Bloomer mock tool can generate random mock customised data for free. No limit on number of records that can be generated. Bloomer mock Bloomer mock 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, EXCEL, 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 No limit on data generation No limit on data generation AI integrated to generate attribute data AI integrated to generate attribute data Javascript dynamic generation of attribute value Javascript dynamic generation of attribute value Multiple export format supported — JSON, EXCEL, CSV, XML, HTML Multiple export format supported — JSON, EXCEL, CSV, XML, HTML Flat and Nested data support Flat and Nested data support Support existing json schema and json data upload Support existing json schema and json data upload Around 1.5K pre-defined data keys to choose Around 1.5K pre-defined data keys to choose User define data list supported User define data list supported No backend storage and data sharing 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
EXCEL
XML
HTML JSON CSV EXCEL 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 - 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.


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 categoriesb. AI based generated listc. User defined listd. Generate through javascript program


Data Type : 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. 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. Name of Attribute (Column name) 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 categoriesb. AI based generated listc. User defined listd. Generate through javascript program Value of Attribute (Column value) : Attribute value is randomly set from list of values.Example— name, country code, book title, actors etc. Value of Attribute (Column value) Example Attribute values can be picked -a. Based on pre defined list of around 1.5 K categoriesb. AI based generated listc. User defined listd. Generate through javascript program a. Based on pre defined list of around 1.5 K categoriesb. AI based generated listc. User defined listd. Generate through javascript program Data Type : Data Type : Data Type : Data type define the type of generated data for attribute or column. For most people stringdata type is sufficient for data production. string string 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”] a. string b. number c. boolean d. object e. array : 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 attributeEdit — Edit button is used to edit selected attributeDelete — Delete selected attributeSave — Save currently edited attributeMore — More button provide extra configuration based on data type Add — Add button is used to add child attributeEdit — Edit button is used to edit selected attributeDelete — Delete selected attributeSave — Save currently edited attributeMore — More button provide extra configuration based on data type Add — Add button is used to add child attributeEdit — Edit button is used to edit selected attributeDelete — Delete selected attributeSave — Save currently edited attributeMore — More button provide extra configuration based on data type 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. Generate Generate 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 Generate CSV with 2 columns — name and age name : characters data type


age : number data type name : characters data type name : characters data type age : number 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 2 attributes to data definition screen. For first attribute set attribute name as name and for second attribute set name as age name age 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 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 Artist → Names 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. 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. 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. Preview screen will show preview of 10 records Preview screen will show preview of 10 records 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. 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 rows to be generated and data format as CSV.Click on Generate button to generate csv data. CSV data is downloaded to the Downloads folder. CSV data is downloaded to the Downloads folder. 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 website - https://bloomer-mock.org https://bloomer-mock.org

This Tool Unlocks Unlimited Free Data for Testing, Prototyping, and Demos

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

5 Ways to Store Market Data: CSV, SQLite, Postgres, Mongo, Arctic

Everything I Learned as a Software Developer While Creating my Product

Exporting Data to Fit Your Needs

From CSV to Buxfer: an unexpected journey — Cleaner

From CSV to Buxfer: an unexpected journey — Introduction

How to Export Your Data from WordPress

5 Ways to Store Market Data: CSV, SQLite, Postgres, Mongo, Arctic

Everything I Learned as a Software Developer While Creating my Product

Exporting Data to Fit Your Needs

From CSV to Buxfer: an unexpected journey — Cleaner

From CSV to Buxfer: an unexpected journey — Introduction

How to Export Your Data from WordPress

Light-Mode

Classic

Newspaper

Minty

Dark-Mode

Neon Noir

Minty

HN StartUps