Domain Generators¶
DATAMIMIC domains are a vehicle for defining, bundling and reusing domain specific data generation, e.g. for personal data, addresses, internet, banking, telecom. They may be localized to specific languages and be grouped to hierarchical datasets, e.g. for continents, countries and regions.
DATAMIMIC includes several domains that have simple implementation of specific data generation. If you need further domains, we highly appreciate your feedback and contributions.
The following domains are included:
-
person: Data related to a person
-
address: Data related to contacting a person by post
-
organization: Organization data
-
finance: Finance data
-
net: Internet and network related data
-
product: Product-related data
-
br and us: Country specific data
Additionally, DATAMIMIC includes an easy way to utilize the FAKER library document below for additional datasets.
Person Related generators¶
The person domain has three major components:
-
Person: Generates Person entities
-
AcademicTitleGenerator: Generates academic titles The generator can be config with
academic_title_quota
. -
NobilityTitleGenerator: Generates nobility title The generator can be config with
noble_quota
. -
GivenNameGenerator: Generates given names
-
FamilyNameGenerator: Generates family names
-
BirthDateGenerator: Generates birth dates
-
GenderGenerator: Generates Gender values. The generated gender can be one of the values
MALE
,FEMALE
,OTHER
. The generator is configured with the propertyfemale_quota
,other_gender_quota
.female_quota
is highest priority, thenother_gender_quota
. -
EmailAddressGenerator: Generates Email addresses
Person Entity¶
Creates Person entities to be used for prototype-based data generation. It can be configured with dataset and locale property. The generated Person Entity exhibits the properties salutation, title, given_name, family_name (four fields dataset-dependent), gender, birthdate, age, email. If the chosen dataset definition provides name weights, DATAMIMIC generates person names according to their statistical probability. Of course, gender, salutation and given_name are consistent.
You can use the Person entity like this:
1 2 3 4 5 |
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to get output similar to this:
1 2 3 4 5 6 |
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The Person entity has the following data fields:
property name | type | property description |
---|---|---|
salutation | String | Salutation (e.g. Mr/Mrs) |
academic_title | String | Academic title (e.g. Dr) |
name | String | Name (first name + last name) |
given_name | String | Given name ('first name' in western countries) |
family_name | String | Family name ('surname' in western countries) |
gender | Gender | Gender (male, female or other) |
birthdate | Date | Birth date |
age | Integer | actual age |
phone | String | phone number in text |
String | email address | |
nobility_title | String | Noble title (e.g. Baron/Baroness) |
Person Entity Properties¶
The Person Entity can be configured with several properties:
Property | Description | Default Value |
---|---|---|
dataset | Either a region name or the two-letter-ISO-code of a country, e.g. US for the USA. | The user's default country |
min_age | The minimum age of generated persons | 15 |
max_age | The maximum age of generated persons | 105 |
female_quota | The quota of generated women (1 → 100%) | 0.49 |
other_gender_quota | The quota of generated other gender (1 → 100%) | 0.02 |
noble_quota | The rate of generated noble title (1 → 100%) | 0.001 |
academic_title_quota | The rate of generated academic title (1 → 100%) | 0.5 |
Supported countries¶
country | code | remarks |
---|---|---|
Austria | AT | most common 120 given names with absolute weight, most common 40 family names with absolute weight |
Australia | AU | most common 40 given names (unweighted), most common 20 family names with absolute weight |
Belgium | BE | most common 38 given names (unweighted), most common 15 family names with absolute weight |
Brazil | BR | most common 100 given names (unweighted), most common 29 family names (unweighted) |
Canada | CA | most common 80 given names (unweighted), most common 20 family names (unweighted). No coupling between given name locale and family name locale |
Switzerland | CH | most common 30 given names with absolute weight, most common 20 family names with absolute weight |
China | CN | Chinese letters. Most common 46 given names (unweighted), most common 106 family names with absolute weight |
