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Add tqdm v4.21.0
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JonnyWong16
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fabced9942
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207
lib/tqdm/tests/tests_pandas.py
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207
lib/tqdm/tests/tests_pandas.py
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from nose.plugins.skip import SkipTest
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from tqdm import tqdm
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from tests_tqdm import with_setup, pretest, posttest, StringIO, closing
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@with_setup(pretest, posttest)
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def test_pandas_series():
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"""Test pandas.Series.progress_apply and .progress_map"""
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try:
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from numpy.random import randint
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import pandas as pd
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except ImportError:
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raise SkipTest
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with closing(StringIO()) as our_file:
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tqdm.pandas(file=our_file, leave=True, ascii=True)
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series = pd.Series(randint(0, 50, (123,)))
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res1 = series.progress_apply(lambda x: x + 10)
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res2 = series.apply(lambda x: x + 10)
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assert res1.equals(res2)
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res3 = series.progress_map(lambda x: x + 10)
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res4 = series.map(lambda x: x + 10)
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assert res3.equals(res4)
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expects = ['100%', '123/123']
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for exres in expects:
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our_file.seek(0)
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if our_file.getvalue().count(exres) < 2:
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our_file.seek(0)
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raise AssertionError(
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"\nExpected:\n{0}\nIn:\n{1}\n".format(
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exres + " at least twice.", our_file.read()))
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@with_setup(pretest, posttest)
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def test_pandas_data_frame():
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"""Test pandas.DataFrame.progress_apply and .progress_applymap"""
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try:
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from numpy.random import randint
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import pandas as pd
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except ImportError:
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raise SkipTest
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with closing(StringIO()) as our_file:
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tqdm.pandas(file=our_file, leave=True, ascii=True)
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df = pd.DataFrame(randint(0, 50, (100, 200)))
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def task_func(x):
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return x + 1
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# applymap
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res1 = df.progress_applymap(task_func)
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res2 = df.applymap(task_func)
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assert res1.equals(res2)
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# apply
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for axis in [0, 1]:
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res3 = df.progress_apply(task_func, axis=axis)
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res4 = df.apply(task_func, axis=axis)
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assert res3.equals(res4)
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our_file.seek(0)
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if our_file.read().count('100%') < 3:
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our_file.seek(0)
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raise AssertionError("\nExpected:\n{0}\nIn:\n{1}\n".format(
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'100% at least three times', our_file.read()))
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# apply_map, apply axis=0, apply axis=1
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expects = ['20000/20000', '200/200', '100/100']
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for exres in expects:
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our_file.seek(0)
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if our_file.getvalue().count(exres) < 1:
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our_file.seek(0)
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raise AssertionError(
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"\nExpected:\n{0}\nIn:\n {1}\n".format(
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exres + " at least once.", our_file.read()))
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@with_setup(pretest, posttest)
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def test_pandas_groupby_apply():
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"""Test pandas.DataFrame.groupby(...).progress_apply"""
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try:
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from numpy.random import randint
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import pandas as pd
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except ImportError:
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raise SkipTest
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with closing(StringIO()) as our_file:
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tqdm.pandas(file=our_file, leave=False, ascii=True)
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df = pd.DataFrame(randint(0, 50, (500, 3)))
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df.groupby(0).progress_apply(lambda x: None)
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dfs = pd.DataFrame(randint(0, 50, (500, 3)), columns=list('abc'))
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dfs.groupby(['a']).progress_apply(lambda x: None)
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our_file.seek(0)
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# don't expect final output since no `leave` and
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# high dynamic `miniters`
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nexres = '100%|##########|'
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if nexres in our_file.read():
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our_file.seek(0)
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raise AssertionError("\nDid not expect:\n{0}\nIn:{1}\n".format(
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nexres, our_file.read()))
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with closing(StringIO()) as our_file:
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tqdm.pandas(file=our_file, leave=True, ascii=True)
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dfs = pd.DataFrame(randint(0, 50, (500, 3)), columns=list('abc'))
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dfs.loc[0] = [2, 1, 1]
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dfs['d'] = 100
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expects = ['500/500', '1/1', '4/4', '2/2']
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dfs.groupby(dfs.index).progress_apply(lambda x: None)
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dfs.groupby('d').progress_apply(lambda x: None)
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dfs.groupby(dfs.columns, axis=1).progress_apply(lambda x: None)
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dfs.groupby([2, 2, 1, 1], axis=1).progress_apply(lambda x: None)
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our_file.seek(0)
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if our_file.read().count('100%') < 4:
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our_file.seek(0)
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raise AssertionError("\nExpected:\n{0}\nIn:\n{1}\n".format(
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'100% at least four times', our_file.read()))
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for exres in expects:
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our_file.seek(0)
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if our_file.getvalue().count(exres) < 1:
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our_file.seek(0)
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raise AssertionError(
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"\nExpected:\n{0}\nIn:\n {1}\n".format(
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exres + " at least once.", our_file.read()))
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@with_setup(pretest, posttest)
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def test_pandas_leave():
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"""Test pandas with `leave=True`"""
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try:
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from numpy.random import randint
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import pandas as pd
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except ImportError:
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raise SkipTest
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with closing(StringIO()) as our_file:
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df = pd.DataFrame(randint(0, 100, (1000, 6)))
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tqdm.pandas(file=our_file, leave=True, ascii=True)
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df.groupby(0).progress_apply(lambda x: None)
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our_file.seek(0)
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exres = '100%|##########| 100/100'
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if exres not in our_file.read():
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our_file.seek(0)
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raise AssertionError(
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"\nExpected:\n{0}\nIn:{1}\n".format(exres, our_file.read()))
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@with_setup(pretest, posttest)
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def test_pandas_apply_args_deprecation():
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"""Test warning info in
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`pandas.Dataframe(Series).progress_apply(func, *args)`"""
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try:
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from numpy.random import randint
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from tqdm import tqdm_pandas
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import pandas as pd
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except ImportError:
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raise SkipTest
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with closing(StringIO()) as our_file:
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tqdm_pandas(tqdm(file=our_file, leave=False, ascii=True, ncols=20))
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df = pd.DataFrame(randint(0, 50, (500, 3)))
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df.progress_apply(lambda x: None, 1) # 1 shall cause a warning
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# Check deprecation message
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res = our_file.getvalue()
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assert all([i in res for i in (
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"TqdmDeprecationWarning", "not supported",
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"keyword arguments instead")])
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@with_setup(pretest, posttest)
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def test_pandas_deprecation():
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"""Test bar object instance as argument deprecation"""
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try:
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from numpy.random import randint
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from tqdm import tqdm_pandas
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import pandas as pd
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except ImportError:
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raise SkipTest
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with closing(StringIO()) as our_file:
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tqdm_pandas(tqdm(file=our_file, leave=False, ascii=True, ncols=20))
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df = pd.DataFrame(randint(0, 50, (500, 3)))
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df.groupby(0).progress_apply(lambda x: None)
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# Check deprecation message
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assert "TqdmDeprecationWarning" in our_file.getvalue()
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assert "instead of `tqdm_pandas(tqdm(...))`" in our_file.getvalue()
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with closing(StringIO()) as our_file:
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tqdm_pandas(tqdm, file=our_file, leave=False, ascii=True, ncols=20)
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df = pd.DataFrame(randint(0, 50, (500, 3)))
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df.groupby(0).progress_apply(lambda x: None)
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# Check deprecation message
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assert "TqdmDeprecationWarning" in our_file.getvalue()
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assert "instead of `tqdm_pandas(tqdm, ...)`" in our_file.getvalue()
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