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from tqdm import tqdm
from .tests_tqdm import StringIO, closing, importorskip, mark, skip
pytestmark = mark.slow
random = importorskip('numpy.random')
rand = random.rand
randint = random.randint
pd = importorskip('pandas')
def test_pandas_setup():
"""Test tqdm.pandas()"""
with closing(StringIO()) as our_file:
tqdm.pandas(file=our_file, leave=True, ascii=True, total=123)
series = pd.Series(randint(0, 50, (100,)))
series.progress_apply(lambda x: x + 10)
res = our_file.getvalue()
assert '100/123' in res
def test_pandas_rolling_expanding():
"""Test pandas.(Series|DataFrame).(rolling|expanding)"""
with closing(StringIO()) as our_file:
tqdm.pandas(file=our_file, leave=True, ascii=True)
series = pd.Series(randint(0, 50, (123,)))
res1 = series.rolling(10).progress_apply(lambda x: 1, raw=True)
res2 = series.rolling(10).apply(lambda x: 1, raw=True)
assert res1.equals(res2)
res3 = series.expanding(10).progress_apply(lambda x: 2, raw=True)
res4 = series.expanding(10).apply(lambda x: 2, raw=True)
assert res3.equals(res4)
expects = ['114it'] # 123-10+1
for exres in expects:
our_file.seek(0)
if our_file.getvalue().count(exres) < 2:
our_file.seek(0)
raise AssertionError("\nExpected:\n{0}\nIn:\n{1}\n".format(
exres + " at least twice.", our_file.read()))
def test_pandas_series():
"""Test pandas.Series.progress_apply and .progress_map"""
with closing(StringIO()) as our_file:
tqdm.pandas(file=our_file, leave=True, ascii=True)
series = pd.Series(randint(0, 50, (123,)))
res1 = series.progress_apply(lambda x: x + 10)
res2 = series.apply(lambda x: x + 10)
assert res1.equals(res2)
res3 = series.progress_map(lambda x: x + 10)
res4 = series.map(lambda x: x + 10)
assert res3.equals(res4)
expects = ['100%', '123/123']
for exres in expects:
our_file.seek(0)
if our_file.getvalue().count(exres) < 2:
our_file.seek(0)
raise AssertionError("\nExpected:\n{0}\nIn:\n{1}\n".format(
exres + " at least twice.", our_file.read()))
def test_pandas_data_frame():
"""Test pandas.DataFrame.progress_apply and .progress_applymap"""
with closing(StringIO()) as our_file:
tqdm.pandas(file=our_file, leave=True, ascii=True)
df = pd.DataFrame(randint(0, 50, (100, 200)))
def task_func(x):
return x + 1
# applymap
res1 = df.progress_applymap(task_func)
res2 = df.applymap(task_func)
assert res1.equals(res2)
# apply unhashable
res1 = []
df.progress_apply(res1.extend)
assert len(res1) == df.size
# apply
for axis in [0, 1, 'index', 'columns']:
res3 = df.progress_apply(task_func, axis=axis)
res4 = df.apply(task_func, axis=axis)
assert res3.equals(res4)
our_file.seek(0)
if our_file.read().count('100%') < 3:
our_file.seek(0)
raise AssertionError("\nExpected:\n{0}\nIn:\n{1}\n".format(
'100% at least three times', our_file.read()))
# apply_map, apply axis=0, apply axis=1
expects = ['20000/20000', '200/200', '100/100']
for exres in expects:
our_file.seek(0)
if our_file.getvalue().count(exres) < 1:
our_file.seek(0)
raise AssertionError("\nExpected:\n{0}\nIn:\n {1}\n".format(
exres + " at least once.", our_file.read()))
def test_pandas_groupby_apply():
"""Test pandas.DataFrame.groupby(...).progress_apply"""
with closing(StringIO()) as our_file:
tqdm.pandas(file=our_file, leave=False, ascii=True)
df = pd.DataFrame(randint(0, 50, (500, 3)))
df.groupby(0).progress_apply(lambda x: None)