Czech Republic | CZ | most common 20 given names with absolute weight, most common 20 family names with absolute weight. Female surnames are supported. |
Germany | DE | most common 1998 given names with absolute weight, most common 3421 family names with absolute weight |
Spain | ES | most common 40 given names (unweighted), most common 40 family names with absolute weight |
Finland | FI | most common 785 given names (unweighted), most common 448 family names (unweighted) |
France | FR | most common 100 given names (unweighted), most common 30 family names with relative weight |
Ireland | IE | most common 41 given names (unweighted), most common 26 family names (unweighted) |
Israel | IL | 264 given names (unweighted), most common 30 family names with relative weight |
India | IN | most common 155 given names (unweighted), most common 50 family names (unweighted) |
Italy | IT | most common 60 given names (unweighted), most common 20 family names (unweighted) |
Japan | JP | Kanji letters. Most common 109 given names (unweighted), most common 50 family names with absolute weight |
Republic of Korea | KR | Hangul letters. Most common 91 given names (unweighted), most common 182 family names with absolute weigh |
Netherlands | NL | 3228 given names (unweighted), most common 10 family names with absolute weight |
Norway | NO | most common 300 given names (unweighted), most common 100 family names with absolute weight |
New Zealand | NZ | most common 20 given names (unweighted), most common 8 family names (unweighted) |
Poland | PL | most common 67 given names with absolute weight, most common 20,000 family names with absolute weight. Female surnames are supported. |
Russia | RU | Cyrillic letters. Most common 33 given names with relative weight, most common 20 family names with relative weight. Female surnames are supported. |
Sweden | SE | 779 given names (unweighted), most common 22 family names with relative weight |
Slovenia | SI | most common 400 given names with relative weight, most common 200 family names with relative weight |
Slovakia | SK | most common 20 given names with relative weight, most common 22 family names with relative weight |
Turkey | TR | 1077 given names (unweighted), 37 family names (unweighted) |
Ukraine | UA | most common 48 given (unweighted), most common 20 family names (unweighted) |
United Kingdom | GB | most common 20 given (unweighted), most common 25 family names (unweighted) |
USA | US | most common 600 given names and most common 1000 family names both with absolute weight |
Address Generators¶
-
Address Entity: Generates addresses that match simple validity checks: The City exists, the ZIP code matches and the phone number area codes are right. The street names are random, so most addresses will not stand validation of real existence.
-
Country Entity: Generates countries
-
City Entity: Generates Cities for a given country
-
PhoneNumberGenerator: Generates landline telephone numbers for a country
-
StreetNameGenerator: Generates street names for a given country
Address Entity¶
You can use the Address entity like this:
1 2 3 4 5 |
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to get output similar to this:
1 2 3 4 5 6 |
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The generated Address entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
street | String | The regular street address |
house_number | String | The house number associated with the street address |
postal_code(zip_code) | String | The postal or ZIP code |
city | String | The name of the city |
state | String | The state or region |
country | String | The country |
country_code | String | Two-letter country codes, equal to dataset |
phone | String | Home phone number |
mobile_phone | String | Mobile phone number |
fax | String | Fax number |
organization | String | The associated organization |
City Entity¶
You can use the City entity like this:
1 2 3 4 5 |
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to get output similar to this:
1 2 3 4 5 6 |
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The generated City entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
name | String | The name of the city |
name_extension | String | Additional name or descriptor for the city |
state | String | The state or region where the city is located |
country | String | The country where the city is located |
area_code | String | The telephone area code for the city |
