handle quoted values containing a delimiter. - Fixed a bug that when there is
None
value in an arithmetic calculation, the output should remainNone
instead ofmath.nan
. - Fixed a bug in function
sum
andcovar_pop
that when there ismath.nan
in the data, the output should also bemath.nan
. - Fixed a bug that stage operation can not handle directories.
- Fixed a bug that
DataFrame.to_pandas
should take Snowflake numeric types with precision 38 asint64
.
- Added
truncate
save mode inDataFrameWrite
to overwrite existing tables by truncating the underlying table instead of dropping it. - Added telemetry to calculate query plan height and number of duplicate nodes during collect operations.
- Added the functions below to unload data from a
DataFrame
into one or more files in a stage:DataFrame.write.json
DataFrame.write.csv
DataFrame.write.parquet
- Added distributed tracing using open telemetry APIs for action functions in
DataFrame
andDataFrameWriter
:- snowflake.snowpark.DataFrame:
- collect
- collect_nowait
- to_pandas
- count
- show
- snowflake.snowpark.DataFrameWriter:
- save_as_table
- snowflake.snowpark.DataFrame:
- Added support for snow:// URLs to
snowflake.snowpark.Session.file.get
andsnowflake.snowpark.Session.file.get_stream
- Added support to register stored procedures and UDxFs with a
comment
. - UDAF client support is ready for public preview. Please stay tuned for the Snowflake announcement of UDAF public preview.
- Added support for dynamic pivot. This feature is currently in private preview.
- Improved the generated query performance for both compilation and execution by converting duplicate subqueries to Common Table Expressions (CTEs). It is still an experimental feature not enabled by default, and can be enabled by setting
session.cte_optimization_enabled
toTrue
.
- Fixed a bug where
statement_params
was not passed to query executions that register stored procedures and user defined functions. - Fixed a bug causing
snowflake.snowpark.Session.file.get_stream
to fail for quoted stage locations. - Fixed a bug that an internal type hint in
utils.py
might raise AttributeError in case the underlying module can not be found.
- Added support for registering UDFs and stored procedures.
- Added support for the following APIs:
- snowflake.snowpark.Session:
- file.put
- file.put_stream
- file.get
- file.get_stream
- read.json
- add_import
- remove_import
- get_imports
- clear_imports
- add_packages
- add_requirements
- clear_packages
- remove_package
- udf.register
- udf.register_from_file
- sproc.register
- sproc.register_from_file
- snowflake.snowpark.functions
- current_database
- current_session
- date_trunc
- object_construct
- object_construct_keep_null
- pow
- sqrt
- udf
- sproc
- snowflake.snowpark.Session:
- Added support for StringType, TimestampType and VariantType data conversion in the mocked function
to_time
.
- Fixed a bug that null filled columns for constant functions.
- Fixed a bug that implementation of to_object, to_array and to_binary to better handle null inputs.
- Fixed a bug that timestamp data comparison can not handle year beyond 2262.
- Fixed a bug that
Session.builder.getOrCreate
should return the created mock session.
- Added support for creating vectorized UDTFs with
process
method. - Added support for dataframe functions:
- to_timestamp_ltz
- to_timestamp_ntz
- to_timestamp_tz
- locate
- Added support for ASOF JOIN type.
- Added support for the following local testing APIs:
- snowflake.snowpark.functions:
- to_double
- to_timestamp
- to_timestamp_ltz
- to_timestamp_ntz
- to_timestamp_tz
- greatest
- least
- convert_timezone
- dateadd
- date_part
- snowflake.snowpark.Session:
- get_current_account
- get_current_warehouse
- get_current_role
- use_schema
- use_warehouse
- use_database
- use_role
- snowflake.snowpark.functions:
- Fixed a bug in
SnowflakePlanBuilder
thatsave_as_table
does not filter column that name start with '$' and follow by number correctly. - Fixed a bug that statement parameters may have no effect when resolving imports and packages.
- Fixed bugs in local testing:
- LEFT ANTI and LEFT SEMI joins drop rows with null values.
- DataFrameReader.csv incorrectly parses data when the optional parameter
field_optionally_enclosed_by
is specified. - Column.regexp only considers the first entry when
pattern
is aColumn
. - Table.update raises
KeyError
when updating null values in the rows. - VARIANT columns raise errors at
DataFrame.collect
. count_distinct
does not work correctly when counting.- Null values in integer columns raise
TypeError
.
