def get_export_data(cls):
count_attrs = ['state', 'has_been_read', 'vote']
edits_attrs = ['state', 'vote', 'note']
data = {
'public': {
'votes': {
'counts': export_attr_counts(cls, count_attrs),
'edits': export_attr_edits(cls, edits_attrs),
},
},
'tables': ['cfp_vote', 'cfp_vote_version'],
}
data['public']['votes']['counts']['created_day'] = export_intervals(cls.query, cls.created, 'day', 'YYYY-MM-DD')
return data
def get_export_data(cls):
count_attrs = ['state', 'has_been_read', 'vote']
edits_attrs = ['state', 'vote', 'note']
data = {
'public': {
'votes': {
'counts': export_attr_counts(cls, count_attrs),
'edits': export_attr_edits(cls, edits_attrs),
},
},
'tables': ['cfp_vote', 'cfp_vote_version'],
}
data['public']['votes']['counts']['created_day'] = export_intervals(
cls.query, cls.created, 'day', 'YYYY-MM-DD')
return data
def get_export_data(cls):
count_attrs = ["state", "has_been_read", "vote"]
edits_attrs = ["state", "vote", "note"]
data = {
"public": {
"votes": {
"counts": export_attr_counts(cls, count_attrs),
"edits": export_attr_edits(cls, edits_attrs),
}
},
"tables": ["cfp_vote", "cfp_vote_version"],
}
data["public"]["votes"]["counts"]["created_day"] = export_intervals(
cls.query, cls.created, "day", "YYYY-MM-DD")
return data
def get_export_data(cls):
if cls.__name__ == 'Proposal':
# Export stats for each proposal type separately
return {}
count_attrs = [
'needs_help', 'needs_money', 'needs_laptop', 'one_day',
'notice_required', 'may_record', 'state'
]
edits_attrs = [
'published_title', 'published_description', 'requirements',
'length', 'notice_required', 'needs_help', 'needs_money',
'one_day', 'has_rejected_email', 'published_names',
'arrival_period', 'departure_period', 'telephone_number',
'may_record', 'needs_laptop', 'available_times', 'attendees',
'cost', 'size', 'funds', 'age_range', 'participant_equipment'
]
# FIXME: include published_title
proposals = cls.query.with_entities(
cls.id,
cls.title,
cls.description,
cls.favourite_count, # don't care about performance here
cls.length,
cls.notice_required,
cls.needs_money,
cls.available_times,
cls.allowed_times,
cls.arrival_period,
cls.departure_period,
cls.needs_laptop,
cls.may_record,
).order_by(cls.id)
if cls.__name__ == 'WorkshopProposal':
proposals = proposals.add_columns(cls.attendees, cls.cost)
elif cls.__name__ == 'InstallationProposal':
proposals = proposals.add_columns(cls.size, cls.funds)
elif cls.__name__ == 'YouthWorkshopProposal':
proposals = proposals.add_columns(cls.attendees, cls.cost,
cls.age_range,
cls.participant_equipment)
# Some unaccepted proposals have scheduling data, but we shouldn't need to keep that
accepted_columns = (
User.name,
User.email,
cls.published_names,
cls.scheduled_time,
cls.scheduled_duration,
Venue.name,
)
accepted_proposals = proposals.filter(cls.state.in_(['accepted', 'finished'])) \
.outerjoin(cls.scheduled_venue) \
.join(cls.user) \
.add_columns(*accepted_columns)
other_proposals = proposals.filter(
~cls.state.in_(['accepted', 'finished']))
user_favourites = cls.query.filter(cls.state.in_(['accepted', 'finished'])) \
.join(cls.favourites) \
.with_entities(User.id.label('user_id'), cls.id) \
.order_by(User.id)
anon_favourites = []
for user_id, proposals in groupby(user_favourites,
lambda r: r.user_id):
anon_favourites.append([p.id for p in proposals])
anon_favourites.sort()
public_columns = (
cls.published_title,
cls.published_description,
cls.published_names.label('names'),
cls.may_record,
cls.scheduled_time,
cls.scheduled_duration,
Venue.name.label('venue'),