language | String | The primary language spoken in the city |
population | Integer | The population count of the city |
postal_code | String | The postal code of the city |
country_code | String | The country code of the city |
Country Entity¶
You can use the Country entity like this:
1 2 3 4 5 |
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to get output similar to this:
1 2 3 4 5 6 |
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The generated Country entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
iso_code | String | The ISO code representing the country |
name | String | The official name of the country |
default_language_locale | String | The default language locale used in the country |
phone_code | String | The international phone code for the country |
population | Integer | The population count of the country |
Supported countries¶
The following countries are supported for this domain:
country | code | remarks |
---|---|---|
USA | US | Valid ZIP codes and area codes, no assurance that the street exists in this city. |
United Kingdom | GB | Valid area codes, no postcodes, no assurance that the street exists in this city or the local phone number has the appropriate length. Contributions are welcome |
Germany | DE | Valid ZIP codes and area codes, no assurance that the street exists in this city or the local phone number has the appropriate length |
Switzerland | CH | Valid ZIP codes and area codes, no assurance that the street exists in this city or the local phone number has the appropriate length |
Brazil | BR | Valid ZIP codes and area codes, no assurance that the street exists in this city or the local phone number has the appropriate length |
Update:
We now support more country: | AD, AL, AT, AU, BA, BE, BG, CA, CY, CA, DK, EE, ES, FI, FR, GR, HR, HU, EI, IS, IT, LI, LT, LU, LV, MC, NL, NO, NZ, PL, PT, RO, RU, SE, SI, SK, SM, TH, TR, UA, VA, VE, VN |
---|---|
(Noted that some countries are missing postcodes, also no assurance that the street exists in this city or the local phone number has the appropriate length. Contributions are welcome.)
Net¶
The net domain provides the
- DomainGenerator, which generates Internet domain names
1 |
|
Organization¶
Provides the Company Entity along with the following generators:
-
CompanyNameGenerator, a generator for company names.
-
DepartmentNameGenerator, a generator for department names
If you use the CompanyNameGenerator like this:
1 2 3 4 |
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1 2 3 4 5 6 |
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Company names can be generated for the following countries:
country | code | remarks |
---|---|---|
Germany | DE | none |
USA | US | none |
Company Entity¶
The generated Company entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
city | String | The city where the company is located |
country | String | The country where the company is located |
country_code | String | The ISO country code |
String | The company's email address | |
fax | String | The company's fax number |
full_name | String | The full legal name of the company |
house_number | String | The house number associated with the company's address |
id | String | A unique identifier for the company |
sector | String | The sector or industry in which the company operates |
short_name | String | The short or common name of the company |
office_phone | String | The company's office phone number |
zip_code | String | The postal or ZIP code |
state | String | The state or region where the company is located |
street | String | The street address of the company |
url | String | The company's website URL |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 |
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Finance¶
Generates and validates finance related data:
The following generators are provided:
-
Bank Entity: Entity for data around a bank.
-
BankAccount Entity: Entity for data around a bank account.
-
CreditCard Entity: Entity for data around a credit card.
Bank Entity¶
The generated Bank entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
bank_data | dict | All bank data including name, SWIFT, routing, etc. |
name | String | Bank name (e.g., Chase Bank, Deutsche Bank) |
swift_code | String | International SWIFT code for the bank |
routing_number | String | Domestic routing number used in fund transfers |
bank_code | String | Alias of the SWIFT code |
bic | String | Bank Identifier Code |
bin | String | Bank Identification Number |
