ɯeiU( ddlZddlZddlZddlmZddlmZddlmZddl m Z ddl m Z m Z mZdZdee d ee fd Zd e d e fd Zed dd ed ededed df dZeZy)N)List) experimental) DataFrame)Row) StructType_FractionalType _IntegralTypez--- actual --- +++ expected +++rowsreturncLd}tj|}t||S)Ncdt||D]!\}}||k(r |y|y||kDry||ks!yy)Nr)zip)row1row2value1value2s \/var/www/html/glpi_dashboard/venv/lib/python3.12/site-packages/snowflake/snowpark/testing.py compare_rowsz&_get_sorted_rows..compare_rowssO!$o NFF~&& )key) functools cmp_to_keysorted)r rsort_keys r_get_sorted_rowsrs& ##L1H $H %%ractualexpectedct|jt|jk(s4Jdt|jdt|jdtt|j|jD]\}\}}d}|j|jk7rd|d|jd|j}|j |j k7rst |j trt |tsIt |j trt |tsd|d|j d|j }|j|jk7rd |d|jd|j}|s t|}t|}||k7s)tj|j|j}d j|} t|d t d | y) zM Asserts whether two :class:`types.StructType` objects are the same. z(Different number of columns: actual has z columns, expected has z columnsNzColumn name mismatch at column : actual , expected z$Column data type mismatch at column z#Column nullable mismatch at column  z Different schema: )lenfields enumeraternamedatatype isinstancer rnullablestrdifflibndiff splitlinesjoinAssertionErrorACTUAL_EXPECTED_STRING) rr column_index actual_fieldexpected_field error_message actual_str expected_strdiffdiff_strs r_assert_schema_equalr:%s9 v}} " | 1#fmm2D1EE\]`aiapap]q\rrz{| 9B FMM8??+94 4|^    3 3 3=l^9UaUfUfTggrtBtGtGsHIM  N$;$; ;|44mD">=A|44oF">?C#G|nT]^j^s^s]ttAOAXAX@Y!Z  N$;$; ;A,yYeYnYnXooz|J|S|S{TUM VJx=L\)}}Z%:%:%U>U>WX99T?$$o%:;Q:RRTU]T^_5rz1.21.0)versionrtolatolc t|ts tdt|ts td|j}|j}t ||t |j }t |j }t|t|k(s Jdt|dt|dtt||D]\}\} } tt| | D]\} \} } d|d| d| d | }d }t| trItj| tj| k7rd }tj| | || sd }nt| | k7}|st| }t| }||k7st!j"|j%|j%}d j'|}t)|dt*d |y)am Asserts that two Snowpark :class:`DataFrame` objects are equal. This function compares both the schema and the data of the DataFrames. If there are differences, an ``AssertionError`` is raised with a detailed message including differences. This function is useful for unit testing and validating data transformations and processing in Snowpark. Args: actual: The actual DataFrame to be compared. expected: The expected DataFrame to compare against. rtol: The relative tolerance for comparing float values. Default is 1e-5. atol: The absolute tolerance for comparing float values. Default is 1e-8. Examples:: >>> from snowflake.snowpark.testing import assert_dataframe_equal >>> from snowflake.snowpark.types import StructType, StructField, IntegerType, StringType, DoubleType >>> schema1 = StructType([ ... StructField("id", IntegerType()), ... StructField("name", StringType()), ... StructField("value", DoubleType()) ... ]) >>> data1 = [[1, "Rice", 1.0], [2, "Saka", 2.0], [3, "White", 3.0]] >>> df1 = session.create_dataframe(data1, schema1) >>> df2 = session.create_dataframe(data1, schema1) >>> assert_dataframe_equal(df2, df1) # pass, DataFrames are identical >>> data2 = [[2, "Saka", 2.0], [1, "Rice", 1.0], [3, "White", 3.0]] # change the order >>> df3 = session.create_dataframe(data2, schema1) >>> assert_dataframe_equal(df3, df1) # pass, DataFrames are identical >>> data3 = [[1, "Rice", 1.0], [2, "Saka", 2.0], [4, "Rowe", 4.0]] >>> df4 = session.create_dataframe(data3, schema1) >>> assert_dataframe_equal(df4, df1) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): AssertionError: Value mismatch on row 2 at column 0: actual 4, expected 3 Different row: --- actual --- +++ expected +++ - Row(ID=4, NAME='Rowe', VALUE=4.0) ? ^ ^^^ ^ + Row(ID=3, NAME='White', VALUE=3.0) ? ^ ^^^^ ^ >>> data4 = [[1, "Rice", 1.0], [2, "Saka", 2.0], [3, "White", 3.0001]] >>> df5 = session.create_dataframe(data4, schema1) >>> assert_dataframe_equal(df5, df1, atol=1e-3) # pass, DataFrames are identical due to higher error tolerance >>> assert_dataframe_equal(df5, df1, atol=1e-5) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): AssertionError: Value mismatch on row 2 at column 2: actual 3.0001, expected 3.0 Different row: --- actual --- +++ expected +++ - Row(ID=3, NAME='White', VALUE=3.0001) ? --- + Row(ID=3, NAME='White', VALUE=3.0) >>> schema2 = StructType([ ... StructField("id", IntegerType()), ... StructField("key", StringType()), ... StructField("value", DoubleType()) ... ]) >>> df6 = session.create_dataframe(data1, schema2) >>> assert_dataframe_equal(df6, df1) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): AssertionError: Column name mismatch at column 1: actual KEY, expected NAME Different schema: --- actual --- +++ expected +++ - StructType([StructField('ID', LongType(), nullable=True), StructField('KEY', StringType(), nullable=True), StructField('VALUE', DoubleType(), nullable=True)]) ? ^ - + StructType([StructField('ID', LongType(), nullable=True), StructField('NAME', StringType(), nullable=True), StructField('VALUE', DoubleType(), nullable=True)]) ? >>> schema3 = StructType([ ... StructField("id", IntegerType()), ... StructField("name", StringType()), ... StructField("value", IntegerType()) ... ]) >>> df7 = session.create_dataframe(data1, schema3) >>> assert_dataframe_equal(df7, df1) # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): AssertionError: Column data type mismatch at column 2: actual LongType(), expected DoubleType() Different schema: --- actual --- +++ expected +++ - StructType([StructField('ID', LongType(), nullable=True), StructField('NAME', StringType(), nullable=True), StructField('VALUE', LongType(), nullable=True)]) ? ^ ^^ + StructType([StructField('ID', LongType(), nullable=True), StructField('NAME', StringType(), nullable=True), StructField('VALUE', DoubleType(), nullable=True)]) ? Note: 1. Data in a Snowpark DataFrame is unordered, so when comparing two DataFrames, this function sorts rows based on their values first. 2. 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