def response_with_students_csv_download(sids, benchmark):
rows = []
for student in get_student_profiles(sids=sids):
profile = student.get('profile')
profile = profile and json.loads(profile)
rows.append({
'first_name': profile.get('firstName'),
'last_name': profile.get('lastName'),
'sid': profile.get('sid'),
'email': profile.get('sisProfile', {}).get('emailAddress'),
'phone': profile.get('sisProfile', {}).get('phoneNumber'),
})
benchmark('end')
def _norm(row, key):
value = row.get(key)
return value and value.upper()
return response_with_csv_download(
rows=sorted(
rows,
key=lambda r:
(_norm(r, 'last_name'), _norm(r, 'first_name'), _norm(r, 'sid'))),
filename_prefix='cohort',
fieldnames=['first_name', 'last_name', 'sid', 'email', 'phone'],
)
def download_boa_users_csv():
users = _get_boa_users()
fieldnames = users[-1].keys()
return response_with_csv_download(
rows=sorted(users, key=lambda row: row['last_name'].upper()),
filename_prefix='boa_users',
fieldnames=fieldnames,
)
def response_with_admits_csv_download(sids, fieldnames, benchmark):
key_aliases = {
'cs_empl_id': 'sid',
}
def _row_for_csv(result):
return {f: result.get(key_aliases.get(f, f)) for f in fieldnames}
rows = [_row_for_csv(student) for student in get_admitted_students_by_sids(sids=sids)]
benchmark('end')
return response_with_csv_download(
rows=sorted(rows, key=lambda r: (_norm(r, 'last_name'), _norm(r, 'first_name'), _norm(r, 'cs_empl_id'))),
filename_prefix='cohort',
fieldnames=fieldnames,
)
def get_boa_notes_metadata():
return response_with_csv_download(
rows=get_summary_of_boa_notes(),
filename_prefix='boa_advising_notes_metadata',
fieldnames=[
'author_uid',
'author_name',
'author_role',
'author_dept_codes',
'sid',
'subject',
'topics',
'created_at',
'updated_at',
],
)
def alerts_log_export():
def _param_to_utc_date(key):
value = (params.get(key) or '').strip()
return localized_timestamp_to_utc(
value, date_format='%m/%d/%Y') if value else None
params = request.get_json()
from_date_utc = _param_to_utc_date('fromDate')
to_date_utc = _param_to_utc_date('toDate') + timedelta(days=1)
if from_date_utc and to_date_utc:
def _to_api_json(alert):
term_id_match = re.search(r'^2[012]\d[0258]', alert.key[0:4])
active_until = alert.deleted_at or utc_now()
return {
'sid':
alert.sid,
'term':
term_name_for_sis_id(term_id_match.string)
if term_id_match else None,
'key':
alert.key,
'type':
alert.alert_type,
'is_active':
not alert.deleted_at,
'active_duration_hours':
round(
(active_until - alert.created_at).total_seconds() / 3600),
'created_at':
alert.created_at,
'deleted_at':
alert.deleted_at,
}
alerts = Alert.get_alerts_per_date_range(from_date_utc, to_date_utc)
return response_with_csv_download(
rows=[_to_api_json(a) for a in alerts],
filename_prefix='alerts_log',
fieldnames=[
'sid', 'term', 'key', 'type', 'is_active',
'active_duration_hours', 'created_at', 'deleted_at'
],
)
else:
raise BadRequestError('Invalid arguments')
def download_boa_users_csv():
rows = []
for dept in _get_boa_user_groups():
for user in dept['users']:
rows.append(
{
'last_name': user.get('lastName') or '',
'first_name': user.get('firstName') or '',
'uid': user.get('uid'),
'email': user.get('campusEmail') or user.get('email'),
'dept_code': dept.get('code'),
'dept_name': dept.get('name'),
}, )
return response_with_csv_download(
rows=sorted(rows, key=lambda row: row['last_name'].upper()),
filename_prefix='boa_users',
fieldnames=[
'last_name', 'first_name', 'uid', 'email', 'dept_code', 'dept_name'
],
)
def response_with_students_csv_download(sids, fieldnames, benchmark):
rows = []
getters = {
'first_name':
lambda profile: profile.get('firstName'),
'last_name':
lambda profile: profile.get('lastName'),
'sid':
lambda profile: profile.get('sid'),
'email':
lambda profile: profile.get('sisProfile', {}).get('emailAddress'),
'phone':
lambda profile: profile.get('sisProfile', {}).get('phoneNumber'),
'majors':
lambda profile: ';'.join([
plan.get('description')
for plan in profile.get('sisProfile', {}).get('plans', [])
if plan.get('status') == 'Active'
], ),
'level':
lambda profile: profile.get('sisProfile', {}).get('level', {}).get(
'description'),
'terms_in_attendance':
lambda profile: profile.get('sisProfile', {}).get('termsInAttendance'),
'expected_graduation_date':
lambda profile: profile.get('sisProfile', {}).get(
'expectedGraduationTerm', {}).get('name'),
'units_completed':
lambda profile: profile.get('sisProfile', {}).get('cumulativeUnits'),