BankAccount Entity¶
The generated BankAccount entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
account_number | String | The bank account number |
bank_code | String | The code identifying the bank |
bank_name | String | The name of the bank |
bic | String | The Bank Identifier Code (BIC) |
iban | String | The International Bank Account Number (IBAN) |
account_type | String | Type of account (INVESTMENT, SAVINGS, ...) |
balance | float | Money balance in account |
currency | String | Currency code (USD, EUR, GBP, JPY, ...) |
created_date | datetime | Open account date |
last_transaction_date | datetime | Last used date |
bin | String | The bank identification number (BIN) |
CreditCard Entity¶
The generated CreditCard entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
card_number | String | The credit card number |
card_holder | String | The name of the cardholder |
cvc_number | String | The card verification code (CVC) number |
expiration_date | String | The expiration date of the credit card |
card_type | String | The type of the credit card (e.g., Visa, MasterCard) |
card_provider | String | The provider of the credit card (bank's name) |
cvv | String | CCV number of the credit card |
is_active | bool | The status of the credit card |
credit_limit | float | The maximum amount granted by the credit card |
current_balance | float | The total amount you owe at a specific point in time |
issue_date | datetime | The date the card was first issued with the expiration date. |
Ecommerce¶
-
EANGenerator: Generates both 8-digit and 13-digit EAN codes
-
Product Entity: Generates products including product IDs, names, descriptions, prices, categories, and other product attributes
-
Order Entity: Generates orders of buy products
Product Entity¶
User can use Product
entity like this
1 2 3 4 5 6 7 8 9 |
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The generated Product
entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
product_id | String | A unique product identifier (e.g., PROD3A1B2C4D) |
category | String | The product's category |
brand | String | The brand of the product |
name | String | A generated product name combining brand, adjective, and noun |
description | String | A detailed description with features, category, and benefits |
price | float | The price of the product |
sku | String | SKU in the format BRN-CAT-XXXXXX |
condition | String | Product condition (e.g., NEW, USED) |
availability | String | Availability status (e.g., IN_STOCK, OUT_OF_STOCK) |
currency | String | Currency code (e.g., USD, EUR) |
weight | float | Weight in kilograms |
dimensions | String | Dimensions in the format L x W x H cm |
color | String | Color of the product |
rating | float | Rating between 1.0 and 5.0 (supports half-star ratings) |
tags | list | Relevant tags based on category, brand, condition, and other factors |
Order Entity¶
You can use Order
entity like this
1 2 3 4 5 6 7 8 |
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The generated Order
entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
order_id | String | Unique order ID (e.g., ORD1A2B3C4) |
user_id | String | Unique user ID who placed the order |
product_list | list | A list of Product instances in the order |
date | datetime | Order date (randomly within the last 12 months) |
status | String | Order status (e.g., PENDING, SHIPPED, DELIVERED) |
payment_method | String | Payment method used (e.g., CREDIT_CARD, PAYPAL) |
shipping_method | String | Shipping type selected (e.g., STANDARD, EXPRESS) |
shipping_address | Address | Shipping address generated for the order |
billing_address | Address | Billing address (same as shipping in 80% of cases) |
currency | String | Currency code used in the transaction (e.g., USD) |
tax_amount | float | Tax applied (5% to 12% of subtotal) |
shipping_amount | float | Shipping cost based on method |
discount_amount | float | Discount applied (0–25% chance, rate 5% to 25%) |
coupon_code | String | A coupon code if a discount was applied |
notes | String | Optional delivery notes (e.g., "Leave at the door") |
total_amount | float | Final order total (subtotal + tax + shipping − discount) |
Healthcare¶
-
Hospital Entity: Entity for data around a hospital.
-
MedicalProcedure Entity: Entity for data around medical procedure.
-
MedicalDevice Entity: Entity for data around medical device.
-
Doctor Entity: Entity for data around a doctor.
-
Patient Entity: Entity for data around a patient.
