Dumda 4.0.5

Python Library to get fast extensive Dummy Data for testing https://pypi.org/project/dumda/

Installation

pip install dumda

or update from previous version:

pip install --update dumda

Usage

This section will cover the functionality of Dumda and how you can power your applicaiton
with fast customizable randomly generated data.

import dumda

Names

You can generate random names with a handful of specifiers such as the associated
sex of the name and the format of the name string.

from dumda import random_name, random_names, names_by_prefix

# Basic call with default arguments, returns a full name
n1 = random_name()
print("Hello, world. My name is %s" % n1)

# You can specify the sex of the name generated (1 for female and 0 for male)
# the default is None, so any name of any sex is chosen
male_name = random_name(sex=0)
female_name = random_name(sex=1)
print("Hi, %s. My name is %s" % (male_name, female_name))

# finally you can specify the format of the string
# the default is First Last, but if you mark 'reversed' parameter as True
# it will return the name in Last, First format
formal_name = random_name(reversed=True)
print("Student: %s" % formal_name)

# Most relevantly you can generated n number of names and the parameter list
# stays the same
name_list = random_names(n=7, sex=0, reversed=False)  # returns an iterator
print(list(name_list))

# you can also retrieve names with just a given prefix
BEST_PREFIX = "oliv"
print(names_by_prefix(BEST_PREFIX, n=1, sex=0, full=False))

Output:

Hello, world. My name is Tracie Bradley
Hi, Hugo Flores. My name is Rosario Romero
Student: Benton, Audrea
['Kris Gould', 'Wes Heath', 'Arthur Larsen', 'Lucien Christian', 'Lincoln Moody', 'Cortez Jimenez', 'Giuseppe Meadows']
Oliver

Countries/Cities

You can generate random countries with a handful of specifiers as well.

from dumda import random_country, random_countries, random_city, random_cities, NAMEKEY, POPULATIONKEY, LNGKEY, \
    LATKEY

# Countries
c1 = random_country()  # you can generate a random country like names
print("I'm from %s" % c1)
c2 = random_country(iso=True)  # you can specify whether you want the country string to be in iso3 format
print("COUNTRY: %s" % c2)

# as with names, you can get an iterator of a specified amount of countries
country_codes = random_countries(10, iso=True)
print(list(country_codes))

# Cities
# you can generate random cities. There are 3 optional parameters
# 1. country - there are valid countries to get cities from
#               check COUNTRIES_WITH_CITIES_DATA to see, will raise Exception if not valid
# 2.populous - if marked, it will only return cities that have a population higher than
#               the average population of the dataset
# 3. returnobj - if marked, will return a dictionary object rather than just a city name str
#               - with data related to the city
# 4. pop - define the min population yourself rather than the average
city1 = random_city()
print("Random city: %s" % city1)
norwegian_city = random_city(country="norway")  # country string can be in any casing
print("I wonder how cold it is in %s, Norway" % norwegian_city)
city2 = random_city(country="United States", populous=True)
big_city = random_city(populous=True, pop=1_000_000)
print("%s is a pretty sizable place" % city2)
obj = random_city(country="Colombia", populous=True, returnobj=True)
# Keys are in the __init__ file
lng = obj[LNGKEY]
lat = obj[LATKEY]
print(f"{obj[NAMEKEY]} has a population of {obj[POPULATIONKEY]} and is located at: {lat, lng}")

# and of course, you can get numerous
print(list(random_cities(n=3, country="United States", populous=False, returnobj=True)))

Output:

I'm from Montenegro
COUNTRY: CIV
['ZAF', 'ALB', 'ARG', 'SWZ', 'MOZ', 'GBR', 'SWE', 'BGR', 'CZE', 'POL']
Random city: Presidente Medici
I wonder how cold it is in Haugesund, Norway
Chicago is a pretty sizable place
Pasto has a population of 382236 and is located at: (1.2136, -77.2811)
[{'name': 'Wescosville', 'latitude': 40.5617, 'longitude': -75.5489, 'country': 'United States', 'iso3': 'USA', 'population': 6694}, {'name': 'Moundsville', 'latitude': 39.9221, 'longitude': -80.7422, 'country': 'United States', 'iso3': 'USA', 'population': 8252}, {'name': 'Nampa', 'latitude': 43.5845, 'longitude': -116.5631, 'country': 'United States', 'iso3': 'USA', 'population': 184428}]

Misc.

There is also some other functions for full person recreation, (and then more on that)

from dumda import generate_email, generate_number, Person, names_by_prefix
import json

# generate an email address
email_list = []
names = list(names_by_prefix("oli", n=3, full=True))
for i in range(3):
    # name passed to email generator *must* be a full name of style; First Last
    e = generate_email(names[i])
    email_list.append(e)
    
print(email_list)

# generate a phone number
print("Call me: %s" % generate_number())

# possible parameters
# - area_code (defaults to randomly generated) and country_code (defaults to +1)

DC_AREA_CODE = 202
print("for store hours call: %s" % generate_number(area_code=DC_AREA_CODE))




p = Person() # generate a person object that uses all of the functions in Dumda
print(json.dumps(p.json(), indent=4))

Output:

['ohuffman@baz.net', 'olivesloan@qux.org', 'olivalin@bar.org']
Call me: +1 (743)-792-9493
for store hours call: +1 (202)-293-2130
{
    "name": "Katelynn Brown",
    "location": {
        "name": "Atlantic",
        "latitude": 41.3957,
        "longitude": -95.0138,
        "country": "United States",
        "iso3": "USA",
        "population": 6526
    },
    "email": "katelynnbrown@foo.org",
    "phone": "+1 (793)-759-380"
}