dfs = pd.DataFrame(randint(0, 50, (500, 3)), columns=list('abc'))
dfs.groupby(['a']).progress_apply(lambda x: None)
df2 = df = pd.DataFrame({'a': randint(1, 8, 10000), 'b': rand(10000)})
res1 = df2.groupby("a").apply(max)
res2 = df2.groupby("a").progress_apply(max)
assert res1.equals(res2)
our_file.seek(0)
# don't expect final output since no `leave` and
# high dynamic `miniters`
nexres = '100%|##########|'
if nexres in our_file.read():
our_file.seek(0)
raise AssertionError("\nDid not expect:\n{0}\nIn:{1}\n".format(
nexres, our_file.read()))
with closing(StringIO()) as our_file:
tqdm.pandas(file=our_file, leave=True, ascii=True)
dfs = pd.DataFrame(randint(0, 50, (500, 3)), columns=list('abc'))
dfs.loc[0] = [2, 1, 1]
dfs['d'] = 100
expects = ['500/500', '1/1', '4/4', '2/2']
dfs.groupby(dfs.index).progress_apply(lambda x: None)
dfs.groupby('d').progress_apply(lambda x: None)
dfs.groupby(dfs.columns, axis=1).progress_apply(lambda x: None)
dfs.groupby([2, 2, 1, 1], axis=1).progress_apply(lambda x: None)
our_file.seek(0)
if our_file.read().count('100%') < 4:
our_file.seek(0)
raise AssertionError("\nExpected:\n{0}\nIn:\n{1}\n".format(
'100% at least four times', our_file.read()))
for exres in expects:
our_file.seek(0)
if our_file.getvalue().count(exres) < 1:
our_file.seek(0)
raise AssertionError("\nExpected:\n{0}\nIn:\n {1}\n".format(
exres + " at least once.", our_file.read()))
def test_pandas_leave():
"""Test pandas with `leave=True`"""
with closing(StringIO()) as our_file:
df = pd.DataFrame(randint(0, 100, (1000, 6)))
tqdm.pandas(file=our_file, leave=True, ascii=True)
df.groupby(0).progress_apply(lambda x: None)
our_file.seek(0)
exres = '100%|##########| 100/100'
if exres not in our_file.read():
our_file.seek(0)
raise AssertionError("\nExpected:\n{0}\nIn:{1}\n".format(
exres, our_file.read()))
def test_pandas_apply_args_deprecation():
"""Test warning info in
`pandas.Dataframe(Series).progress_apply(func, *args)`"""
try:
from tqdm import tqdm_pandas
except ImportError as err:
skip(str(err))
with closing(StringIO()) as our_file:
tqdm_pandas(tqdm(file=our_file, leave=False, ascii=True, ncols=20))
df = pd.DataFrame(randint(0, 50, (500, 3)))
df.progress_apply(lambda x: None, 1) # 1 shall cause a warning
# Check deprecation message
res = our_file.getvalue()
assert all(i in res for i in (
"TqdmDeprecationWarning", "not supported",
"keyword arguments instead"))
def test_pandas_deprecation():
"""Test bar object instance as argument deprecation"""
try:
from tqdm import tqdm_pandas
except ImportError as err:
skip(str(err))
with closing(StringIO()) as our_file:
tqdm_pandas(tqdm(file=our_file, leave=False, ascii=True, ncols=20))
df = pd.DataFrame(randint(0, 50, (500, 3)))
df.groupby(0).progress_apply(lambda x: None)
# Check deprecation message
assert "TqdmDeprecationWarning" in our_file.getvalue()
assert "instead of `tqdm_pandas(tqdm(...))`" in our_file.getvalue()
with closing(StringIO()) as our_file:
tqdm_pandas(tqdm, file=our_file, leave=False, ascii=True, ncols=20)
df = pd.DataFrame(randint(0, 50, (500, 3)))
df.groupby(0).progress_apply(lambda x: None)
# Check deprecation message
assert "TqdmDeprecationWarning" in our_file.getvalue()
assert "instead of `tqdm_pandas(tqdm, ...)`" in our_file.getvalue()
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