Hospital Entity¶
The generated Hospital entities have the following data fields:
Property | Type | Description |
---|---|---|
hospital_id | String | A unique identifier for the hospital (e.g., HOSP-AB12CD34) |
name | String | Name of the hospital, generated based on city and state |
type | String | Type of hospital (General, Specialty, Teaching, etc.) |
departments | list | List of departments in the hospital |
services | list | List of services offered by the hospital |
bed_count | int | Number of beds available, based on hospital type |
staff_count | int | Total staff members, calculated from bed count and a staff ratio |
founding_year | int | Year the hospital was founded (within the last 150 years) |
accreditation | list | List of accreditations the hospital holds |
emergency_services | bool | Indicates if the hospital provides emergency services |
teaching_status | bool | Indicates if the hospital is a teaching hospital |
website | String | Generated website URL based on hospital name and dataset |
phone | String | Hospital's phone number |
String | Email address derived from website domain (e.g., [email protected]) |
Example usage:
1 2 3 4 5 6 7 8 9 |
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MedicalProcedure Entity¶
The generated MedicalProcedure entities have the following data fields:
Property | Type | Description |
---|---|---|
procedure_id | String | A unique identifier for the procedure (e.g., PROC-A1B2C3D4) |
procedure_code | String | A generated procedure code |
cpt_code | String | A random numeric CPT (Current Procedural Terminology) code |
name | String | Name of the medical procedure, generated contextually |
category | String | General category of the procedure (e.g., surgical, diagnostic) |
description | String | A full description based on the procedure’s attributes |
specialty | String | Medical specialty associated with the procedure (e.g., cardiology) |
duration_minutes | int | Estimated duration of the procedure in minutes |
cost | float | Estimated cost of the procedure in local currency |
requires_anesthesia | bool | Whether the procedure requires anesthesia |
is_surgical | bool | Whether the procedure is surgical |
is_diagnostic | bool | Whether the procedure is diagnostic in nature |
is_preventive | bool | Whether the procedure is preventive |
recovery_time_days | int | Recovery time required post-procedure, in days |
Example usage:
1 2 3 4 5 6 7 8 |
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MedicalDevice Entity¶
The generated MedicalDevice entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
device_id | String | A unique identifier for the medical device. |
device_type | String | The type/category of the medical device. |
manufacturer | String | The name of the manufacturer of the device. |
model_number | String | The model number assigned to the device. |
serial_number | String | The serial number of the device. |
manufacture_date | String | The date when the device was manufactured. |
expiration_date | String | The expiration date of the device. |
last_maintenance_date | String | The date when the device was last maintained. |
next_maintenance_date | String | The scheduled date for the next maintenance. |
status | String | The current operational status of the device. |
location | String | The location of the device within the facility. |
assigned_to | String | The name of the person to whom the device is assigned. |
specifications | dict | Key-value pairs detailing technical specifications. |
usage_logs | list | A list of usage log entries. |
maintenance_history | list | A list of past maintenance actions and their corresponding dates. |
Example usage:
1 2 3 4 5 6 7 8 |
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Doctor Entity¶
The generated Doctor entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
doctor_id | String | A unique identifier for the doctor (e.g., DOC-XXXXXXXX). |
npi_number | String | A 10-digit National Provider Identifier number. |
license_number | String | A formatted medical license number (e.g., AB-123456). |
given_name | String | The doctor's first name. |
family_name | String | The doctor's last name. |
full_name | String | The full name (first + last) of the doctor. |
gender | String | The doctor's gender. |
birthdate | datetime | The doctor's date of birth. |
age | Integer | The doctor's age in years. |
specialty | String | The medical specialty of the doctor (e.g., Cardiology, Pediatrics). |
medical_school | String | The name of the medical school attended by the doctor. |
graduation_year | int | The year the doctor graduated from medical school. |
years_of_experience | int | The number of years the doctor has been practicing. |
certifications | list | A list of the doctor’s medical certifications. |
accepting_new_patients | bool | Indicates if the doctor is currently accepting new patients. |
String | The doctor's email address. | |
phone | String | The doctor's phone number. |
Example usage:
1 2 3 4 5 6 7 |
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Patient Entity¶
The generated Patient entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
patient_id | String | A unique identifier for the patient (e.g., PAT-XXXXXXXX). |
medical_record_number | String | A unique medical record number (e.g., MRN-XXXXXXXX). |
ssn | String | Social Security Number in the format XXX-XX-XXXX. |
given_name | String | The patient’s first name. |
family_name | String | The patient’s last name. |
full_name | String | The full name (first + last) of the patient. |
gender | String | The patient's gender. |
birthdate | datetime | The patient’s date of birth. |
age | int | The patient’s age in years. |
blood_type | String | The patient’s blood type (e.g., A+, O-). |
height_cm | float | The patient’s height in centimeters. |
weight_kg | float | The patient’s weight in kilograms. |
bmi | float | The patient’s Body Mass Index. |
allergies | list | A list of the patient’s known allergies. |
medications | list | A list of medications the patient is taking. |
conditions | list | A list of medical conditions diagnosed in the patient. |
emergency_contact | dict | A dictionary of emergency contact info (name, phone, relationship). |
insurance_provider | String | The patient’s insurance provider name. |
insurance_policy_number | String | The patient’s insurance policy number (e.g., ABC-12345678). |
Example usage:
1 2 3 4 5 6 7 |
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Insurance¶
-
InsuranceCompany Entity: Entity for data around Insurance company information.
