How to use test_func_io method in pandera

Best Python code snippet using pandera_python

test_decorators.py

Source:test_decorators.py Github

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...172 in_schema = DataFrameSchema({"column1": Column(int, coerce=True)})173 out_schema = DataFrameSchema({"column2": Column(float, coerce=True)})174 @check_input(in_schema)175 @check_output(out_schema)176 def test_func_io(df):177 return df.assign(column2=10)178 @check_input(in_schema)179 @check_output(out_schema, obj_getter=1)180 def test_func_out_tuple_obj_getter(df):181 return None, df.assign(column2=10)182 @check_input(in_schema)183 @check_output(out_schema, obj_getter=1)184 def test_func_out_list_obj_getter(df):185 return None, df.assign(column2=10)186 @check_input(in_schema)187 @check_output(out_schema, obj_getter="key")188 def test_func_out_dict_obj_getter(df):189 return {"key": df.assign(column2=10)}190 cases: typing.Iterable[...

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manualtest.py

Source:manualtest.py Github

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...18 return None19 except Exception as e:20 raise AssertionError(f"Value raised was '{e}' (not private error)")21 raise AssertionError("No value was raised")22def test_func_io(func: Callable[[T], O], arg: T, expect: O) -> None:23 assert func(arg) == expect, f"func({arg=})={func(arg)} != {expect=}"24def try_or_return(func: Callable[[], Optional[Iterable[Exception]]]) -> Callable[[], Optional[Iterable[Exception]]]:25 def wrapped() -> Optional[Iterable[Exception]]:26 try:27 return func()28 except Exception as e:29 return [e]30 return wrapped31@try_or_return32def test_parse_duration() -> Optional[Iterable[Exception]]:33 from lib_goparsers import ParseDurationSuper34 WEEK: Final = 7 * 24 * 60 * 6035 DAY: Final = 24 * 60 * 6036 HOUR: Final = 60 * 6037 MINUTE: Final = 6038 SECOND: Final = 139 tests = (40 [41 # "Real user" tests, general correctness42 ("123", 123),43 ("5minutes", 5 * MINUTE),44 ("45s", 45),45 ("s", 1),46 # Various rejection paths47 ("5monite", None),48 ("sfgdsgf", None),49 ("minutes5", None),50 ("5seconds4", None),51 ("seconds5m", None),52 ("", None),53 ("josh", None),54 ("seconds5seconds", None),55 ("1w1wday", None),56 ("1day2weeks7dam", None),57 # Test all unit names have correct outputs58 ("1w1week1weeks", 3 * WEEK),59 ("1d1day1days", 3 * DAY),60 ("1h1hour1hours", 3 * HOUR),61 ("1m1minute1minutes", 3 * MINUTE),62 ("1s1second1seconds", 3 * SECOND),63 # Test all single unit cases64 ("week", WEEK),65 ("w", WEEK),66 ("day", DAY),67 ("d", DAY),68 ("hour", HOUR),69 ("h", HOUR),70 ("minute", MINUTE),71 ("m", MINUTE),72 ("second", SECOND),73 ("s", SECOND),74 # Test for floating point accuracy75 (f"{(1<<54)+1}m1s", ((1 << 54) + 1) * 60 + 1),76 ("4.5h", 4 * HOUR + 30 * MINUTE),77 ("4.7h", 4 * HOUR + (7 * HOUR // 10)),78 ("3.5d7.3m", 3 * DAY + 12 * HOUR + 7 * MINUTE + (3 * MINUTE // 10)),79 # Test for fp parse rejection80 ("5.6.34seconds", None),81 # Test fractions82 ("3/6days", 12 * HOUR),83 ("1/0", None),84 ("0/0", None),85 ("17/60m", 17 * SECOND),86 ("13/24d1/0w", None),87 (f"{(1<<54)+2}/2d", (((1 << 54) + 2) * DAY) // 2),88 ]89 )90 out = []91 for i in tests:92 try:93 test_func_io(ParseDurationSuper, i[0], i[1])94 except AssertionError as e:95 out.append(e)96 if out: return out97 else:98 return None99@try_or_return100def test_ramfs() -> Optional[Iterable[Exception]]:101 from contextlib import redirect_stdout, redirect_stderr102 sink = io.StringIO()103 # Reroute stderr and stdout to ignore import warnings from main104 with redirect_stdout(sink):105 with redirect_stderr(sink):106 from main import ram_filesystem # pylint: disable=E0401107 testfs = ram_filesystem()...

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main.py

Source:main.py Github

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...16 17### Each of these routines is a test to verify some aspect of the code18#test_func_scaler()19#test_func_pca()20#test_func_io()21#test_func_holistic(10)22#test_func_regressor(31)23### This is an example of a full run of the program:24# - First, we generate a number of datasets with a random distribution25# of starting points but which use the same reaction rate26number_of_datasets = 10027input_data = test_func_create_dataset_simple_2(number_of_datasets)28# - Next, we select the number of principle components we wish to retain29# (currently, must be equal to number of species, i.e. no reduction)30n_comp = 331# - Finally, we run the regression example...

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