def test_age(): f = Faker() age1 = f.age() age2 = f.age() ok_(isinstance(age1, int)) ok_(isinstance(age2, int)) ok_(age1 >= f.min_age) ok_(age1 <= f.max_age) f = Faker(min_age=30, max_age=30) age1 = f.age() age2 = f.age() ok_(age1 == age2)
def main(): # How to create your own provider # Note you cannot have multiple locales!!!! fake = Faker(['en_UK']) # Add your provider fake.add_provider(AgeProvider(fake)) # Use it! print(fake.age())
def main(): fake = Faker() fake.add_provider(Provider) #with open('data.txt', 'r+') as outfile: for i in range(10): basic_profile = fake.simple_profile() basic_profile = fake.basics(basic_profile) profile = fake.build_profile(basic_profile, fake.gender(), fake.gender_preference(), fake.age(basic_profile['age_group']), fake.kids(), fake.drugs()) print(profile)
} recipeNames = [] recipeSteps = defaultdict(list) ##Now, let’s decide on the kind of data that we’re going to take from the Faker instance to be stored in the fake variable. #200,000 fake users #-- myuser (usr_id, usrname, password, email, age, weight, height, calorie_goal, date_joined) f1 = open("test_populate_user.sql", "w") f1.write("--Populating user table\n") for i in range(20): ids["user"] = ids["user"] + 1 username = fake.first_name() + str(i) password = fake.password() email = username + "@gmail.com" age = fake.age() weight = fake.weight() height = fake.height() calorie_goal = fake.calorie_goal() f1.write("insert into myuser(usrname, pssword, email, age, weight, height, calorie_goal) values ('{}', '{}', '{}', {}, {}, {}, {});\n".format(username, password, email, age, weight, height, calorie_goal)) f1.close() #600,000 fake recipes #-- recipe (recipe_id, recipe_name, recipe_description) f2 = open("test_populate_recipe.sql", "w") f2.write("--Populating recipe table\n") for i in range(60): ids["recipe"] = ids["recipe"] + 1 rname = fake.food_name() recipeNames.append(rname) recipe_description = fake.sentence()
def test_age(): f = Faker() age1 = f.age() age2 = f.age() ok_(isinstance(age1, int)) ok_(isinstance(age2, int))
from faker import Faker import csv output=open("dirty-data.csv','w') fake=Faker() header=['guid','age','birthday','signup_date','account_type'] mywriter=csv.writer(output) mywriter.writerow(header) for r in range(1000): mywriter.writerow([fake.guid(),fake.random_int(min=18, max=80, step=1), fake.guid(), fake.age(),fake.birthday(),fake.signup_date(),fake.account_type())]) output.close()
# symptom = options[random.randrange(len(options))] symptom = possibilities[random.randrange(len(possibilities))] if symptom in symptoms: continue symptoms.append(symptom) return symptoms gen.add_provider(MedicalProvider) f = open('csvfile.csv', 'w') f.write( 'ID,Age,Gender,Race,Blood Group,Disease Group A (0-5),Disease Group B (6-10),Disease Group C (11-20),Disease Group D (21-30),Disease Group E (31-40),Disease Group F (41-50),Disease Group G (51-60),Disease Group H (61-70),Disease Group I (70+),Current Symptoms\n' ) for i in range(2999): age = gen.age() gender = gen.gender() race = gen.race() blood = gen.blood() diseases = [ gen.diseases(5, gender), gen.diseases(10, gender), gen.diseases(20, gender), gen.diseases(30, gender), gen.diseases(40, gender), gen.diseases(50, gender), gen.diseases(60, gender), gen.diseases(70, gender), gen.diseases(80, gender) ] symptoms = gen.symptoms()
from elasticsearch import Elasticsearch from elasticsearch import helpers from faker import Faker fake = Faker() es = Elasticsearch() #or pi {127.0.0.1} actions = [ { "_index": "users", "_type": "doc", "_source": { "guid": fake.guid(), "age": fake.age(), "birthday": fake.birthday(), "signup_date": fake.signup_date(), "account_type": fake.account_type } } for x in range(998) # or for i,r in df.iterrows() ] response = helpers.bulk(es, actions) print(response)