- Added telemetry to local testing.
- Improved the error message of
DataFrameReader
to raiseFileNotFound
error when reading a path that does not exist or when there are no files under the path.
- Added support for an optional
date_part
argument in functionlast_day
. SessionBuilder.app_name
will set the query_tag after the session is created.- Added support for the following local testing functions:
- current_timestamp
- current_date
- current_time
- strip_null_value
- upper
- lower
- length
- initcap
- Added cleanup logic at interpreter shutdown to close all active sessions.
- Closing sessions within stored procedures now is a no-op logging a warning instead of raising an error.
- Fixed a bug in
DataFrame.to_local_iterator
where the iterator could yield wrong results if another query is executed before the iterator finishes due to wrong isolation level. For details, please see #945. - Fixed a bug that truncated table names in error messages while running a plan with local testing enabled.
- Fixed a bug that
Session.range
returns empty result when the range is large.
- Use
split_blocks=True
by default duringto_pandas
conversion, for optimal memory allocation. This parameter is passed topyarrow.Table.to_pandas
, which enablesPyArrow
to split the memory allocation into smaller, more manageable blocks instead of allocating a single contiguous block. This results in better memory management when dealing with larger datasets.
- Fixed a bug in
DataFrame.to_pandas
that caused an error when evaluating on a Dataframe with anIntergerType
column with null values.
- Exposed
statement_params
inStoredProcedure.__call__
. - Added two optional arguments to
Session.add_import
.chunk_size
: The number of bytes to hash per chunk of the uploaded files.whole_file_hash
: By default only the first chunk of the uploaded import is hashed to save time. When this is set to True each uploaded file is fully hashed instead.
- Added parameters
external_access_integrations
andsecrets
when creating a UDAF from Snowpark Python to allow integration with external access. - Added a new method
Session.append_query_tag
. Allows an additional tag to be added to the current query tag by appending it as a comma separated value. - Added a new method
Session.update_query_tag
. Allows updates to a JSON encoded dictionary query tag. SessionBuilder.getOrCreate
will now attempt to replace the singleton it returns when token expiration has been detected.- Added support for new functions in
snowflake.snowpark.functions
:array_except
create_map
sign
/signum
- Added the following functions to
DataFrame.analytics
:- Added the
moving_agg
function inDataFrame.analytics
to enable moving aggregations like sums and averages with multiple window sizes. - Added the
cummulative_agg
function inDataFrame.analytics
to enable commulative aggregations like sums and averages on multiple columns. - Added the
compute_lag
andcompute_lead
functions inDataFrame.analytics
for enabling lead and lag calculations on multiple columns. - Added the
time_series_agg
function inDataFrame.analytics
to enable time series aggregations like sums and averages with multiple time windows.
- Added the
-
Fixed a bug in
DataFrame.na.fill
that caused Boolean values to erroneously override integer values. -
Fixed a bug in
Session.create_dataframe
where the Snowpark DataFrames created using pandas DataFrames were not inferring the type for timestamp columns correctly. The behavior is as follows:- Earlier timestamp columns without a timezone would be converted to nanosecond epochs and inferred as
LongType()
, but will now be correctly maintained as timestamp values and be inferred asTimestampType(TimestampTimeZone.NTZ)
. - Earlier timestamp columns with a timezone would be inferred as
TimestampType(TimestampTimeZone.NTZ)
and loose timezone information but will now be correctly inferred asTimestampType(TimestampTimeZone.LTZ)
and timezone information is retained correctly. - Set session parameter
PYTHON_SNOWPARK_USE_LOGICAL_TYPE_FOR_CREATE_DATAFRAME
to revert back to old behavior. It is recommended that you update your code to align with correct behavior because the parameter will be removed in the future.
- Earlier timestamp columns without a timezone would be converted to nanosecond epochs and inferred as
-
Fixed a bug that
DataFrame.to_pandas
gets decimal type when scale is not 0, and creates an object dtype inpandas
. Instead, we cast the value to a float64 type. -
Fixed bugs that wrongly flattened the generated SQL when one of the following happens:
DataFrame.filter()
is called afterDataFrame.sort().limit()
.DataFrame.sort()
orfilter()
is called on a DataFrame that already has a window function or sequence-dependent data generator column. For instance,df.select("a", seq1().alias("b")).select("a", "b").sort("a")
won't flatten the sort clause anymore.- a window or sequence-dependent data generator column is used after
DataFrame.limit()
. For instance,df.limit(10).select(row_number().over())
won't flatten the limit and select in the generated SQL.
