-
Notifications
You must be signed in to change notification settings - Fork 0
/
filter_by_quiz.py
221 lines (153 loc) · 8.97 KB
/
filter_by_quiz.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
import json
from urllib import response
import pandas as pd
import requests
import os, sys
from sqlalchemy import null
from gdive_util import gsheet
from process_application import ProcessApplication
from insert_response import InsertResponse
from secret import get_auth
curdir = os.path.dirname(os.path.realpath(__file__))
print(curdir)
cpath = os.path.dirname(curdir)
if not cpath in sys.path:
sys.path.append(cpath)
from strapi_methods import StrapiMethods as sm
from secret import get_auth
class FilterByQuiz:
def __init__(self):
self.api_url = "https://dev-cms.10academy.org"
self.token = get_auth(ssmkey='dev/strapi/token',
envvar='STRAPI_TOKEN',
fconfig=f'{cpath}/.env/Strapi_token.json')
print("Writing gspread config to /.env/Strapi_token.json")
def get_quiz_result(self):
sid_radar = '1_DRJTusGRG-S_V3xaTjTVSj6Ou2KVI3jGKxOe7D5dHc'
gd = gsheet(sheetid=sid_radar,fauth='gdrive_10acad_auth.json')
sname = f'Form responses 1'
try:
df = gd.get_sheet_df(sname)
# print(df.head())
# print(f'------------{sname} df.shape={df.shape}----')
except Exception as e:
print(f'ERROR: Could not obtain sheet for {sname}',e)
return df
def select_from_applicant(self):
dic_list= []
table= f"https://dev-cms.10academy.org/api/applicant-informations?pagination[page]=0&pagination[pageSize]=1042"
dic = sm.fetch_data(self, table,self.token['token'])
df_0 = pd.json_normalize(dic['data'])
pageCount = dic['meta']['pagination']['pageCount']
dic_list.append(df_0)
for i in range (pageCount):
if i == 0:
continue
else:
table= f"https://dev-cms.10academy.org/api/applicant-informations?pagination[page]={i+1}&pagination[pageSize]=100"
dic = sm.fetch_data(self, table,self.token['token'])
df = pd.json_normalize(dic['data'])
dic_list.append(df)
return dic_list
def get_applicant_gender(self):
app_list =FilterByQuiz.select_from_applicant(self)
merged = pd.concat(app_list)
merged.rename(columns = {'attributes.email':'Email address'}, inplace = True)
merged.rename(columns = {'attributes.gender':'gender'}, inplace = True)
merged = merged [['Email address', 'gender']]
new_df = merged.drop_duplicates(subset=['Email address'], keep='first')
return new_df
def process_quiz (self):
score_df = FilterByQuiz.get_quiz_result(self)
transform = score_df.T
transform.rename(columns = {"Email address: please ensure that you use the same email address as you used on your 10 Academy Batch 5 application. Using a different email address will make it much more difficult for us to assign this result to you.":'Email address'}, inplace = True)
user_list = ProcessApplication.select_from_trainees(self)
merged = pd.concat(user_list)
applicant_df = merged [merged['attributes.role']=="applicant"]
applicant_df.rename(columns = {'attributes.email':'Email address'}, inplace = True)
transform['Email address']= transform['Email address'].str.rstrip()
transform['Email address']= transform['Email address'].str.lower()
all_info_df = pd.merge(transform,applicant_df , on="Email address", how="left")
all_info_df.rename(columns = {'attributes.name':'name'}, inplace = True)
clean_df = all_info_df [['Score', 'Email address','id','name']]
ids = clean_df ['id'].to_list()
# print(ids)
gender_df = FilterByQuiz.get_applicant_gender(self)
gender = gender_df.drop_duplicates(keep='first')
with_gender = pd.merge(clean_df,gender , on="Email address", how="left")
post_process = with_gender.dropna()
# print("with gender",post_process)
# return post_process
return clean_df
def flatten_json(y):
