def detail_teacher_bamboo(request, uid):
''' Report Card View leveraging bamboo aggregation '''
context = {'category': 'teachers',
'schoolcat': '%s|%s'
% (request.user.project.slug, 'school_names')}
# retrieve short ID
sid = request.GET.get('short', None)
if not sid:
sid = short_id_from(uid)
# build barcode (identifier on submissions) from UID param.
barcode = build_urlid_with(uid, sid)
connection = Connection(get_bamboo_url(request.user.project))
teacher_dataset = CachedDataset(get_bamboo_dataset_id(request.user.project,
is_registration=True),
connection=connection)
# Retrieve teacher data from bamboo (1req)
teacher = teacher_dataset.get_data(query={'barcode': barcode},
cache=True, cache_expiry=VLONG)[0]
context.update({'teacher': teacher})
teacher.update(detailed_id_dict(teacher))
return render(request, 'detail_teacher_bamboo.html', context)
def detail_teacher_django(request, uid):
''' Report Card View processing data from submissions list/data only
2 bamboo requests:
- teacher data from uuid
- list of submissions for that teacher
All processing/grouping done in python. '''
context = {'category': 'teachers',
'schoolcat': '%s|%s'
% (request.user.project.slug, 'school_names')}
connection = Connection(get_bamboo_url(request.user.project))
main_dataset = CachedDataset(get_bamboo_dataset_id(request.user.project),
connection=connection)
teacher_dataset = CachedDataset(get_bamboo_dataset_id(request.user.project,
is_registration=True),
connection=connection)
def get_age_group(sub):
''' return age group (key str) of a given submission based on age'''
for key, age_range in REPORTS_AGE_GROUPS.items():
if (sub.get(u'general_information_age', 0)
in range(age_range[0], age_range[1] + 1)):
return key
return u"all"
def init_reports():
''' A reports container with initial values '''
reports = {}
for age_group in REPORTS_AGE_GROUPS.keys():
reports[age_group] = {}
for sex in ('male', 'female', 'total'):
reports[age_group][sex] = {}
for level in REPORTS_READING_LEVELS.keys() \
+ REPORTS_NUMERACY_LEVELS.keys() + ['total']:
reports[age_group][sex][level] = {'nb': 0, 'percent': None}
return reports
def compute_report_for(reports, submission, is_numeracy=False):
''' increment counters on all categories for a submission '''
age_group = get_age_group(submission)
sex = submission.get('general_information_sex')
level = submission.get('learning_levels_numeracy_nothing' if is_numeracy
else 'learning_levels_reading_nothing')
# AGE GRP SEX LEVEL
reports['all']['total']['total']['nb'] += 1
reports['all']['total'][level]['nb'] += 1
reports['all'][sex]['total']['nb'] += 1
reports['all'][sex][level]['nb'] += 1
reports[age_group][sex][level]['nb'] += 1
reports[age_group]['total'][level]['nb'] += 1
reports[age_group][sex]['total']['nb'] += 1
reports[age_group]['total']['total']['nb'] += 1
def compute_percentages(reports):
''' calculates the percentages fields for the reports dict '''
def pc(num, denum):
try:
return float(num['nb']) / float(denum['nb'])
except ZeroDivisionError:
return 0
for age_group, ago in reports.items():
for sex, so in ago.items():
for level, lo in so.items():
reports[age_group][sex][level]['percent'] = \
pc(reports[age_group][sex][level],
reports[age_group][sex]['total'])
def sort_reports(reports_dict):
''' sort report by Age (asc) then gender keeping total/All at last '''
def cmp_rep(x, y):
if x == y:
return 0
# 'all' age group is last
if x == 'all' or y == 'all':
return 1 if x == 'all' else -1
# compare minimum age for group to sort
xa_min = REPORTS_AGE_GROUPS.get(x, (100, 0))[0]
ya_min = REPORTS_AGE_GROUPS.get(y, (100, 0))[0]
return 1 if xa_min > ya_min else -1
reports = []
# loop on dict and transform to:
# - dicts composed of {'name': x, 'data': y}
# - data is an ordered array of dicts
for age_group in sorted(reports_dict.keys(), cmp=cmp_rep):
age_group_data = reports_dict.get(age_group)
age_group_data.update({'name': age_group})
age_group_sex = []
for sex in sorted(age_group_data.keys()):
if sex == 'name':
continue
sex_data = age_group_data.get(sex)
sex_data.update({'name': sex})
age_group_sex.append(sex_data)
reports.append({'name': age_group,
'data': age_group_sex})
return reports
# retrieve short ID
sid = request.GET.get('short', None)
if not sid:
sid = short_id_from(uid)
# if we don't have an UID, find out teacher from SID.
if uid == sid:
barcodes = {}
for bc in teacher_dataset.get_data(select=['barcode'],
cache=True, cache_expiry=VSHORT):
barcodes[short_id_from(bc)] = bc
barcode = barcodes.get(sid, '')
else:
barcode = uid
# Retrieve teacher data from bamboo (1req)
teacher = teacher_dataset.get_data(query={'barcode': barcode},
cache=True, cache_expiry=VLONG)[0]
teacher.update(detailed_id_dict(teacher))
# retrieve list of submissions from bamboo (1req)
submissions = main_dataset.get_data(
query={'$or': [{'teacher_barcode': barcode},
{'teacher_fallback_id':
{'$regex':sid, '$options':'i'}}]},
select=['general_information_age',
'general_information_sex',
'learning_levels_numeracy_nothing',
'learning_levels_reading_nothing',
'school_junior_secondary',
'school_primary',
'school_senior_secondary',
'schooling_status_grades'])
# initialize containers for reading report and numeracy report.
reading_dict = init_reports()
numeracy_dict = init_reports()
# loop on submissions to fill reading/num reports
for submission in submissions:
compute_report_for(reading_dict, submission)
compute_report_for(numeracy_dict, submission, is_numeracy=True)
# compute percentages for reading/num reports
compute_percentages(reading_dict)
compute_percentages(numeracy_dict)
# sort/transform reports for template
reading_reports = sort_reports(reading_dict)
numeracy_reports = sort_reports(numeracy_dict)
context.update({'teacher': teacher,
'reading_reports': reading_reports,
'numeracy_reports': numeracy_reports})
return render(request, 'detail_teacher.html', context)