-
Fixed a bug where aliasing a DataFrame column raised an error when the DataFame was copied from another DataFrame with an aliased column. For instance,
df = df.select(col("a").alias("b")) df = copy(df) df.select(col("b").alias("c")) # threw an error. Now it's fixed.
-
Fixed a bug in
Session.create_dataframe
that the non-nullable field in a schema is not respected for boolean type. Note that this fix is only effective when the user has the privilege to create a temp table. -
Fixed a bug in SQL simplifier where non-select statements in
session.sql
dropped a SQL query when used withlimit()
. -
Fixed a bug that raised an exception when session parameter
ERROR_ON_NONDETERMINISTIC_UPDATE
is true.
- When parsing data types during a
to_pandas
operation, we rely on GS precision value to fix precision issues for large integer values. This may affect users where a column that was earlier returned asint8
gets returned asint64
. Users can fix this by explicitly specifying precision values for their return column. - Aligned behavior for
Session.call
in case of table stored procedures where runningSession.call
would not trigger stored procedure unless acollect()
operation was performed. StoredProcedureRegistration
will now automatically addsnowflake-snowpark-python
as a package dependency. The added dependency will be on the client's local version of the library and an error is thrown if the server cannot support that version.
- Fixed a bug that numpy should not be imported at the top level of mock module.
- Added support for these new functions in
snowflake.snowpark.functions
:from_utc_timestamp
to_utc_timestamp
-
Add the
conn_error
attribute toSnowflakeSQLException
that stores the whole underlying exception fromsnowflake-connector-python
. -
Added support for
RelationalGroupedDataframe.pivot()
to accesspivot
in the following patternDataframe.group_by(...).pivot(...)
. -
Added experimental feature: Local Testing Mode, which allows you to create and operate on Snowpark Python DataFrames locally without connecting to a Snowflake account. You can use the local testing framework to test your DataFrame operations locally, on your development machine or in a CI (continuous integration) pipeline, before deploying code changes to your account.
-
Added support for
arrays_to_object
new functions insnowflake.snowpark.functions
. -
Added support for the vector data type.
- Bumped cloudpickle dependency to work with
cloudpickle==2.2.1
- Updated
snowflake-connector-python
to3.4.0
.
- DataFrame column names quoting check now supports newline characters.
- Fix a bug where a DataFrame generated by
session.read.with_metadata
creates inconsistent table when doingdf.write.save_as_table
.
- Added support for managing case sensitivity in
DataFrame.to_local_iterator()
. - Added support for specifying vectorized UDTF's input column names by using the optional parameter
input_names
inUDTFRegistration.register/register_file
andfunctions.pandas_udtf
. By default,RelationalGroupedDataFrame.applyInPandas
will infer the column names from current dataframe schema. - Add
sql_error_code
andraw_message
attributes toSnowflakeSQLException
when it is caused by a SQL exception.
- Fixed a bug in
DataFrame.to_pandas()
where converting snowpark dataframes to pandas dataframes was losing precision on integers with more than 19 digits. - Fixed a bug that
session.add_packages
can not handle requirement specifier that contains project name with underscore and version. - Fixed a bug in
DataFrame.limit()
whenoffset
is used and the parentDataFrame
useslimit
. Now theoffset
won't impact the parent DataFrame'slimit
. - Fixed a bug in
DataFrame.write.save_as_table
where dataframes created from read api could not save data into snowflake because of invalid column name$1
.
- Changed the behavior of
date_format
:- The
format
argument changed from optional to required. - The returned result changed from a date object to a date-formatted string.
- The
- When a window function, or a sequence-dependent data generator (
normal
,zipf
,uniform
,seq1
,seq2
,seq4
,seq8
) function is used, the sort and filter operation will no longer be flattened when generating the query.
- Added support for the Python 3.11 runtime environment.
- Added back the dependency of
typing-extensions
.
- Fixed a bug where imports from permanent stage locations were ignored for temporary stored procedures, UDTFs, UDFs, and UDAFs.
