def get_session_results_dct(session_or_request,
fixture_store=FIXTURE_STORE, # type: Union[Mapping[str, Any], Iterable[Mapping[str, Any]]]
results_bag_fixture_name='results_bag' # type: str
):
# type: (...) -> Mapping[str, Mapping[str, Any]]
"""
Helper method to get exactly the same object than the `session_results_dct` fixture, from a session object.
This can be useful to retrieve the results from the `pytest_sessionfinish` hook for example.
See `session_results_dct` fixture for details.
:param session_or_request: the pytest session or request
:param fixture_store: an optional fixture store
:param results_bag_fixture_name: an optional name for results bag fixture in the fixture store. Default is
"results_bag"
:return:
"""
results_dct = get_session_synthesis_dct(session_or_request, durations_in_ms=True,
test_id_format='full', status_details=True, pytest_prefix=False,
fixture_store=fixture_store,
flatten=False, flatten_more=results_bag_fixture_name)
# We do not want to post-process according to steps here, this fixture should have as a contract that the keys
# are the True test ids.
# try:
# # if pytest_steps is installed, separate the test ids from the step ids
# from pytest_steps import handle_steps_in_synthesis_dct
# results_dct = handle_steps_in_synthesis_dct(results_dct, is_flat=False)
# except ImportError:
# # pytest_steps is not installed, ok.
# pass
return results_dct
def session_results_dct(request, fixture_store):
"""
This fixture contains a synthesis dictionary for all tests completed "so far", with 'full' id format. It includes
contents from the default `fixture_store`, including `results_bag`.
Behind the scenes it relies on `get_session_synthesis_dct`.
This fixture has a function scope because we want its contents to be refreshed every time it is needed.
"""
results_dct = get_session_synthesis_dct(request, durations_in_ms=True,
test_id_format='full', status_details=True, pytest_prefix=False,
fixture_store=fixture_store,
flatten=False, flatten_more='results_bag')
# We do not want to post-process according to steps here, this fixture should have as a contract that the keys
# are the True test ids.
# try:
# # if pytest_steps is installed, separate the test ids from the step ids
# from pytest_steps import handle_steps_in_synthesis_dct
# results_dct = handle_steps_in_synthesis_dct(results_dct, is_flat=False)
# except ImportError:
# # pytest_steps is not installed, ok.
# pass
return results_dct
def get_filtered_results_df(
session,
filter=None, # type: Any
test_id_format='full', # type: str
fixture_store=FIXTURE_STORE, # type: Union[Mapping[str, Any], Iterable[Mapping[str, Any]]]
results_bag_fixture_name='results_bag' # type: str
):
# type: (...) -> pd.DataFrame
"""
Combines `get_session_synthesis_dct` with a transformation into a pandas DataFrame.
:param session: the pytest session object
:param filter: any filter, see `get_session_synthesis_dct` for details
:param fixture_store: an optional fixture store
:param results_bag_fixture_name: an optional name for results bag fixture in the fixture store. Default is
"results_bag"
:return:
"""
# in case of xdist, make sure persisted workers results have been reloaded
possibly_restore_xdist_workers_structs(session)
# get the synthesis dictionary, merged with default fixture store and flattening default results_bag
module_results_dct = get_session_synthesis_dct(
session,
durations_in_ms=True,
filter=filter,
test_id_format=test_id_format,
status_details=False,
fixture_store=fixture_store,
flatten=True,
flatten_more=results_bag_fixture_name)
# convert to a pandas dataframe
results_df = pd.DataFrame.from_dict(module_results_dct, orient='index')
results_df = results_df.loc[list(
module_results_dct.keys()), :] # fix rows order
results_df.index.name = 'test_id' # set index name
# We do not want to post-process according to steps here, this fixture should have as a contract that the keys
# are the True test ids.
#
# try:
# # if pytest_steps is installed, separate the test ids from the step ids
# from pytest_steps import handle_steps_in_results_df
# results_df = handle_steps_in_results_df(results_df, keep_orig_id=True, no_steps_policy='skip')
# except ImportError:
# # pytest_steps is not installed, ok.
# pass
# except Exception as e:
# # other issue: warn about it but continue
# warn("%s: %s" % (e, type(e)))
return results_df
def module_results_df(request, fixture_store):
"""
This fixture returns a synthesis dataframe for all tests completed "so far" in the module of the caller,
with 'function' id format. It includes contents from the default `fixture_store`, including `results_bag`.
It is basically just a transformation of the `module_results_dct` fixture into a pandas DataFrame.
If `pytest-steps` is installed, the step ids will be extracted and the dataframe index will be multi-level
(test id without step, step id).
This fixture has a function scope because we want its contents to be refreshed every time it is needed.
"""
try:
import pandas as pd
# get the synthesis dictionary, merged with default fixture store and flattening default results_bag
module_results_dct = get_session_synthesis_dct(request, durations_in_ms=True,
filter=request.module.__name__,
test_id_format='function', status_details=False,
fixture_store=fixture_store,
flatten=True, flatten_more='results_bag')
# convert to a pandas dataframe
results_df = pd.DataFrame.from_dict(module_results_dct, orient='index')
results_df = results_df.loc[list(module_results_dct.keys()), :] # fix rows order
results_df.index.name = 'test_id' # set index name
# We do not want to post-process according to steps here, this fixture should have as a contract that the keys
# are the True test ids.
#
# try:
# # if pytest_steps is installed, separate the test ids from the step ids
# from pytest_steps import handle_steps_in_results_df
# results_df = handle_steps_in_results_df(results_df, keep_orig_id=True, no_steps_policy='skip')
# except ImportError:
# # pytest_steps is not installed, ok.
# pass
# except Exception as e:
# # other issue: warn about it but continue
# warn("%s: %s" % (e, type(e)))
return results_df
except ImportError as e:
six.raise_from(Exception("There was an error importing `pandas` module. Fixture `session_results_df` can not "
"be used in this session because "), e)
def get_session_results_df(session_or_request,
fixture_store=FIXTURE_STORE, # type: Union[Mapping[str, Any], Iterable[Mapping[str, Any]]]
results_bag_fixture_name='results_bag' # type: str
):
# type: (...) -> pd.DataFrame
"""
Helper method to get exactly the same object than the `session_results_df` fixture, from a session object.
This can be useful to retrieve the results from the `pytest_sessionfinish` hook for example.
See `session_results_df` fixture for details.
:param session_or_request: the pytest session or request
:param fixture_store: an optional fixture store
:param results_bag_fixture_name: an optional name for results bag fixture in the fixture store. Default is
"results_bag"
:return:
"""
# get the synthesis dictionary, merged with default fixture store and flattening default results_bag
session_results_dct = get_session_synthesis_dct(session_or_request, durations_in_ms=True,
test_id_format='full', status_details=False,
fixture_store=fixture_store,
flatten=True, flatten_more=results_bag_fixture_name)
# convert to a pandas dataframe
results_df = pd.DataFrame.from_dict(session_results_dct, orient='index')
results_df = results_df.loc[list(session_results_dct.keys()), :] # fix rows order
results_df.index.name = 'test_id' # set index name
# We do not want to post-process according to steps here, this fixture should have as a contract that the keys
# are the True test ids.
#
# try:
# # if pytest_steps is installed, separate the test ids from the step ids
# from pytest_steps import handle_steps_in_results_df
# results_df = handle_steps_in_results_df(results_df, keep_orig_id=True, no_steps_policy='skip')
# except ImportError:
# # pytest_steps is not installed, ok.
# pass
# except Exception as e:
# # other issue: warn about it but continue
# warn("%s: %s" % (e, type(e)))
return results_df