'term_gpa':
lambda profile: profile.get('termGpa'),
'cumulative_gpa':
lambda profile: profile.get('sisProfile', {}).get('cumulativeGPA'),
'program_status':
lambda profile: profile.get('sisProfile', {}).get(
'academicCareerStatus'),
}
term_gpas = get_term_gpas_by_sid(sids, as_dicts=True)
for student in get_student_profiles(sids=sids):
profile = student.get('profile')
profile = profile and json.loads(profile)
student_term_gpas = term_gpas.get(profile['sid'])
profile['termGpa'] = student_term_gpas[sorted(
student_term_gpas)[-1]] if student_term_gpas else None
row = {}
for fieldname in fieldnames:
row[fieldname] = getters[fieldname](profile)
rows.append(row)
benchmark('end')
def _norm(row, key):
value = row.get(key)
return value and value.upper()
return response_with_csv_download(
rows=sorted(
rows,
key=lambda r:
(_norm(r, 'last_name'), _norm(r, 'first_name'), _norm(r, 'sid'))),
filename_prefix='cohort',
fieldnames=fieldnames,
)
def response_with_students_csv_download(sids, fieldnames, benchmark):
term_id_last = previous_term_id(current_term_id())
term_id_previous = previous_term_id(term_id_last)
rows = []
getters = {
'first_name':
lambda profile: profile.get('firstName'),
'last_name':
lambda profile: profile.get('lastName'),
'sid':
lambda profile: profile.get('sid'),
'email':
lambda profile: profile.get('sisProfile', {}).get('emailAddress'),
'phone':
lambda profile: profile.get('sisProfile', {}).get('phoneNumber'),
'majors':
lambda profile: ';'.join([
plan.get('description')
for plan in profile.get('sisProfile', {}).get('plans', [])
if plan.get('status') == 'Active'
], ),
'intended_majors':
lambda profile: ';'.join([
major.get('description')
for major in profile.get('sisProfile', {}).get('intendedMajors')
], ),
'level_by_units':
lambda profile: profile.get('sisProfile', {}).get('level', {}).get(
'description'),
'minors':
lambda profile: ';'.join([
plan.get('description')
for plan in profile.get('sisProfile', {}).get('plansMinor', [])
if plan.get('status') == 'Active'
], ),
'subplans':
lambda profile: ';'.join([
subplan
for subplan in profile.get('sisProfile', {}).get('subplans', [])
]),
'terms_in_attendance':
lambda profile: profile.get('sisProfile', {}).get('termsInAttendance'),
'expected_graduation_term':
lambda profile: profile.get('sisProfile', {}).get(
'expectedGraduationTerm', {}).get('name'),
'units_completed':
lambda profile: profile.get('sisProfile', {}).get('cumulativeUnits'),
f'term_gpa_{term_id_previous}':
lambda profile: profile.get('termGpa', {}).get(term_id_previous),
f'term_gpa_{term_id_last}':
lambda profile: profile.get('termGpa', {}).get(term_id_last),
'cumulative_gpa':
lambda profile: profile.get('sisProfile', {}).get('cumulativeGPA'),
'program_status':
lambda profile: ';'.join(
list(
set([
plan.get('status')
for plan in profile.get('sisProfile', {}).get('plans', [])
], ), ), ),
'academic_standing':
lambda profile: profile.get('academicStanding'),
'transfer':
lambda profile: 'Yes'
if profile.get('sisProfile', {}).get('transfer') else '',
'intended_major':
lambda profile: ', '.join([
major.get('description') for major in
(profile.get('sisProfile', {}).get('intendedMajors') or [])
]),
'units_in_progress':
lambda profile: profile.get('enrolledUnits', {}),
}
academic_standing = get_academic_standing_by_sid(sids, as_dicts=True)
term_gpas = get_term_gpas_by_sid(sids, as_dicts=True)
term_units = get_term_units_by_sid(current_term_id(), sids)
def _get_last_element(results):
return results[sorted(results)[-1]] if results else None
def _add_row(student_profile):
student_profile['academicStanding'] = _get_last_element(
academic_standing.get(student_profile['sid']))
student_profile['termGpa'] = term_gpas.get(student_profile['sid'], {})
student_profile['enrolledUnits'] = term_units[student_profile['sid']]
row = {}
for fieldname in fieldnames:
row[fieldname] = getters[fieldname](student_profile)
rows.append(row)
students = get_student_profiles(sids=sids)
for student in students:
profile = student.get('profile')
if profile:
_add_row(json.loads(profile))
remaining_sids = list(set(sids) - set([s.get('sid') for s in students]))
if remaining_sids:
for profile in get_historical_student_profiles(remaining_sids):
_add_row(profile)
benchmark('end')
return response_with_csv_download(
rows=sorted(
rows,
key=lambda r:
(_norm(r, 'last_name'), _norm(r, 'first_name'), _norm(r, 'sid'))),
filename_prefix='cohort',
fieldnames=fieldnames,
)