-
InsuranceProduct Entity: Entity for data around Insurance product information.
-
InsuranceCoverage Entity: Entity for data around Insurance coverage information.
-
InsurancePolicy Entity: Entity for data around Insurance policy information.
InsuranceCompany Entity¶
The generated InsuranceCompany entities have the following data fields:
Property Name | Type | Property Description |
---|---|---|
id | String | A unique identifier for the insurance company. |
name | String | The official name of the insurance company. |
code | String | A unique code assigned to the insurance company. |
founded_year | String | The year the insurance company was founded. |
headquarters | String | The location of the company's headquarters. |
website | String | The official website of the insurance company. |
Example usage:
1 2 3 4 5 6 7 |
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InsuranceProduct Entity¶
The generated InsuranceProduct entities have the following data fields:
Property Name | Type | Description |
---|---|---|
id | String | A unique identifier for the insurance product. |
type | String | The type/category of the insurance product (e.g., health, auto, life). |
code | String | A unique code assigned to the insurance product. |
description | String | A detailed description of the insurance product. |
Example usage:
1 2 3 4 5 6 7 |
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InsuranceCoverage Entity¶
The generated InsuranceCoverage entities have the following data fields:
Property Name | Type | Description |
---|---|---|
name | String | The name of the coverage (e.g., "Medical Expenses", "Accident Coverage"). |
code | String | A unique identifier for the coverage. |
product_code | String | The insurance product's code associated with this coverage. |
description | String | A detailed description of the coverage. |
min_coverage | String | The minimum coverage amount offered. |
max_coverage | String | The maximum coverage amount available. |
Example usage:
1 2 3 4 5 6 7 8 9 |
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InsurancePolicy Entity¶
The generated InsurancePolicy entities have the following data fields:
Property Name | Type | Description |
---|---|---|
id | String | A unique identifier for the insurance policy. |
company | InsuranceCompany | The insurance company issuing the policy. |
product | InsuranceProduct | The insurance product associated with this policy. |
policy_holder | Person | The person holding the insurance policy. |
premium | float | The premium amount for the policy. |
premium_frequency | String | The frequency of premium payments (e.g., "monthly", "yearly"). |
start_date | data | The policy's start date. |
end_date | data | The policy's end date. |
status | String | The policy status ("active", "inactive", or "cancelled"). |
created_date | datetime | The date and time when the policy was created. |
Example usage:
1 2 3 4 5 6 7 |
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Public Sector¶
-
AdministrationOffice Entity: Entity for data around administration office.
-
EducationalInstitution Entity: Entity for data around educational institution.
-
PoliceOfficer Entity: Entity for data around police officer.
