def test_connection(self):
'''
This unittest will test whether the mongo driver is connecting successfully to:
Database name:
collection name = "aggregated_GCOE"
'''
try:
conn = mongo.mongo_driver()
conn.get_db_collection(DB_NAME, COLLECTION_NAME)
conn_status = True
except:
conn_status = False
return self.assertEqual(True, conn_status)
def test_course_api_endings(self):
'''
This unit test will ping each of the currently created api endings with a variety of different courses to make sure they hit.
'''
# Define the currently working courses - You can generate this by running api_functions.py
course_function_list = [
CourseFig1Table, CourseFig2Chart, CourseFig3Timeseries,
CourseFig4TableBar
]
# Generate random course/instructor IDs for the test
response = SearchAutocomplete(mongo_driver(), 'course')
res_dict = json.loads(json.dumps(response))
id_list = [el['value'] for el in res_dict]
test_id_list = random.choices(id_list, k=8)
print(
'Testing for the following instructor IDs, generated randomly from viable options: '
)
pprint.pprint(test_id_list)
# Create connection to the db
db = mongo.mongo_driver()
# Try the function for autocomplete for all courses
try:
print('SearchAutocomplete for all courses')
response = SearchAutocomplete(db, search_type='course')
response_dict = json.loads(json.dumps(response))
except:
return self.assertEqual(True, False)
for course in test_id_list:
print(course)
for func in course_function_list:
try:
response = func(db, course)
json.loads(json.dumps(response))
except:
return self.assertEqual(True, False)
return self.assertEqual(True, True)
def test_instructor_api_endings(self):
'''
This unit test will ping each of the currently created api endings with a variety of different instructors to make sure they hit.
'''
# Define the currently working course APIs
instructor_function_list = [
InstructorFig1Table, InstructorFig2Timeseries,
InstructorFig3TableBar
]
# Generate random course/instructor IDs for the test
response = SearchAutocomplete(mongo_driver(), 'instructor')
res_dict = json.loads(json.dumps(response))
id_list = [el['value'] for el in res_dict]
test_id_list = random.choices(id_list, k=8)
print(
'Testing for the following instructor IDs, generated randomly from viable options: '
)
pprint.pprint(test_id_list)
# Create connection to the db
db = mongo.mongo_driver()
try:
print('SearchAutocomplete for all instructors')
response = SearchAutocomplete(db, search_type='instructor')
response_dict = json.loads(json.dumps(response))
except:
return self.assertEqual(True, False)
print('Testing the api functions for the following instructors: ')
for instr in test_id_list:
print(instr)
for func in instructor_function_list:
try:
response = func(db, instr)
json.loads(json.dumps(response))
except:
return self.assertEqual(True, False)
return self.assertEqual(True, True)
from flask_cors import CORS
from data_loader import update_database
from mongo import mongo_driver
from bson.json_util import dumps
import pandas as pd
import json
import api_functions as api
# Establish a database connection
DB_NAME = "reviews-db"
COLLECTION_NAME = "reviews-collection"
# base route for this api version
base_api_route = '/api/v0/'
db = mongo_driver()
# PreCompute the instructor and course lists
instructor_list = api.SearchAutocomplete(db, 'instructor')
course_list = api.SearchAutocomplete(db, 'course')
app = Flask(__name__)
CORS(app)
# useful for testing
# curl -i http://localhost:5050/api/v0/
@app.route('/')
def hello_world():
return 'Ping <a href="/api/v0/">/api/v0/</a> for api'.format(str(request.remote_addr))
df_coll = pd.DataFrame(list(cursor))
df_coll.drop_duplicates(search_key, inplace=True)
df = pd.concat([df, df_coll], ignore_index=True, sort=True)
df.drop_duplicates(search_key, inplace=True)
# Now, we just need to convert the dataframe to a dictionary with needed form for search autocomplete
if search_type == 'course':
# Create the label column
df['label'] = df['Subject Code'].str.strip()+df['Course Number'].astype(str)+': '+df['Course Title']
return_list = [{'label':row['label'], 'value':row[search_key]} for index, row in df.iterrows()]
else:
df['label'] = df['Instructor First Name']+' '+ df['Instructor Last Name']
return_list = [{'label':row['label'], 'value':row[search_key]} for index, row in df.iterrows()]
return return_list
if __name__ == '__main__':
# Test the db search
# test = [201410, 201420, 201530, 201620, 201230, 201810]
# print(test)
# sort_by_term_code([201710, 201820, 201620, 201410, 201110, 201630, 201610])
# uuid_df, coll_name = query_df_from_mongo(mongo_driver(),cursor)
pprint.pprint(CourseFig1Table(mongo_driver(), "753572960")) # Statics
pprint.pprint(CourseFig2Chart(mongo_driver(), "753572960"))
pprint.pprint(CourseFig3Timeseries(mongo_driver(), "753572960"))
pprint.pprint(CourseFig4TableBar(mongo_driver(), "753572960")) # Make sure the full unmodified dataset is uploaded before running
pprint.pprint(InstructorFig1Table(mongo_driver(), 624629390)) # Janet Allen
pprint.pprint(InstructorFig2Timeseries(mongo_driver(), 624629390))
pprint.pprint(InstructorFig3TableBar(mongo_driver(), 624629390)) # Make sure the full unmodified dataset is uploaded before running
pprint.pprint(InstructorChipAPI(mongo_driver(), 624629390))