def test_short_drug_name():
"""
Tests that the get_url function does not search for drug names shorter than 4 characters
"""
scraper = EverydayHealthScraper()
url = scraper.get_url('ACE')
assert not url
def test_get_url_real_drug_name():
"""
Tests that the get_url function returns the correct url for a standard drug name ('dupixent')
"""
scraper = EverydayHealthScraper()
url = scraper.get_url('dupixent')
assert url == 'https://www.everydayhealth.com/drugs/dupixent/reviews'
def test_drug_name_with_space():
"""
Tests that the get_url function returns the correct url for a drug name
that includes a space
"""
scraper = EverydayHealthScraper()
url = scraper.get_url('Mucinex Allergy')
assert url == 'https://www.everydayhealth.com/drugs/mucinex-allergy/reviews'
def test_url_fake_drug_name():
"""
Tests tha the get_url function returns 'None' for a drug name that does not have a review
page
"""
scraper = EverydayHealthScraper()
url = scraper.get_url('garbage')
assert not url
def main():
scraper = WebMDScraper(
) # non funziona DrugsScraper(), non funziona DrugRatingzScraper(), or EverydayHealthScraper()
url = ""
json_aggregrationReviews = {"website": "webmd.com"}
json_aggregrationReviews["ratingSystem"] = "stars"
json_aggregrationReviews["itemsNamesAggregration"] = input_list
reviewsAggregrate = []
for i in range(len(input_list)):
json_reviews = {"name": input_list[i]}
try:
url = scraper.get_url(input_list[i]) # or any other drug name
scraper.scrape(url)
dataframe_reviews = pd.DataFrame.from_dict(scraper.reviews)
json_reviews["averageEffectiveness"] = round(
pd.DataFrame.from_records(
dataframe_reviews["rating"])["effectiveness"].mean(), 1)
json_reviews["averageEaseOfUse"] = round(
pd.DataFrame.from_records(
dataframe_reviews["rating"])["ease of use"].mean(), 1)
json_reviews["averageSatisfaction"] = round(
pd.DataFrame.from_records(
dataframe_reviews["rating"])["satisfaction"].mean(), 1)
json_reviews["minRating"] = round(
pd.DataFrame.from_records(
dataframe_reviews["rating"])["satisfaction"].min(), 1)
json_reviews["maxRating"] = round(
pd.DataFrame.from_records(
dataframe_reviews["rating"])["satisfaction"].max(), 1)
json_reviews["reviews"] = scraper.reviews
except:
print("Could not get " + input_list[i] + " from webmd website")
webmd_names_errors.append(input_list[i])
reviewsAggregrate.append(json_reviews)
json_aggregrationReviews["aggregrateReviews"] = reviewsAggregrate
with open("webmdresult.json", "w") as f:
obj = json.dumps(json_aggregrationReviews, indent=4)
f.write(obj)
scraper2 = EverydayHealthScraper()
json_aggregrationReviews = {"website": "everydayhealth.com"}
json_aggregrationReviews["ratingSystem"] = "stars"
json_aggregrationReviews["itemsNamesAggregration"] = input_list
reviewsAggregrate = []
for i in range(len(input_list)):
json_reviews = {"name": input_list[i]}
try:
url = scraper2.get_url("Adderall")
print(url)
scraper2.scrape(url)
dataframe_reviews = pd.DataFrame.from_dict(scraper2.reviews)
json_reviews["averageRating"] = round(
dataframe_reviews["rating"].mean(), 1)
json_reviews["minRating"] = round(
dataframe_reviews["rating"].min(), 1)
json_reviews["maxRating"] = round(
dataframe_reviews["rating"].max(), 1)
json_reviews["reviews"] = scraper2.reviews
except:
print("Could not get " + input_list[i] +
" from everydayhealthscraper website ")
everydayhealth_names_errors.append(input_list[i])
reviewsAggregrate.append(json_reviews)
json_aggregrationReviews["aggregrateReviews"] = reviewsAggregrate
with open("everydayhealth.json", "w") as f:
obj = json.dumps(json_aggregrationReviews, indent=4)
f.write(obj)
if (len(webmd_names_errors) != 0):
print("I could not get from webmd " + str(webmd_names_errors))
if (len(everydayhealth_names_errors) != 0):
print("I could not get from everydayhealth " +
str(everydayhealth_names_errors))