Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/human-37/h37-fakestream
H37 Fakestream synthetic data generation package
https://github.com/human-37/h37-fakestream
Last synced: 2 months ago
JSON representation
H37 Fakestream synthetic data generation package
- Host: GitHub
- URL: https://github.com/human-37/h37-fakestream
- Owner: human-37
- Created: 2023-11-30T15:28:42.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2023-12-01T11:44:00.000Z (7 months ago)
- Last Synced: 2024-01-21T14:48:47.927Z (5 months ago)
- Language: JavaScript
- Size: 7.81 KB
- Stars: 6
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Lists
- awesome-faker - h37-fakestream - h37-fakestream is a package that allows you to generate synthetic data for your Segment data pipeline. (Projects using `@faker-js/faker`)
README
# Human37 Fakestream Package
Authors -- Maxime Wauthy & Glenn Vanderlinden @Human37
## Purpose & Architecture
The Fakestream package is developed in order to generate synthetic data using [Faker](https://fakerjs.dev/) and send it to [Segment](https://segment.com), which in turn can dispatch it to final destinations. We have chosen to send it to Segment as Segment can act as a event pipeline from which data can then be distributed towards a number of tools for testing, training and demo applications. One SDK to rule them all if you will.
Out of the box the script will generate event for the following customer journey. To modify see the section on event creation.
## Demo and application documentation
* [Unlocking the Power of Synthetic Data – A short introduction](https://www.human37.com/post/unlocking-the-power-of-synthetic-data-a-short-introduction)
* [Synthetic data - An introduction to Faker.js](https://www.youtube.com/watch?v=kEnZslyQaS4&list=PL4YD95ENcSNTRAW5k65PDrzzQd2OsJs_c&ab_channel=Human37)
* [Synthetic data - A practical application](https://www.youtube.com/watch?v=JSyif515NFU&list=PL4YD95ENcSNTRAW5k65PDrzzQd2OsJs_c&index=2&ab_channel=Human37)
## Installation
On MacOS - Go to your folder location in which the script is stored using terminal. Then execute the following:
To install the Faker.js library:
```sh
npm install @faker-js/faker --save-dev
```
To install the Segment Node library:
```sh
npm install @segment/analytics-node
```
## Configuration
### Segment write key
Insert your Segment write key.
```sh
const analytics = new Analytics({
writeKey: "{{INSERT KEY HERE}}",
});
```
### User count
Define the number of user you would like to be generated.
```sh
const numUsers = 10;
```
### Event creation
Create events in the templated structure.
```sh
{
name: "CTA Selected",
properties: {
cta_type: ["Sign-up Now", "Sign-up For Free"],
},
probability: 1.0,
}
```
Where
- name -- corresponds to the event name
- Properties -- properties contains the relevant properties linked to an event. The value can be an array of possible values you wish to eventually send with the event payload. The value which will eventually be chosen at random.
- Probability -- Indicates the chance that this event will be executes where 1.0 represents 100% chance.
### User trait generation
Add traits where needed
```sh
function generateUser() {
const userId = faker.string.uuid();
const name = faker.person.fullName();
const userTraits = {
company: faker.company.name(),
name: name,
email: `${name.split(" ")[1].toLowerCase()}${Math.round(
Math.random() * 100
)}@fakeHuman.37`,
};
return { userId, userTraits };
}
```
## Running the script
In your IDE hit run.
In terminal - navigate to the root folder and run:
```sh
node FakeStream.js
```