AdministrationOffice¶
The generated AdministrationOffice entities have the following data fields:
Property Name | Type | Description |
---|---|---|
office_id | String | A unique identifier for the administration office. |
address | Address | The physical address of the office. |
name | String | The official name of the office. |
type | String | The type of administration office (e.g., municipal, federal). |
jurisdiction | String | The jurisdiction the office operates under. |
founding_year | int | The year the office was established. |
staff_count | int | The number of staff members working at the office. |
annual_budget | float | The annual budget allocated to the office (in dollars). |
hours_of_operation | dict | Office working hours mapped by day (e.g., "Monday": "9 AM - 5 PM"). |
website | String | The official website of the office. |
String | The contact email address of the office. | |
phone | String | The contact phone number of the office. |
services | list | A list of public services provided by the office. |
departments | list | A list of departments within the office. |
leadership | dict | Key leadership positions mapped to names (e.g., "Director": "John Doe"). |
Example usage:
1 2 3 4 5 6 7 8 |
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EducationalInstitution¶
The generated EducationalInstitution entities have the following data fields:
Property Name | Type | Description |
---|---|---|
institution_id | String | A unique identifier for the institution. |
name | String | The name of the institution, generated based on location and type. |
type | String | The type of institution (e.g., Public School, University, College). |
level | String | The education level (e.g., Elementary, High School, Undergraduate). |
founding_year | int | The year the institution was founded. |
student_count | int | The number of students enrolled. |
staff_count | int | The number of staff members. |
website | String | The institution's website URL. |
String | The institution's official email address. | |
phone | String | The institution's phone number. |
programs | list | A list of educational programs offered. |
accreditations | list | A list of accreditations the institution has received. |
facilities | list | A list of available facilities at the institution. |
address | Address | The institution's physical address. |
Example usage:
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PoliceOfficer¶
The generated PoliceOfficer entities have the following data fields:
Property Name | Type | Description |
---|---|---|
officer_id | String | Unique identifier for the police officer. |
badge_number | String | Unique badge number assigned to the officer. |
given_name | String | First name of the officer. |
family_name | String | Last name of the officer. |
full_name | String | Full name of the officer. |
gender | String | Gender of the officer. |
birthdate | String | Birthdate of the officer in YYYY-MM-DD format. |
age | int | Age of the officer in years. |
rank | String | Rank of the officer. |
department | String | Department where the officer works. |
unit | String | Specific unit assigned within the department. |
hire_date | String | Date the officer was hired in YYYY-MM-DD format. |
years_of_service | int | Number of years the officer has served. |
certifications | list | Certifications held by the officer. |
languages | list | Languages spoken by the officer. |
shift | String | Officer’s assigned shift schedule. |
String | Officer’s official email address. | |
phone | String | Contact phone number of the officer. |
address | Address | Address details of the officer. |
Example usage:
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BR¶
Provides objects specific to Brazil:
-
CNPJGenerator: Generates CNPJs (Cadastro Nacional da Pessoa JurÃdica)
-
CPFGenerator: Generates CPFs (Cadastro de Pessoa Fisica)
US¶
Provides objects specific for the United States of America:
- SSNGenerator: Generates Social Security Numbers
Faker¶
The faker package provides the Generator object with the Faker Library of Python.
- DataFakerGenerator : Generates data for many topics such as bank, color, currency, file, geo...
Because this Generator has many topics, each topic has many properties, you have to choose the Provider Name and put it
into the 'generator' as parameters (like this generator="DataFakerGenerator('faker_provider_name')"
).
Optionally you may want to define the Locale like this
generator="DataFakerGenerator('faker_provider_name', locale='de_AT')"
You can use the DataFakerGenerator like this:
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to get output similar to this:
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Supported topics:¶
FakerGenerator can generate data for multiple topics. Learn more about available providers in the Faker Docs.
Supported Locales¶
Locales may vary depending on the data you create and not available for all datasets.
Language | code |
---|---|
Bulgarian | bg |
Catalan | ca, ca_CAT, da_DK |
German | de, de_AT, de_CH |
English | en, en_AU, en_au_ocker, en_BORK, en_CA, en_GB, en_IND, en_MS, en_NEP, en_NG, en_NZ, en_PAK, en_SG, en_UG, en_US, en_ZA |
Spanish | es, es_MX |
Finnish | fi_FI |
French | fr |
Hungarian | hu |
Indonesian | in_ID |
Italian | it |
Japanese | ja |
Korean | ko |
Norwegian Bokmål | nb_NO |
Dutch | nl |
Polish | pl |
Portuguese | pt, pt_BR |
Russian | ru |
Slovak | sk |
Swedish | sv, sv_SE |
Turkish | tr |
Ukrainian | uk |
Vietnamese | vi |
Chinese | zh_CN, zh_TW |