mockaroo-tool

Mockaroo - Test data generation tool.
Mockaroo - Test data generation tool.

Test data generation service with predefined real world datasets.
Free service to download 1000 records without signup/subscription.
Supports multiple downloadable data formats and complex datatypes.
Provides AI powered data generation by analysing the given prompts.
Homepage: Mockaroo
Contents
  1. Test Data Generation
  2. Numbers from Range
  3. Random values from the given Set
  4. Credit card type number
  5. Complex(Nested) Types - JSON Object
  6. Complex(Nested) Types - JSON Array
  7. Complex(Nested) Type example
1. Test Data Generation

     1. Select the required columns in the Schema window.
     2. Choose the required column type or select from real world datasets.
     3. Preview and generate the data.

2. Custom - Numerical values in the Range

     1. Input field name as salary and type as number
     2. Supply min and max values and choose decimals points.
     3. Choose the blank records percentage of generated records.
         If you give 5% as blank, for every 100 records generated, 5 will be blank for the selected column
     4. Preview and generate the data.

3. Random values in the given values

     1. Rename column name and choose type related to string/name.
     2. Click on Σ(formula) and give below text.
     randval = random(1,4)
     if randval == 1 then "A1_."
     elsif randval == 2 then "B2@/"
     elsif randval == 3 then "C3*+"
     elsif randval == 4 then "D4#="
     end
     3. Preview and generate the data.

4. Credit card type number

     1. Rename column name and choose type as character sequence.
    
     2. Enter below text in the options.
     ####-####-####-####
     Eg. 1234-3453-5353-5352
    
     Supported types:
     Use "#" for a random digit.
     Use "@" for a random lower case letter.
     Use "^" for a random upper case letter.
     Use "*" for a random digit or letter.
     Use "$" for a random digit or lower case letter.
     Use "%" for a random digit or upper case letter.
     Any other character will be included in the output.
    
     3. Preview and generate the data.

5. Complex(Nested) Types - JSON Object

     1. Create 3 columns with common prefix following with dot(.) and then column name
     Eg. id - rownumber type,address.city - city type, address.state - state type, address.country - country type
    
     2. Choose export format as JSON and preview the data.
     Eg. Data generated
     [{
     "id": 1,
     "address": {
     "city": "Montfort-sur-Meu",
     "state": "Bretagne",
     "country": "France"
     }
     }, {
     "id": 2,
     "address": {
     "city": "Laau",
     "state": null,
     "country": "Indonesia"
     }
     }]

6. Complex(Nested) Types - JSON Array

     1. Create 6 columns with below names and types. Use common prefix following with dot(.) and then column name for the nested column
    
     Eg. Columns: a. id - rownumber type, b. location - city type, c. departments - JSON Array type,
     d. departments.name - department(corporate) name type, e. departments.hod - first name type, f. departments.contact - email address type
    
     2. Choose export format as JSON and preview the data.
     Data generated:
     [{
     "id": 1,
     "location": "Alice",
     "departments": [
     {
     "name": "Research and Development",
     "hod": "Karrah",
     "contact": "kplows0@addtoany.com"
     },
     {
     "name": "Research and Development",
     "hod": "Coriss",
     "contact": "cissatt1@google.ca"
     }
     ]
     }, {
     "id": 2,
     "location": "Tromsø",
     "departments": [
     {
     "name": "Training",
     "hod": "Kenna",
     "contact": "kstading0@soundcloud.com"
     },
     {
     "name": "Engineering",
     "hod": "Pepita",
     "contact": "pevamy1@ask.com"
     }
     ]
     }

7. Another Complex(Nested) Type example - JSON Array inside a JSON Object.

     1. Create 6 columns with below names and types. Use common prefix following with dot(.) and then column name for the nested column
     id - row number type
     result.type - drug name(generic) type
     result.samples - JSON Array - min elements: 1 - max elements: 3
     result.samples.testvalue - Number type - Min: 1 - Max: 100
     result.samples.date - Datetime type - Min: 10/17/2023 - Max: 10/17/2024 - format: yyyy-mm-dd
     result.samples.success - boolean type - depends on testvalue - Σ(formula): if testvalue >= 50 then true else false end
    
     2. Preview to generate data and download
     Eg. records
     [{
     "id": 1,
     "result": {
     "type": "Ziprasidone hydrochloride",
     "samples": [
     {
     "testvalue": 45.13,
     "date": "2024-03-12",
     "success": false
     },
     {
     "testvalue": 33.21,
     "date": "2024-02-02",
     "success": false
     }
     ]
     }
     }, {
     "id": 2,
     "result": {
     "type": "Naproxen",
     "samples": [
     {
     "testvalue": 39.85,
     "date": "2024-08-20",
     "success": false
     },
     {
     "testvalue": 61.07,
     "date": "2024-03-24",
     "success": true
     }
     ]
     }
     }, {
     "id": 3,
     "result": {
     "type": "Nifedipine",
     "samples": [
     {
     "testvalue": 76.74,
     "date": "2024-04-14",
     "success": true
     },
     {
     "testvalue": 34.63,
     "date": "2024-03-11",
     "success": false
     },
     {
     "testvalue": 88.04,
     "date": "2024-04-11",
     "success": true
     }
     ]
     }
     }]

Compiled on THURSDAY, 17-OCTOBER-2024, 08:57:30 PM IST

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