)
accepted_public = cls.query.filter(cls.state.in_(['accepted', 'finished'])) \
.outerjoin(cls.scheduled_venue) \
.with_entities(*public_columns)
favourite_counts = [p.favourite_count for p in proposals]
data = {
'private': {
'proposals': {
'accepted_proposals': accepted_proposals,
'other_proposals': other_proposals,
},
'favourites': anon_favourites,
},
'public': {
'proposals': {
'counts': export_attr_counts(cls, count_attrs),
'edits': export_attr_edits(cls, edits_attrs),
'accepted': accepted_public,
},
'favourites': {
'counts':
bucketise(favourite_counts,
[0, 1, 10, 20, 30, 40, 50, 100, 200]),
},
},
'tables': [
'proposal', 'proposal_version', 'favourite_proposal',
'favourite_proposal_version'
],
}
data['public']['proposals']['counts'][
'created_week'] = export_intervals(cls.query, cls.created, 'week',
'YYYY-MM-DD')
return data
def get_export_data(cls):
if cls.__name__ == "Proposal":
# Export stats for each proposal type separately
return {}
count_attrs = [
"needs_help",
"needs_money",
"needs_laptop",
"one_day",
"notice_required",
"may_record",
"state",
]
edits_attrs = [
"published_title",
"published_description",
"requirements",
"length",
"notice_required",
"needs_help",
"needs_money",
"one_day",
"has_rejected_email",
"published_names",
"arrival_period",
"departure_period",
"telephone_number",
"may_record",
"needs_laptop",
"available_times",
"attendees",
"cost",
"size",
"funds",
"age_range",
"participant_equipment",
]
# FIXME: include published_title
proposals = cls.query.with_entities(
cls.id,
cls.title,
cls.description,
cls.favourite_count, # don't care about performance here
cls.length,
cls.notice_required,
cls.needs_money,
cls.available_times,
cls.allowed_times,
cls.arrival_period,
cls.departure_period,
cls.needs_laptop,
cls.may_record,
).order_by(cls.id)
if cls.__name__ == "WorkshopProposal":
proposals = proposals.add_columns(cls.attendees, cls.cost)
elif cls.__name__ == "InstallationProposal":
proposals = proposals.add_columns(cls.size, cls.funds)
elif cls.__name__ == "YouthWorkshopProposal":
proposals = proposals.add_columns(
cls.attendees, cls.cost, cls.age_range, cls.participant_equipment
)
# Some unaccepted proposals have scheduling data, but we shouldn't need to keep that
accepted_columns = (
User.name,
User.email,
cls.published_names,
cls.scheduled_time,
cls.scheduled_duration,
Venue.name,
)
accepted_proposals = (
proposals.filter(cls.state.in_(["accepted", "finished"]))
.outerjoin(cls.scheduled_venue)
.join(cls.user)
.add_columns(*accepted_columns)
)
other_proposals = proposals.filter(~cls.state.in_(["accepted", "finished"]))
user_favourites = (
cls.query.filter(cls.state.in_(["accepted", "finished"]))
.join(cls.favourites)
.with_entities(User.id.label("user_id"), cls.id)
.order_by(User.id)
)
anon_favourites = []
for user_id, proposals in groupby(user_favourites, lambda r: r.user_id):
anon_favourites.append([p.id for p in proposals])
anon_favourites.sort()
public_columns = (
cls.published_title,
cls.published_description,
cls.published_names.label("names"),
cls.may_record,
cls.scheduled_time,
cls.scheduled_duration,
Venue.name.label("venue"),
)
accepted_public = (
cls.query.filter(cls.state.in_(["accepted", "finished"]))
.outerjoin(cls.scheduled_venue)
.with_entities(*public_columns)
)
favourite_counts = [p.favourite_count for p in proposals]
data = {
"private": {
"proposals": {
"accepted_proposals": accepted_proposals,
"other_proposals": other_proposals,
},
"favourites": anon_favourites,
},
"public": {
"proposals": {
"counts": export_attr_counts(cls, count_attrs),
