def get_photos(id):
response = []
connect('high_school')
if not HighSchool.objects(id=id):
response = "invalid id in request"
return jsonify(response), 400
else:
for school in HighSchool.objects(id=id):
name = school.name.replace(' ', '%20')
url_textsearch = 'https://maps.googleapis.com/maps/api/place/textsearch/json?query=' + \
name + '&key=AIzaSyBqleXsttoPMyDVWDMQgcYwutB7ENx4icQ'
with urllib.request.urlopen(url_textsearch) as textsearch_json:
textsearch_data = json.load(textsearch_json)
if textsearch_data["status"] != "OK":
response = []
return jsonify(response), 200
place_id = textsearch_data["results"][0]["place_id"]
url_details = 'https://maps.googleapis.com/maps/api/place/details/json?placeid=' + \
place_id + '&key=AIzaSyBqleXsttoPMyDVWDMQgcYwutB7ENx4icQ'
with urllib.request.urlopen(url_details) as details_json:
details_data = json.load(details_json)
if 'photos' in details_data["result"]:
for photo in details_data["result"]["photos"]:
photo_reference = photo["photo_reference"]
url_photo = 'https://maps.googleapis.com/maps/api/place/photo?photoreference=' + \
photo_reference + '&sensor=false&maxheight=1600&maxwidth=1600' \
'&key=AIzaSyBqleXsttoPMyDVWDMQgcYwutB7ENx4icQ'
response.append(url_photo)
return jsonify(response), 200
def avg_min_selective_score(sid):
response = {}
connect('high_school')
avg = -1
if not HighSchool.objects(id=sid):
response['error'] = "invalid id in request"
return jsonify(response), 400
else:
for school in HighSchool.objects(id=sid):
if school.selective == "Not Selective":
return jsonify({}), 200
scores = list(map(float, school.selective_entry_scores.values()))
avg = st.mean(scores)
return jsonify({'avg_min_selective_scores': int(avg)}), 200
def get_average_enrollments(sid):
response = {}
connect('high_school')
avg = 0
if not HighSchool.objects(id=sid):
response['error'] = "invalid id in request"
return jsonify(response), 400
else:
for school in HighSchool.objects(id=sid):
enrollments = list(map(float, school.enrollments.values()))
if len(enrollments) == 0:
return jsonify({}), 200
avg = st.mean(enrollments)
return jsonify({'avg_enrollments': int(avg)}), 200
def get_average_attendance(sid):
response = {}
connect('high_school')
avg = 0
if not HighSchool.objects(id=sid):
response['error'] = "invalid id in request"
return jsonify(response), 400
else:
for school in HighSchool.objects(id=sid):
attendance = list(map(float, school.attendance_rates.values()))
if len(attendance) == 0:
return jsonify({}), 200
avg = st.harmonic_mean(attendance)
return jsonify({'avg_attendance': avg}), 200
def compare_students():
schools = request.args.getlist('school_id')
connect('high_school')
num_students = {}
for sid in schools:
for school in HighSchool.objects(id=int(sid)):
# get current num. of students
num_students[school.name] = int(school.students)
return jsonify(num_students), 200
def compare_enrollments():
schools = request.args.getlist('school_id')
connect('high_school')
average_enrollments = {}
for sid in schools:
for school in HighSchool.objects(id=int(sid)):
# get the avg enrolments
enrollments = list(map(float, school.enrollments.values()))
average_enrollments[school.name] = st.mean(enrollments)
return jsonify(average_enrollments), 200
def compare_attendances():
schools = request.args.getlist('school_id')
connect('high_school')
average_attendances = {}
for sid in schools:
for school in HighSchool.objects(id=int(sid)):
# get the avg attendance_rates
attendance = list(map(float, school.attendance_rates.values()))
average_attendances[school.name] = st.harmonic_mean(attendance)
return jsonify(average_attendances), 200
def compare_selective_entry():
schools = request.args.getlist('school_id')
connect('high_school')
average_selective_entry = {}
for sid in schools:
for school in HighSchool.objects(id=int(sid)):
if school.selective != 'Not Selective':
scores = list(map(float, school.selective_entry_scores.values()))
average_selective_entry[school.name] = st.mean(scores)
return jsonify(average_selective_entry), 200
def parse_attendance_rates():
with open('static/2011-2017-attendance-rates-by-nsw-government-schools.csv') as csvfile:
rows = csv.reader(csvfile, delimiter=",")
connect('high_school')
for row in rows:
if row[0] != "school_code" and row[0] != '':
for school in HighSchool.objects(id=int(row[0])):
attendance_rates = {}
for i in range(0, 7):
attendance_rates[str(2011 + i)] = row[i + 2]
school.update(attendance_rates=attendance_rates)
def parse_enrolments():
with open('static/secondary-enrolments-by-school-2014-2018.csv') as csvfile:
connect('high_school')
rows = csv.reader(csvfile, delimiter=",")
enrollments = {}
for row in rows:
if row[0] != '' and row[0] != "School Code" and "Student Enrolments" not in row[0] \
and "Opened" not in row[0]:
school = HighSchool.objects(id=row[0])
if school is not None:
for i in range(0, 4):
enrollments[str(2014 + i)] = row[i + 3]
school.update(enrollments=enrollments)
def parse_selective_entry_scores():
with open('static/2015-2018-selective-high-schools-minimum-entry-scores.csv') as csvfile:
rows = csv.reader(csvfile, delimiter=",")
connect('high_school')
for row in rows:
name = row[0].replace(" (Virtual)", "")
name = name.replace(" (Day)", "")
name = name.replace("(", "")
name = name.replace(")", "")
for school in HighSchool.objects(name=name):
entry_scores = {}
for i in range(0, 4):
entry_scores[str(2015 + i)] = row[i + 1]
school.update(selective_entry_scores=entry_scores)