Today I am writing about faking data again using ts-api-faker . Usually we pass this kind of data to faker
[
{
"name": "name.firstName",
"surname": "name.lastName",
"mail": "internet.email",
"profilePhoto": "internet.avatar",
"animalPhoto": "image.cat"
},
{
"name": "name.firstName",
"surname": "name.lastName",
"mail": "internet.email",
"profilePhoto": "internet.avatar",
"animalPhoto": "image.dog"
}
]
and then we receive faked data
[
{
"name": "Van",
"surname": "Veum",
"mail": "Corbin.Fritsch49@gmail.com",
"profilePhoto": "https://s3.amazonaws.com/uifaces/faces/twitter/pixage/128.jpg",
"animalPhoto": "https://source.unsplash.com/200x200/?cat"
},
{
"name": "Serena",
"surname": "Wilderman",
"mail": "Mariam_Thiel@hotmail.com",
"profilePhoto": "https://s3.amazonaws.com/uifaces/faces/twitter/imcoding/128.jpg",
"animalPhoto": "https://source.unsplash.com/200x200/?dog"
}
]
It works perfect but... Usually a schema looks like this.
[
{
"name": "String",
"surname": "String",
"mail": "String",
"profilePhoto": "String",
"animalPhoto": "String"
}
]
The answer from faker is inappropriate then
[
{
"name": "atque",
"surname": "eos",
"mail": "voluptas",
"profilePhoto": "similique",
"animalPhoto": "earum"
}
]
What if you use levensthein algorithm on keys of values and transform values to the closest to key name option?
Again we pass
[
{
"name": "String",
"surname": "String",
"mail": "String",
"profilePhoto": "String",
"animalPhoto": "String"
}
]
Voila, we get the correct faker structure.
[
{
"name": "Edgar",
"surname": "Alyce64",
"mail": "Eusebio.Gottlieb@yahoo.com",
"profilePhoto": "https://source.unsplash.com/200x200/?profile",
"animalPhoto": "https://source.unsplash.com/200x200/?animal"
}
]
I've just added this feature to my repo ts-api-faker
Feel free to contribute and extend this library functionality. If you support me and this idea please star this repo to help me get more contributors and extend ts-api-faker library.
In future we can add machine learning to this and get ultimate intelligent faker for our apis and databases :)
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