- Revert back to using CTAS (create table as select) statement for
Dataframe.writer.save_as_table
which does not need insert permission for writing tables.
- Support
PythonObjJSONEncoder
json-serializable objects forARRAY
andOBJECT
literals.
-
Added support for VOLATILE/IMMUTABLE keyword when registering UDFs.
-
Added support for specifying clustering keys when saving dataframes using
DataFrame.save_as_table
. -
Accept
Iterable
objects input forschema
when creating dataframes usingSession.create_dataframe
. -
Added the property
DataFrame.session
to return aSession
object. -
Added the property
Session.session_id
to return an integer that represents session ID. -
Added the property
Session.connection
to return aSnowflakeConnection
object . -
Added support for creating a Snowpark session from a configuration file or environment variables.
- Updated
snowflake-connector-python
to 3.2.0.
- Fixed a bug where automatic package upload would raise
ValueError
even when compatible package version were added insession.add_packages
. - Fixed a bug where table stored procedures were not registered correctly when using
register_from_file
. - Fixed a bug where dataframe joins failed with
invalid_identifier
error. - Fixed a bug where
DataFrame.copy
disables SQL simplfier for the returned copy. - Fixed a bug where
session.sql().select()
would fail if any parameters are specified tosession.sql()
- Added parameters
external_access_integrations
andsecrets
when creating a UDF, UDTF or Stored Procedure from Snowpark Python to allow integration with external access. - Added support for these new functions in
snowflake.snowpark.functions
:array_flatten
flatten
- Added support for
apply_in_pandas
insnowflake.snowpark.relational_grouped_dataframe
. - Added support for replicating your local Python environment on Snowflake via
Session.replicate_local_environment
.
- Fixed a bug where
session.create_dataframe
fails to properly set nullable columns where nullability was affected by order or data was given. - Fixed a bug where
DataFrame.select
could not identify and alias columns in presence of table functions when output columns of table function overlapped with columns in dataframe.
- When creating stored procedures, UDFs, UDTFs, UDAFs with parameter
is_permanent=False
will now create temporary objects even whenstage_name
is provided. The default value ofis_permanent
isFalse
which is why if this value is not explicitly set toTrue
for permanent objects, users will notice a change in behavior. types.StructField
now enquotes column identifier by default.
- Added support for these new functions in
snowflake.snowpark.functions
:array_sort
sort_array
array_min
array_max
explode_outer
- Added support for pure Python packages specified via
Session.add_requirements
orSession.add_packages
. They are now usable in stored procedures and UDFs even if packages are not present on the Snowflake Anaconda channel.- Added Session parameter
custom_packages_upload_enabled
andcustom_packages_force_upload_enabled
to enable the support for pure Python packages feature mentioned above. Both parameters default toFalse
.
- Added Session parameter
- Added support for specifying package requirements by passing a Conda environment yaml file to
Session.add_requirements
. - Added support for asynchronous execution of multi-query dataframes that contain binding variables.
- Added support for renaming multiple columns in
DataFrame.rename
. - Added support for Geometry datatypes.
- Added support for
params
insession.sql()
in stored procedures. - Added support for user-defined aggregate functions (UDAFs). This feature is currently in private preview.
- Added support for vectorized UDTFs (user-defined table functions). This feature is currently in public preview.
- Added support for Snowflake Timestamp variants (i.e.,
TIMESTAMP_NTZ
,TIMESTAMP_LTZ
,TIMESTAMP_TZ
)- Added
TimestampTimezone
as an argument inTimestampType
constructor. - Added type hints
NTZ
,LTZ
,TZ
andTimestamp
to annotate functions when registering UDFs.
- Added
- Removed redundant dependency
typing-extensions
. DataFrame.cache_result
now creates temp table fully qualified names under current database and current schema.
- Fixed a bug where type check happens on pandas before it is imported.
- Fixed a bug when creating a UDF from
numpy.ufunc
. - Fixed a bug where
DataFrame.union
was not generating the correctSelectable.schema_query
when SQL simplifier is enabled.
DataFrameWriter.save_as_table
now respects thenullable
field of the schema provided by the user or the inferred schema based on data from user input.
- Updated
snowflake-connector-python
to 3.0.4.
- Added support for the Python 3.10 runtime environment.
