DEV Community: Sadhna Mishra

FAQ — Bloomer Mock Data Generator

Sadhna Mishra — Sun, 15 Dec 2024 06:25:41 +0000

Listing out frequently asked questions around bloomer mock data generator site.

Question: How to generate id for records ?
Answer: Two types of id generation is supported : Row Number and UUID

a. Row Number — Row number assign unique row number to each record in sequence of generation.
b. UUID — UUID assign unique random uuid to each record in output file.

To select id, open attribute value selection screen and in search box type — id. In property list click on id which will list — UUID, Row-number.

Question: How to save in-progress work ?
Answer: To save data definition click on [+] icon placed at bottom right screen.
Click on Download Schema to save the data definition.

To restore data definition later, click on Upload Schema. All fields will be visible in data definition screen and preview pane will show 10 preview records.

Question: Can I provide custom list of values for an attribute ?
Answer: Yes you can provide custom list of values.
a. Click on more icon for the selected attribute
b. Provide custom values in Override Attributes text box
c. Click on Save

Custom Attribute Values

Question: Advanced function to transform values such as lowerCase, upperCase
Answer: To transform output data javascript functions can be used, provided in Advanced Section.
Example — To transform attribute to upper case
a. Click on more icon for the selected attribute
b. Click on Advanced : Javascript Generation checkbox to open javascript code panel
c. In code panel type value.toUpperCase()
d. Click on Save button.
e. Preview screen will show selected attribute value in upper case.

Advanced : Javascript Function

Above function is applied to each value, be sure to click on Apply per row

Question: Generate attribute value through Generative AI
Attribute values can be generated from AI. To generate value through AI -
a. Open attribute value selection screen.
b. Click on robot icon in the top search bar
c. Let’s say you want to generate list of cities in Australia. In search bar type cities in Australia.
d. Preview will show generated values for the search

Question: How many file output formats supported ?
Answer: Currently four output formats are supported — JSON, CSV, XML and HTML.

Bottom of screen contains output format selection button. Click on Type select button to select desired output format.

Question: Submit suggestion or issue
Answer: To submit any suggestion, improvement or issue send email to mail@bloomer-mock.org

Link to Bloomer mock functionalities - Bloomer Mock Functionalities
Link to website - Bloomer mock

Advanced mock generation function.

Sadhna Mishra — Tue, 03 Dec 2024 11:34:48 +0000

Realistic data Generation Using Bloomer Mock

Sadhna Mishra ・ Nov 16

#mock #data #json #csv

Realistic data Generation Using Bloomer Mock

Sadhna Mishra — Sat, 16 Nov 2024 15:33:07 +0000

Bloomer mock tool can generate random mock customised data for free. No limit on number of records that can be generated.

Mock random data can be used for variety of purpose such as showing realistic data to customers, performance testing, data analytics, for fun etc.

Features

No limit on data generation

AI integrated to generate attribute data

Javascript dynamic generation of attribute value

Multiple export format supported — JSON, CSV, XML, HTML

Flat and Nested data support

Support existing json schema and json data upload

Around 1.5K pre-defined data keys to choose

User define data list supported

No backend storage and data sharing

Tool provide intuitive UI to create and generate plain as well as nested data. Generation screen is divided into two parts left pane is used to define data structure which provides a tree like structure that is well suited for hierarchical as well as flat data. Right pane shows preview of the data that will be generated.

Data export format supported

JSON
CSV
XML
HTML

Let’s quickly jump over to steps required to generate the data with our own customisation.

Generation Screen

To generate data user has to define attributes(columns in CSV), each attribute consist of following -

Generate Screen

1. Name of Attribute (Column name) :
Specify required attribute name for data field. In case of JSON this corresponds to json field name and in case of CSV format attribute name corresponds to column name.

2. Value of Attribute (Column value) :
Attribute value is randomly set from list of values. Example — name, country code, book title, actors etc.
Attribute values can be picked -
a. Based on pre defined list of around 1.5 K categories
b. AI based generated list
c. User defined list
d. Generate through javascript program

3. Data Type :
Data type define the type of generated data for attribute or column. For most people string data type is sufficient for data production.
Other data type give granular control for generation of data for JSON format.
Different data types supported :
a. string : Sufficient for most use cases. Example — “West Cherry”, “Law”, “1”, “2”, “West Cherry 1.2”, “true”, “false” etc.
b. number : Number data type is specifically used for generation of any number which include integer, decimal etc. Example — 1, 2, 2.6, -2 etc.
c. boolean : Boolean data type is used to define either true or false value.
d. object **: Object data type is used for defining nested attribute (attribute that contains child attributes).
**e. array : Array data type is used to define list of values. Example — [“West Cherry”, “Law”]

Controls Buttons

Generation screen provide few controls button that help in defining attributes such as add, delete, edit and more button.

Add — Add button is used to add child attribute

Edit — Edit button is used to edit selected attribute

Delete — Delete selected attribute

Save — Save currently edited attribute

More — More button provide extra configuration based on data type

Control Buttons

Once data structure is defined and preview of sample data generated in preview screen looks good, simply provide number of records to be generated and data output format in the bottom left of screen.

Finally click on Generate button to generate data based on selected provided attributes.

Data Generation Example

Let’s quickly go through all the step to generate basic 2 column CSV.

Generate CSV with 2 columns — name and age

name : characters data type

age : number data type

Steps :

Add 2 attributes to data definition screen. For first attribute set attribute name as name and for second attribute set name as age

Add Attribute

Click on save icon
Select value for both the attributes by clicking on value selection box
Selection box list pre-defined values to choose from list of thousand of attributes. For this example let’s choose Artist → Names

Attribute Selection

For age attribute let’s select define custom values. To create custom values click on more icon.

Add minimum and maximum value, in case of age let’s select minimum as 10 and maximum as 80 to set random value for age between 10 and 80.

Min and Max Value

Preview screen will show preview of 10 records

Preview Screen

Now it’s time to generate the data. Select number of rows to be generated and data format as CSV. Click on Generate button to generate CSV data.

Select Number of records to generate

CSV data is downloaded to the Downloads folder.

CSV Output

Customize as per your wish. Bloomer mock also provide advanced feature such AI generated list, user defined custom list and if you are a developer you can even use javascript to generate and modify output.
I will create separate article on advanced features around generation and other capabilities.

Feel free to provide your input, suggestions and feedback in the comment section.
Enjoy, hope this tool help you in your data generation needs. Have fun generating data! 🚀

Link to FAQ - Bloomer mock FAQ
Link to website - Bloomer mock Website