def test_table_pandas_update(self):
# Get the only workflow in the fixture
workflow = Workflow.objects.all()[0]
# Transform new table into string
r_df = pd.DataFrame(self.new_table)
r_df = detect_datetime_columns(r_df)
# Upload a new table
response = self.client.put(reverse('table:api_pops',
kwargs={'wid': workflow.id}),
{'data_frame': df_to_string(r_df)},
format='json')
# Refresh wflow (has been updated)
workflow = Workflow.objects.get(id=workflow.id)
# Load the df from the db
df = load_table(workflow.get_data_frame_table_name())
# Compare both elements
self.compare_tables(r_df, df)
# Check that the rest of the
# information is correct
workflow = Workflow.objects.get(id=workflow.id)
self.assertTrue(check_wf_df(workflow))
def test_table_pandas_create(self):
# Create a second workflow
response = self.client.post(reverse('workflow:api_workflows'), {
'name': test.wflow_name + '2',
'attributes': {
'one': 'two'
}
},
format='json')
# Get the only workflow in the fixture
workflow = Workflow.objects.get(id=response.data['id'])
# Transform new table into a data frame
r_df = pd.DataFrame(self.new_table)
r_df = detect_datetime_columns(r_df)
# Upload the table
response = self.client.post(reverse('table:api_pops',
kwargs={'wid': workflow.id}),
{'data_frame': df_to_string(r_df)},
format='json')
# Refresh wflow (has been updated)
workflow = Workflow.objects.get(id=workflow.id)
# Load the df from the db
df = load_table(workflow.get_data_frame_table_name())
# Compare both elements
self.compare_tables(r_df, df)
# Check that the rest of the
# information is correct
self.assertTrue(check_wf_df(workflow))
def to_internal_value(self, data):
"""Create the data frame from the given data detecting date/time."""
try:
df = pd.DataFrame(data)
# Detect date/time columns
df = detect_datetime_columns(df)
except Exception as exc:
raise serializers.ValidationError(exc)
return df
def test_table_JSON_get(self):
# Get the only workflow in the fixture
workflow = Workflow.objects.all()[0]
# Get the data through the API
response = self.client.get(
reverse('table:api_ops', kwargs={'wid': workflow.id}))
# Transform the response into a data frame
r_df = pd.DataFrame(response.data['data_frame'])
r_df = detect_datetime_columns(r_df)
# Load the df from the db
df = load_table(workflow.get_data_frame_table_name())
# Compare both elements
self.compare_tables(r_df, df)
def test_table_pandas_JSON_get(self):
# Get the only workflow in the fixture
workflow = Workflow.objects.all()[0]
# Get the data through the API
response = self.client.get(
reverse('table:api_merge', kwargs={'wid': workflow.id}))
workflow = Workflow.objects.all()[0]
# Transform new table into string
r_df = pd.DataFrame(response.data['src_df'])
r_df = detect_datetime_columns(r_df)
# Load the df from the db
df = load_table(workflow.get_data_frame_table_name())
# Compare both elements and check wf df consistency
self.compare_tables(r_df, df)
self.assertTrue(check_wf_df(workflow))