- Aggregation results, from functions such as
DataFrame.agg
andDataFrame.describe
, no longer strip away non-printing characters from column names.
- Added support for the Python 3.9 runtime environment.
- Added support for new functions in
snowflake.snowpark.functions
:array_generate_range
array_unique_agg
collect_set
sequence
- Added support for registering and calling stored procedures with
TABLE
return type. - Added support for parameter
length
inStringType()
to specify the maximum number of characters that can be stored by the column. - Added the alias
functions.element_at()
forfunctions.get()
. - Added the alias
Column.contains
forfunctions.contains
. - Added experimental feature
DataFrame.alias
. - Added support for querying metadata columns from stage when creating
DataFrame
usingDataFrameReader
. - Added support for
StructType.add
to append more fields to existingStructType
objects. - Added support for parameter
execute_as
inStoredProcedureRegistration.register_from_file()
to specify stored procedure caller rights.
- Fixed a bug where the
Dataframe.join_table_function
did not run all of the necessary queries to set up the join table function when SQL simplifier was enabled. - Fixed type hint declaration for custom types -
ColumnOrName
,ColumnOrLiteralStr
,ColumnOrSqlExpr
,LiteralType
andColumnOrLiteral
that were breakingmypy
checks. - Fixed a bug where
DataFrameWriter.save_as_table
andDataFrame.copy_into_table
failed to parse fully qualified table names.
- Added support for
session.getOrCreate
. - Added support for alias
Column.getField
. - Added support for new functions in
snowflake.snowpark.functions
:date_add
anddate_sub
to make add and subtract operations easier.daydiff
explode
array_distinct
.regexp_extract
.struct
.format_number
.bround
.substring_index
- Added parameter
skip_upload_on_content_match
when creating UDFs, UDTFs and stored procedures usingregister_from_file
to skip uploading files to a stage if the same version of the files are already on the stage. - Added support for
DataFrameWriter.save_as_table
method to take table names that contain dots. - Flattened generated SQL when
DataFrame.filter()
orDataFrame.order_by()
is followed by a projection statement (e.g.DataFrame.select()
,DataFrame.with_column()
). - Added support for creating dynamic tables (in private preview) using
Dataframe.create_or_replace_dynamic_table
. - Added an optional argument
params
insession.sql()
to support binding variables. Note that this is not supported in stored procedures yet.
- Fixed a bug in
strtok_to_array
where an exception was thrown when a delimiter was passed in. - Fixed a bug in
session.add_import
where the module had the same namespace as other dependencies.
- Added support for
delimiters
parameter infunctions.initcap()
. - Added support for
functions.hash()
to accept a variable number of input expressions. - Added API
Session.RuntimeConfig
for getting/setting/checking the mutability of any runtime configuration. - Added support managing case sensitivity in
Row
results fromDataFrame.collect
usingcase_sensitive
parameter. - Added API
Session.conf
for getting, setting or checking the mutability of any runtime configuration. - Added support for managing case sensitivity in
Row
results fromDataFrame.collect
usingcase_sensitive
parameter. - Added indexer support for
snowflake.snowpark.types.StructType
. - Added a keyword argument
log_on_exception
toDataframe.collect
andDataframe.collect_no_wait
to optionally disable error logging for SQL exceptions.
- Fixed a bug where a DataFrame set operation(
DataFrame.substract
,DataFrame.union
, etc.) being called after another DataFrame set operation andDataFrame.select
orDataFrame.with_column
throws an exception. - Fixed a bug where chained sort statements are overwritten by the SQL simplifier.
- Simplified JOIN queries to use constant subquery aliases (
SNOWPARK_LEFT
,SNOWPARK_RIGHT
) by default. Users can disable this at runtime withsession.conf.set('use_constant_subquery_alias', False)
to use randomly generated alias names instead. - Allowed specifying statement parameters in
session.call()
. - Enabled the uploading of large pandas DataFrames in stored procedures by defaulting to a chunk size of 100,000 rows.
- Added support for displaying source code as comments in the generated scripts when registering stored procedures. This
is enabled by default, turn off by specifying
source_code_display=False
at registration. - Added a parameter
if_not_exists
when creating a UDF, UDTF or Stored Procedure from Snowpark Python to ignore creating the specified function or procedure if it already exists. - Accept integers when calling
snowflake.snowpark.functions.get
to extract value from array. - Added
functions.reverse
in functions to open access to Snowflake built-in function reverse. - Added parameter
require_scoped_url
in snowflake.snowflake.files.SnowflakeFile.open()(in Private Preview)
to replaceis_owner_file
is marked for deprecation.
