def csvdownload_view(
request: HttpRequest,
pk: int,
workflow: Optional[Workflow] = None,
view: Optional[View] = None,
) -> HttpResponse:
"""Download the data in a given view.
:param request: HTML request
:param pk: View ID
:param workflow: Set by the decorator to the current workflow.
:param view: Set by the decorator to the view with the given PK
:return: Return a CSV download of the data in the table
"""
# Fetch the data frame
return _respond_csv(
get_subframe(
workflow.get_data_frame_table_name(),
view.formula,
[col.name for col in view.columns.all()],
), )
def test_eval_conditions(self):
# Get the action first
self.action = Action.objects.get(name=self.action_name)
# Get wflow table, filter and column names
wflow_table = self.action.workflow.get_data_frame_table_name()
filter_formula = self.action.get_filter_formula()
column_names = self.action.workflow.get_column_names()
conditions = self.action.conditions.filter(is_filter=False)
# Get dataframe
df = get_subframe(wflow_table, filter_formula, column_names)
# Get the query set
qs = get_rows(wflow_table,
column_names=column_names,
filter_formula=filter_formula)
# Iterate over the rows in the dataframe and compare
for idx, row in enumerate(qs):
row_value_df = dict(list(zip(column_names, df.loc[idx, :])))
row_value_qs = dict(list(zip(column_names, row)))
cond_eval1 = [
evaluate_formula(x.formula, EVAL_EXP, row_value_df)
for x in conditions
]
cond_eval2 = [
evaluate_formula(x.formula, EVAL_EXP, row_value_qs)
for x in conditions
]
assert cond_eval1 == cond_eval2
def _create_single_message(
msg_body_sbj_to: List[str],
track_str: str,
from_email: str,
cc_email_list: List[str],
bcc_email_list: List[str],
attachments: Optional[List[models.View]] = None,
filter_formula: Optional[Dict] = None,
) -> Union[EmailMessage, EmailMultiAlternatives]:
"""Create either an EmailMessage or EmailMultiAlternatives object.
:param msg_body_sbj_to: List with body, subject, to
:param track_str: String to add to track
:param from_email: From email
:param cc_email_list: CC list
:param bcc_email_list: BCC list
:param attachments: List of views to attach to the message (optional)
:param filter_formula: Filter attached ot the action (optional)
:return: Either EmailMessage or EmailMultiAlternatives
"""
if settings.EMAIL_HTML_ONLY:
# Message only has the HTML text
msg = EmailMessage(
msg_body_sbj_to[1],
msg_body_sbj_to[0] + track_str,
from_email,
[msg_body_sbj_to[2]],
bcc=bcc_email_list,
cc=cc_email_list,
)
msg.content_subtype = 'html'
else:
# Get the plain text content and bundle it together with the HTML
# in a message to be added to the list.
msg = EmailMultiAlternatives(
subject=html2text.html2text(msg_body_sbj_to[0]),
body=msg_body_sbj_to[1],
from_email=from_email,
to=[msg_body_sbj_to[2]],
bcc=bcc_email_list,
cc=cc_email_list,
)
msg.attach_alternative(msg_body_sbj_to[0] + track_str, 'text/html')
if attachments:
for attachment in attachments:
data_frame = pandas.get_subframe(
attachment.workflow.get_data_frame_table_name(),
filter_formula, [col.name for col in attachment.columns.all()])
mime_obj = MIMEText(data_frame.to_csv(), 'csv')
mime_obj.add_header('Content-Disposition',
'attachment',
filename=attachment.name + '.csv')
msg.attach(mime_obj)
return msg
def vis_html_content(context, column_name):
"""Create the HTML visualization code."""
# Get the action
action = context.get(evaluate.ACTION_CONTEXT_VAR)
if not action:
raise Exception(_('Action object not found when processing tag'))
workflow = action.workflow
# Check if the column is correct
if not workflow.columns.filter(name=column_name).exists():
raise Exception(_('Column {0} does not exist').format(column_name))
# Get the visualization number to generate unique IDs
viz_number = context[evaluate.VIZ_NUMBER_CONTEXT_VAR]
# Create the context for the visualization
viz_ctx = {
'style': 'width:400px; height:225px;',
'id': 'viz_tag_{0}'.format(viz_number)
}
# If there is a column name in the context, insert it as individual value
# If the template is simply being saved and rendered to detect syntax
# errors, we may not have the data of an individual, so we have to relax
# this restriction.
ivalue = context.get(evaluate.TR_ITEM(column_name))
if ivalue is not None:
viz_ctx['individual_value'] = ivalue
# Get the data from the data frame
df = pandas.get_subframe(
workflow.get_data_frame_table_name(),
action.get_filter_formula(),
[column_name])
# Get the visualisation
viz = plotly.PlotlyColumnHistogram(data=df, context=viz_ctx)
prefix = ''
if viz_number == 0:
prefix = ''.join([
'<script src="{0}"></script>'.format(x)
for x in plotly.PlotlyColumnHistogram.get_engine_scripts()
])
# Update viz number
context[evaluate.VIZ_NUMBER_CONTEXT_VAR] = viz_number + 1
# Return the rendering of the viz marked as safe
return mark_safe(prefix + viz.render())
def csvdownload(
request: HttpRequest,
workflow: Optional[models.Workflow] = None,
) -> HttpResponse:
"""Download the data in the workflow.
:param request: HTML request
:param workflow: Set by the decorator to the current workflow.
:return: Return a CSV download of the data in the table
"""
del request
return services.create_response_with_csv(
pandas.get_subframe(workflow.get_data_frame_table_name(), None,
workflow.get_column_names()))
def csvdownload_view(
request: HttpRequest,
pk: int,
workflow: Optional[models.Workflow] = None,
view: Optional[models.View] = None,
) -> HttpResponse:
"""Download the data in a given view.
:param request: HTML request
:param pk: View ID
:param workflow: Set by the decorator to the current workflow.
:param view: Set by the decorator to the view with the given PK
:return: Return a CSV download of the data in the table
"""
del request, pk
return services.create_response_with_csv(
pandas.get_subframe(workflow.get_data_frame_table_name(), view.formula,
[col.name for col in view.columns.all()]))
def csvdownload(
request: HttpRequest,
workflow: Optional[Workflow] = None,
) -> HttpResponse:
"""Download the data in the workflow.
:param request: HTML request
:param workflow: Set by the decorator to the current workflow.
:return: Return a CSV download of the data in the table
"""
# Fetch the data frame
return _respond_csv(
get_subframe(
workflow.get_data_frame_table_name(),
None,
workflow.get_column_names(),
), )