out = {}
def flatten(x, name=''):
if type(x) is dict:
for a in x:
flatten(x[a], name + a + '_')
elif type(x) is list:
i = 0
for a in x:
flatten(a, name + str(i) + '_')
i += 1
else:
out[name[:-1]] = x
flatten(y)
return out
def select_review_from_trainees(self,id):
table= f"https://dev-cms.10academy.org/api/all-users/{id}?populate=%2A"
dic = sm.fetch_data(self, table,self.token['token'])
flat = FilterByQuiz.flatten_json(dic)
df = pd.json_normalize(flat)
# print(df.columns)
if 'data_attributes_reviews_data_1_id' in df.columns:
review_id = df['data_attributes_reviews_data_1_id']
email = df['data_attributes_email']
else:
review_id = df['data_attributes_reviews_data_0_id']
email = df['data_attributes_email']
return review_id, email
def score_val(self,row):
split_string = row['Score'].split("/", 1)
score = split_string[0]
if row['gender']=="Female":
return (int(score)+10)
else:
return score
def get_review_data(self):
quiz_data = FilterByQuiz.process_quiz(self)
exclude_email = InsertResponse.process_with_question_type(self)
valid_result = quiz_data[~quiz_data['Email address'].isin(exclude_email)]
valid_result['newScore'] = valid_result.apply(lambda row: FilterByQuiz.score_val(self,row), axis=1)
valid_result['newScore'] = valid_result['newScore'].astype('int32')
filtered_score = valid_result[valid_result['newScore']>39]
all_data = []
table= "https://dev-cms.10academy.org/api/grades/"
try:
for index, row in filtered_score.iterrows():
if int(row['id']) ==1082 or int(row['id']) ==1162 or int(row['id']) ==1196 or int(row['id']) ==620 or int(row['id']) ==481 or int(row['id']) ==772 or int(row['id']) ==1074 or int(row['id']) ==546 or int(row['id']) ==1299 or int(row['id']) ==1335 or int(row['id']) ==1303 or int(row['id']) ==1010 or int(row['id']) ==1371 or int(row['id']) ==829 or int(row['id']) ==531 or int(row['id']) ==1123 or int(row['id']) ==1034 or int(row['id']) ==1247 or int(row['id']) ==491 or int(row['id']) ==598 or int(row['id']) ==826 or int(row['id']) ==507 or int(row['id']) ==1067 or int(row['id']) ==694 or int(row['id']) ==1032 or int(row['id']) ==1311 or int(row['id']) ==1113 or int(row['id']) ==527 or int(row['id']) ==500 or int(row['id']) ==1252 or int(row['id']) ==1259 or int(row['id']) ==1137 or int(row['id']) ==1023 or int(row['id']) ==824 or int(row['id']) ==509 or int(row['id']) ==1155 or int(row['id']) ==1207 or int(row['id']) == 232 or int(row['id']) ==1178 or int(row['id']) ==892 or int(row['id']) ==1130 or int(row['id']) ==1238 or int(row['id']) ==533 or int(row['id']) ==800 or int(row['id']) ==360 or int(row['id']) ==847 or int(row['id']) ==739 or int(row['id']) ==259 or int(row['id']) ==719 or int(row['id']) ==746 or int(row['id']) ==521 or int(row['id']) ==847 or int(row['id']) ==1364 or int(row['id']) ==555 or int(row['id']) ==1211 or int(row['id']) ==817 or int(row['id']) ==1290 or int(row['id']) ==556 or int(row['id']) ==639 or int(row['id']) ==738 or int(row['id']) ==943 or int(row['id']) ==1286 or int(row['id']) ==886 or int(row['id']) ==553 or int(row['id']) ==1043:
continue
else:
grade_id = int(row['id'])
review_id, email= FilterByQuiz.select_review_from_trainees(self,int(row['id']))
if row['newScore']<=39:
grade_data ={
"label": "1hour_test",
"score": row['newScore'],
"all_user":int(grade_id),
"review":int(review_id)
}
print(grade_data)
# sm.insert_data(self,grade_data,table, self.token['token'])
else:
continue
# print(grade_data)
except Exception as e:
print ("Unable to load",e)
return valid_result
if __name__ == "__main__":
obj = FilterByQuiz()
# obj.process_quiz()
# obj.get_review_data()
# obj.select_review_from_trainees(id=847)
obj.sanitycheck()