- Fixed a bug that overwrote
paramstyle
toqmark
when creating a Snowpark session. - Fixed a bug where
df.join(..., how="cross")
fails withSnowparkJoinException: (1112): Unsupported using join type 'Cross'
. - Fixed a bug where querying a
DataFrame
column created from chained function calls used a wrong column name.
- Added
asc
,asc_nulls_first
,asc_nulls_last
,desc
,desc_nulls_first
,desc_nulls_last
,date_part
andunix_timestamp
in functions. - Added the property
DataFrame.dtypes
to return a list of column name and data type pairs. - Added the following aliases:
functions.expr()
forfunctions.sql_expr()
.functions.date_format()
forfunctions.to_date()
.functions.monotonically_increasing_id()
forfunctions.seq8()
functions.from_unixtime()
forfunctions.to_timestamp()
- Fixed a bug in SQL simplifier that didn’t handle Column alias and join well in some cases. See #658 for details.
- Fixed a bug in SQL simplifier that generated wrong column names for function calls, NaN and INF.
- The session parameter
PYTHON_SNOWPARK_USE_SQL_SIMPLIFIER
isTrue
after Snowflake 7.3 was released. In snowpark-python,session.sql_simplifier_enabled
reads the value ofPYTHON_SNOWPARK_USE_SQL_SIMPLIFIER
by default, meaning that the SQL simplfier is enabled by default after the Snowflake 7.3 release. To turn this off, setPYTHON_SNOWPARK_USE_SQL_SIMPLIFIER
in Snowflake toFalse
or runsession.sql_simplifier_enabled = False
from Snowpark. It is recommended to use the SQL simplifier because it helps to generate more concise SQL.
- Added
Session.generator()
to create a newDataFrame
using the Generator table function. - Added a parameter
secure
to the functions that create a secure UDF or UDTF.
- Added new APIs for async job:
Session.create_async_job()
to create anAsyncJob
instance from a query id.AsyncJob.result()
now accepts argumentresult_type
to return the results in different formats.AsyncJob.to_df()
returns aDataFrame
built from the result of this asynchronous job.AsyncJob.query()
returns the SQL text of the executed query.
DataFrame.agg()
andRelationalGroupedDataFrame.agg()
now accept variable-length arguments.- Added parameters
lsuffix
andrsuffix
toDataFram.join()
andDataFrame.cross_join()
to conveniently rename overlapping columns. - Added
Table.drop_table()
so you can drop the temp table afterDataFrame.cache_result()
.Table
is also a context manager so you can use thewith
statement to drop the cache temp table after use. - Added
Session.use_secondary_roles()
. - Added functions
first_value()
andlast_value()
. (contributed by @chasleslr) - Added
on
as an alias forusing_columns
andhow
as an alias forjoin_type
inDataFrame.join()
.
- Fixed a bug in
Session.create_dataframe()
that raised an error whenschema
names had special characters. - Fixed a bug in which options set in
Session.read.option()
were not passed toDataFrame.copy_into_table()
as default values. - Fixed a bug in which
DataFrame.copy_into_table()
raises an error when a copy option has single quotes in the value.
Session.add_packages()
now raisesValueError
when the version of a package cannot be found in Snowflake Anaconda channel. Previously,Session.add_packages()
succeeded, and aSnowparkSQLException
exception was raised later in the UDF/SP registration step.
- Added method
FileOperation.get_stream()
to support downloading stage files as stream. - Added support in
functions.ntiles()
to accept int argument. - Added the following aliases:
functions.call_function()
forfunctions.call_builtin()
.functions.function()
forfunctions.builtin()
.DataFrame.order_by()
forDataFrame.sort()
DataFrame.orderBy()
forDataFrame.sort()
- Improved
DataFrame.cache_result()
to return a more accurateTable
class instead of aDataFrame
class. - Added support to allow
session
as the first argument when callingStoredProcedure
.
- Improved nested query generation by flattening queries when applicable.
