from faker import Faker fake = Faker() Faker.seed(0)

>>> Faker.seed(0) >>> for _ in range(5): ... fake.pyfloat() ... -6.36438676418356 -424604.985946604 -61.8878635605209 -829528891695.97 -69804.3874773259 · pyint(min_value: int = 0, max_value: int = 9999, step: int = 1) → int¶ · Examples: >>> Faker.seed(0) >>> for _ in range(5): ...

>>> Faker.seed(0) >>> for _ in range(5): ... fake.first_name_male() ... 'Ryan' 'Peter' 'Jason' 'David' 'Jorge' first_name_nonbinary() → str¶ · Examples: >>> Faker.seed(0) >>> for _ in range(5): ... fake.first_name_nonbinary() ... 'Megan' 'Katherine' 'Robert' 'Jonathan' 'William' language_name() → str¶ ·

If you are using pytest, you can seed the faker fixture by defining a faker_seed fixture. Please check out the pytest fixture docs to learn more. Run tests: $ tox · Write documentation for the providers of the default locale: $ python -m faker ...

March 23, 2023 - Faker Frenzy: How to Generate Diverse Seed Data with Python’s Faker Library Faker is a Python library that generates realistic and random seed data, such as names, addresses, phone numbers, and …

>>> Faker.seed(0) >>> for _ in range(5): ... fake.json(data_columns={'Spec':'@1.0.1', 'ID':'pyint', 'Details':{'Name':'name', 'Address':'address'}}, num_rows=2) ... '[{"Spec": "1.0.1", "ID": 6311, "Details": {"Name": "Jennifer Green", "Address": "7593 Juan Throughway Apt.

January 9, 2026 - Seeding gives use the same fake data result that was generated at first instance at that seed number. Python · from faker import Faker Faker.seed(1) fake = Faker() print(fake.name()) print(fake.address()) print(fake.email()) Output · Ryan ...

August 10, 2022 - # Using seed for reproducibility Faker.seed(5) secure_db = anonymous(Ecommerce) secure_db

November 11, 2023 - When using Faker for unit testing, you will often want to generate the same data set. For convenience, the generator also provide a seed() method, which seeds the shared random number generator.

August 17, 2024 - In the example below, my 10 names will remain the same after setting the random seed, but the one generated before setting the seed will continue to change. I usually set my random seed to 1234, but you can choose any integer—just be consistent. Awesome work so far! Now, let’s get a bit more sophisticated. Faker can generate much more than just names.

Calling the same script twice with the same seed produces the same results. from faker import Faker fake = Faker() fake.seed(4321) print fake.name() > Margaret Boehm

May 4, 2023 - from faker import Faker Faker.seed(0) fake = Faker()

Each generator can also be switched to its own instance of random.Random, separate to the shared one, by using the seed_instance() method, which acts the same way. For example: from faker import Faker fake = Faker() fake.seed_instance(4321) print(fake.name()) > Margaret Boehm

>>> Faker.seed(0) >>> for _ in range(5): ... fake.random_number(digits=3) ... 864 394 776 911 430 · >>> Faker.seed(0) >>> for _ in range(5): ... fake.random_number(digits=3, fix_len=False) ...

>>> Faker.seed(0) >>> for _ in range(5): ... fake.file_name(extension='') ...

January 21, 2025 - Now, let’s instantiate a new faker object. We can specify its seed number after that as follows. The seed number can be whatever an integer.

January 22, 2014 - import random from faker import Faker fake = Faker() # initial run fake.seed(1234) print fake.name() print fake.name() print fake.name() # repeated run with same data fake.seed(1234) print fake.name() print fake.name() print fake.name() # adding new fake calls prevent us from getting the same names we had originally fake.seed(1234) print fake.name(), fake.email() print fake.name(), fake.email() print fake.name(), fake.email() # One way is to implement a preserve/restore mechanism so that the user can get back to the previous trail of data fake.seed(1234) print fake.name() r = random.getstate()

from random import SystemRandom @pytest.fixture(scope="session", autouse=True) def faker_seed() -> int: """Create a random seed for the Faker library.""" return SystemRandom().randint(0, 999999)

An example how to use Faker python library to create fake data and inject them in a mysql database - db_feeder_with_faker.py