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Quickstart - Skill Enrichment API

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Getting Started

In order to use our Skill Enrichment API, you must have an active API key. You can look up your API key by logging into our self-serve dashboard and going to the API Keys section.

👍

Need an API Key?

If you don't have an API key, you can easily create one by signing up for a self-serve account. Check out our Self-Serve Quickstart Guide, which walks you through the sign-up process as well as shows you how to use the self-serve API dashboard.

Simple Example

As mentioned in the Overview, the Skill Enrichment API is a means of performing a one-to-one match of a skill with those included in our Skill Dataset. In order to use the Skill Enrichment API, you will need the skill that you want to look up.

Here's a quick example that demonstrates retrieving a record with a skill of ai:

# See https://github.com/peopledatalabs/peopledatalabs-python
from peopledatalabs import PDLPY

# Create a client, specifying your API key
CLIENT = PDLPY(
    api_key="YOUR API KEY",
)

# Create a parameters JSON object
QUERY_STRING = {"skill": "ai"}

# Pass the parameters object to the Skill Enrichment API
response = CLIENT.skill(**QUERY_STRING)

# Print the API response
print(response.text)

curl -X GET -G \
  'https://api.peopledatalabs.com/v5/skill/enrich' \
  -H 'X-Api-Key: YOUR API KEY' \
  --data-urlencode 'skill=ai'

// See https://github.com/peopledatalabs/peopledatalabs-js
import PDLJS from 'peopledatalabs';

// Create a client, specifying your API key
const PDLJSClient = new PDLJS({ apiKey: "YOUR API KEY" });

// Create a parameters JSON object
const queryString = {skill: "ai"}

// Pass the parameters object to the Skill API
PDLJSClient.skill(queryString).then((data) => {
    // Print the API response
    console.log(data);
}).catch((error) => {
    console.log(error);
});

# See https://github.com/peopledatalabs/peopledatalabs-ruby
require 'peopledatalabs'

# Set your API key
Peopledatalabs.api_key = 'YOUR API KEY'

# Pass parameters to the Skill API
response = Peopledatalabs::Skill.retrieve("skill": "ai")

# Print the API response
puts response

package main

import (
    "fmt"
    "context"
)

// See https://github.com/peopledatalabs/peopledatalabs-go
import (
    pdl "github.com/peopledatalabs/peopledatalabs-go"
    pdlmodel "github.com/peopledatalabs/peopledatalabs-go/model"
)

func main() {
    // Set your API key
    apiKey := "YOUR API KEY"
    // Set API key as environmental variable
    // apiKey := os.Getenv("API_KEY")

    // Create a client, specifying your API key
    client := pdl.New(apiKey)
    
    // Create a parameters JSON object
    queryString := pdlmodel.SkillBaseParams{Skill: "ai"}
    
    params := pdlmodel.SkillParams{
        SkillBaseParams: queryString,
    }
    
    // Pass the parameters object to the Skill API
    response, err := client.Skill(context.Background(), params)
    // Check for successful response
    if err == nil {
        // Print the API response
        fmt.Println(response)
    }  
}

import requests

# Set your API key
API_KEY = "YOUR API KEY"

# Set the Skill Enrichment API URL
PDL_URL = "https://api.peopledatalabs.com/v5/skill/enrich"

# Create a parameters JSON object
QUERY_STRING = {"skill": "ai"}

# Set headers
HEADERS = {
    'accept': "application/json",
    'content-type': "application/json",
    'x-api-key': API_KEY
}

# Pass the parameters object to the Skill Enrichment API
response = requests.request("GET", PDL_URL, headers=HEADERS, params=QUERY_STRING)

# Print the API response
print(response.text)

The API returns a record like the one below if the skill that you passed it exists in our dataset:

{
  "cleaned_skill": "ai",
  "similar_skills": [
    "machine learning",
    "artificial intelligence",
    "deep learning",
    "data science",
    "iot"
  ],
  "relevant_job_titles": [
    "data scientist",
    "software engineer",
    "senior data scientist",
    "chief technology officer",
    "senior software engineer"
  ]
}

If you don't get this response, check out our Errors page for more information.

Updated about 1 month ago