- This improvement could be enabled by setting
Session.sql_simplifier_enabled = True
. DataFrame.select()
,DataFrame.with_column()
,DataFrame.drop()
and other select-related APIs have more flattened SQLs.DataFrame.union()
,DataFrame.union_all()
,DataFrame.except_()
,DataFrame.intersect()
,DataFrame.union_by_name()
have flattened SQLs generated when multiple set operators are chained.
- This improvement could be enabled by setting
- Improved type annotations for async job APIs.
- Fixed a bug in which
Table.update()
,Table.delete()
,Table.merge()
try to reference a temp table that does not exist.
- Added experimental APIs for evaluating Snowpark dataframes with asynchronous queries:
- Added keyword argument
block
to the following action APIs on Snowpark dataframes (which execute queries) to allow asynchronous evaluations:DataFrame.collect()
,DataFrame.to_local_iterator()
,DataFrame.to_pandas()
,DataFrame.to_pandas_batches()
,DataFrame.count()
,DataFrame.first()
.DataFrameWriter.save_as_table()
,DataFrameWriter.copy_into_location()
.Table.delete()
,Table.update()
,Table.merge()
.
- Added method
DataFrame.collect_nowait()
to allow asynchronous evaluations. - Added class
AsyncJob
to retrieve results from asynchronously executed queries and check their status.
- Added keyword argument
- Added support for
table_type
inSession.write_pandas()
. You can now choose from thesetable_type
options:"temporary"
,"temp"
, and"transient"
. - Added support for using Python structured data (
list
,tuple
anddict
) as literal values in Snowpark. - Added keyword argument
execute_as
tofunctions.sproc()
andsession.sproc.register()
to allow registering a stored procedure as a caller or owner. - Added support for specifying a pre-configured file format when reading files from a stage in Snowflake.
- Added support for displaying details of a Snowpark session.
- Fixed a bug in which
DataFrame.copy_into_table()
andDataFrameWriter.save_as_table()
mistakenly created a new table if the table name is fully qualified, and the table already exists.
- Deprecated keyword argument
create_temp_table
inSession.write_pandas()
. - Deprecated invoking UDFs using arguments wrapped in a Python list or tuple. You can use variable-length arguments without a list or tuple.
- Updated
snowflake-connector-python
to 2.7.12.
- Added support for displaying source code as comments in the generated scripts when registering UDFs.
This feature is turned on by default. To turn it off, pass the new keyword argument
source_code_display
asFalse
when callingregister()
or@udf()
. - Added support for calling table functions from
DataFrame.select()
,DataFrame.with_column()
andDataFrame.with_columns()
which now take parameters of typetable_function.TableFunctionCall
for columns. - Added keyword argument
overwrite
tosession.write_pandas()
to allow overwriting contents of a Snowflake table with that of a pandas DataFrame. - Added keyword argument
column_order
todf.write.save_as_table()
to specify the matching rules when inserting data into table in append mode. - Added method
FileOperation.put_stream()
to upload local files to a stage via file stream. - Added methods
TableFunctionCall.alias()
andTableFunctionCall.as_()
to allow aliasing the names of columns that come from the output of table function joins. - Added function
get_active_session()
in modulesnowflake.snowpark.context
to get the current active Snowpark session.
- Fixed a bug in which batch insert should not raise an error when
statement_params
is not passed to the function. - Fixed a bug in which column names should be quoted when
session.create_dataframe()
is called with dicts and a given schema. - Fixed a bug in which creation of table should be skipped if the table already exists and is in append mode when calling
df.write.save_as_table()
. - Fixed a bug in which third-party packages with underscores cannot be added when registering UDFs.
- Improved function
function.uniform()
to infer the types of inputsmax_
andmin_
and cast the limits toIntegerType
orFloatType
correspondingly.
- 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"
.
- 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.
- 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()
.
- Deprecated keyword argument
create_temp_table
indf.write.save_as_table()
.
- 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
- 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.
- 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.
- 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.
Session.flatten()
and DataFrame.flatten()
.
- Restricted the version of
cloudpickle
<=2.0.0
.
- 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
.
- 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:
- 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.
- Removed pandas hard dependencies in the
Session.create_dataframe()
method.
- Added
typing-extension
as a new dependency with the version >=4.1.0
.
- 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()
.
- 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.
- 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.
- 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.
- Updated
snowflake-connector-python
to 2.7.4.
- 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
.
- 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.
- 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.
- 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.
- 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.
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