API Reference#

datapact.test(dataframe: DataFrame) → DataframeTest#

Creates a datapact test object.

>>> df = pandas.read_csv(...)
>>> dp = datapact.test(df)

class datapact.DataframeTest(dataframe: DataFrame)#

describe(title: Optional[str] = None, description: Optional[str] = None, url: Optional[str] = None)#

Adds human-readable information to the report.

>>> dp.describe(
>>>     title="Vacancy statistics",
>>>     description="data sourced from NYC housing markets"
>>> )

collect() → DataframeResult#

Collects all tests and returns a DataframeResult object. If connected, uploads results.

>>> dp.day.must.be_datetime()
>>> dp.collect() # DataframeResult(...)

expectations() → list[Expectation]#

Returns a list of all executed expectations.

>>> dp.age.should.be_positive() # Pass(be_positive)
>>> dp.day.must.be_datetime() # Fail(be_datetime)
>>> dp.failed_critical_expectations() # [ Pass(be_positive), Fail(be_datetime) ]

failed_expectations() → list[Expectation]#

Returns a list of all failed expectations.

>>> dp.age.should.be_negative() # Fail(be_negative)
>>> dp.day.must.be_datetime() # Fail(be_datetime)
>>> dp.failed_critical_expectations() # [ Fail(be_negative), Fail(be_datetime) ]

failed_critical_expectations() → list[Expectation]#

Returns a list of all failed critical expectations.

>>> dp.age.should.be_negative() # Fail(be_negative)
>>> dp.day.must.be_datetime() # Fail(be_datetime)
>>> dp.failed_critical_expectations() # [ Fail(be_datetime) ]

is_failure() → bool#

Returns True if one of the expectations failed.

>>> dp.day.should.be_datetime() # Fail(be_datetime)
>>> dp.is_failure() # True

is_critical_failure() → bool#

Returns True if a critical expectation failed.

>>> dp.day.should.be_datetime() # Fail(be_datetime)
>>> dp.is_critical_failure() # False
>>> dp.day.must.be_datetime() # Fail(be_datetime)
>>> dp.is_critical_failure() # True

check()#

Raises an exception if a critical expectation failed.

>>> dp.day.must.be_datetime() # Fail(be_datetime)
>>> dp.check() # 💥

to_html()#

Returns a human-readable test result as HTML.

>>> dp.to_html() # "<script>..."

write_html(to: PathLike)#

Writes the test result to a file.

>>> dp.write_html("test.html")

class datapact.SeriesTest(parent: DataframeTest, series: Series)#

should#

should makes an assertion relaxed (results in warnings, not exceptions).

>>> dp.SepalWidth.should.be_in_range(0, 10)

must#

must makes an assertion critical (results in exceptions, not warnings).

>>> dp.SepalWidth.must.be_in_range(0, 10)

describe(title: Optional[str] = None, description: Optional[str] = None, unit: Optional[str] = None)#

Adds human-readable information to the column report.

>>> dp.SepalWidth.describe(
>>>   description="Usually green, sepals typically function as protection ...",
>>>   unit="cm"
>>> )