"edits": export_attr_edits(cls, edits_attrs),
"accepted": accepted_public,
},
"favourites": {
"counts": bucketise(
favourite_counts, [0, 1, 10, 20, 30, 40, 50, 100, 200]
)
},
},
"tables": [
"proposal",
"proposal_version",
"favourite_proposal",
"favourite_proposal_version",
],
}
data["public"]["proposals"]["counts"]["created_week"] = export_intervals(
cls.query, cls.created, "week", "YYYY-MM-DD"
)
return data
def get_export_data(cls):
if cls.__name__ == 'Proposal':
# Export stats for each proposal type separately
return {}
count_attrs = ['needs_help', 'needs_money', 'needs_laptop',
'one_day', 'notice_required', 'may_record', 'state']
edits_attrs = ['published_title', 'published_description', 'requirements', 'length',
'notice_required', 'needs_help', 'needs_money', 'one_day',
'has_rejected_email', 'published_names', 'arrival_period',
'departure_period', 'telephone_number', 'may_record',
'needs_laptop', 'available_times',
'attendees', 'cost', 'size', 'funds',
'age_range', 'participant_equipment']
# FIXME: include published_title
proposals = cls.query.with_entities(
cls.id, cls.title, cls.description,
cls.favourite_count, # don't care about performance here
cls.length, cls.notice_required, cls.needs_money,
cls.available_times, cls.allowed_times,
cls.arrival_period, cls.departure_period,
cls.needs_laptop, cls.may_record,
).order_by(cls.id)
if cls.__name__ == 'WorkshopProposal':
proposals = proposals.add_columns(cls.attendees, cls.cost)
elif cls.__name__ == 'InstallationProposal':
proposals = proposals.add_columns(cls.size, cls.funds)
elif cls.__name__ == 'YouthWorkshopProposal':
proposals = proposals.add_columns(cls.attendees, cls.cost, cls.age_range, cls.participant_equipment)
# Some unaccepted proposals have scheduling data, but we shouldn't need to keep that
accepted_columns = (
User.name, User.email, cls.published_names,
cls.scheduled_time, cls.scheduled_duration, Venue.name,
)
accepted_proposals = proposals.filter(cls.state.in_(['accepted', 'finished'])) \
.outerjoin(cls.scheduled_venue) \
.join(cls.user) \
.add_columns(*accepted_columns)
other_proposals = proposals.filter(~cls.state.in_(['accepted', 'finished']))
user_favourites = cls.query.filter(cls.state.in_(['accepted', 'finished'])) \
.join(cls.favourites) \
.with_entities(User.id.label('user_id'), cls.id) \
.order_by(User.id)
anon_favourites = []
for user_id, proposals in groupby(user_favourites, lambda r: r.user_id):
anon_favourites.append([p.id for p in proposals])
anon_favourites.sort()
public_columns = (
cls.published_title, cls.published_description,
cls.published_names.label('names'), cls.may_record,
cls.scheduled_time, cls.scheduled_duration, Venue.name.label('venue'),
)
accepted_public = cls.query.filter(cls.state.in_(['accepted', 'finished'])) \
.outerjoin(cls.scheduled_venue) \
.with_entities(*public_columns)
favourite_counts = [p.favourite_count for p in proposals]
data = {
'private': {
'proposals': {
'accepted_proposals': accepted_proposals,
'other_proposals': other_proposals,
},
'favourites': anon_favourites,
},
'public': {
'proposals': {
'counts': export_attr_counts(cls, count_attrs),
'edits': export_attr_edits(cls, edits_attrs),
'accepted': accepted_public,
},
'favourites': {
'counts': bucketise(favourite_counts, [0, 1, 10, 20, 30, 40, 50, 100, 200]),
},
},
'tables': ['proposal', 'proposal_version', 'favourite_proposal', 'favourite_proposal_version'],
}
data['public']['proposals']['counts']['created_week'] = export_intervals(cls.query, cls.created, 'week', 'YYYY-MM-DD')
return data