Reference example
# Fixed reference example. Playground inputs do not update this sample.
curl --request POST \
--url https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"email": "john.doe@example.com"
}'curl --request POST \
--url https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"email": "john.doe@example.com"
}
'import requests
url = "https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data"
payload = { "email": "john.doe@example.com" }
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({email: 'john.doe@example.com'})
};
fetch('https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'email' => 'john.doe@example.com'
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data"
payload := strings.NewReader("{\n \"email\": \"john.doe@example.com\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"email\": \"john.doe@example.com\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"email\": \"john.doe@example.com\"\n}"
response = http.request(request)
puts response.read_body{
"data": {
"id": "<string>",
"sex": "<string>",
"emails": true,
"phones": [
{
"number": "<string>",
"last_seen": "<string>",
"first_seen": "<string>",
"num_sources": 123
}
],
"skills": [
"<string>"
],
"regions": true,
"summary": "<string>",
"headline": "<string>",
"industry": "<string>",
"profiles": [
{
"id": "<string>",
"url": "<string>",
"network": "<string>",
"username": "<string>",
"last_seen": "<string>",
"first_seen": "<string>",
"num_sources": 123
}
],
"countries": [
"<string>"
],
"education": [
{
"gpa": 123,
"raw": [
"<string>"
],
"majors": [
"<string>"
],
"minors": [
"<string>"
],
"school": {
"id": "<string>",
"raw": [
"<string>"
],
"name": "<string>",
"type": "<string>",
"domain": "<string>",
"website": "<string>",
"location": {
"geo": "<string>",
"name": "<string>",
"metro": "<string>",
"region": "<string>",
"country": "<string>",
"locality": "<string>",
"continent": "<string>",
"last_seen": "<string>",
"first_seen": "<string>",
"num_sources": 123,
"postal_code": "<string>",
"address_line_2": "<string>",
"street_address": "<string>"
},
"linkedin_id": "<string>",
"twitter_url": "<string>",
"facebook_url": "<string>",
"linkedin_url": "<string>"
},
"degrees": [
"<string>"
],
"summary": "<string>",
"end_date": "<string>",
"start_date": "<string>"
}
],
"full_name": "<string>",
"interests": [
"<string>"
],
"job_title": "<string>",
"languages": [
{
"name": "<string>",
"proficiency": 123
}
],
"last_name": "<string>",
"last_seen": "<string>",
"birth_date": true,
"birth_year": true,
"experience": [
{
"title": {
"raw": [
"<string>"
],
"name": "<string>",
"role": "<string>",
"class": "<string>",
"levels": [
"<string>"
],
"sub_role": "<string>"
},
"company": {
"id": "<string>",
"raw": [
"<string>"
],
"name": "<string>",
"size": "<string>",
"type": "<string>",
"ticker": "<string>",
"founded": 123,
"website": "<string>",
"industry": "<string>",
"location": {
"geo": "<string>",
"name": "<string>",
"metro": "<string>",
"region": "<string>",
"country": "<string>",
"locality": "<string>",
"continent": "<string>",
"last_seen": "<string>",
"first_seen": "<string>",
"num_sources": 123,
"postal_code": "<string>",
"address_line_2": "<string>",
"street_address": "<string>"
},
"fuzzy_match": true,
"industry_v2": "<string>",
"linkedin_id": "<string>",
"twitter_url": "<string>",
"facebook_url": "<string>",
"linkedin_url": "<string>"
},
"summary": "<string>",
"end_date": "<string>",
"last_seen": "<string>",
"first_seen": "<string>",
"is_primary": true,
"start_date": "<string>",
"num_sources": 123,
"location_names": [
"<string>"
]
}
],
"first_name": "<string>",
"first_seen": "<string>",
"github_url": "<string>",
"work_email": true,
"facebook_id": "<string>",
"job_history": [
"<unknown>"
],
"job_summary": "<string>",
"linkedin_id": "<string>",
"middle_name": "<string>",
"num_records": 123,
"num_sources": 123,
"twitter_url": "<string>",
"facebook_url": "<string>",
"last_initial": "<string>",
"linkedin_url": "<string>",
"location_geo": true,
"mobile_phone": true,
"name_aliases": [
"<string>"
],
"first_initial": "<string>",
"job_onet_code": "<string>",
"location_name": true,
"phone_numbers": true,
"certifications": [
{
"name": "<string>",
"end_date": "<string>",
"start_date": "<string>",
"organization": "<string>"
}
],
"job_company_id": "<string>",
"job_start_date": "<string>",
"job_title_role": "<string>",
"location_metro": true,
"location_names": true,
"middle_initial": "<string>",
"dataset_version": "<string>",
"github_username": "<string>",
"inferred_salary": "<string>",
"job_title_class": "<string>",
"location_region": true,
"personal_emails": true,
"possible_emails": [
"<unknown>"
],
"possible_phones": [
"<unknown>"
],
"facebook_friends": 123,
"job_company_name": "<string>",
"job_company_size": "<string>",
"job_company_type": "<string>",
"job_last_changed": "<string>",
"job_title_levels": [
"<string>"
],
"location_country": "<string>",
"street_addresses": true,
"twitter_username": "<string>",
"facebook_username": "<string>",
"job_last_verified": "<string>",
"linkedin_username": "<string>",
"location_locality": true,
"possible_profiles": [
"<unknown>"
],
"job_company_ticker": "<string>",
"job_title_sub_role": "<string>",
"location_continent": "<string>",
"job_company_founded": 123,
"job_company_website": "<string>",
"job_company_industry": "<string>",
"job_onet_major_group": "<string>",
"job_onet_minor_group": "<string>",
"linkedin_connections": 123,
"location_postal_code": true,
"possible_birth_dates": [
"<string>"
],
"location_last_updated": "<string>",
"job_company_industry_v2": "<string>",
"job_company_linkedin_id": "<string>",
"job_company_twitter_url": "<string>",
"location_address_line_2": "<string>",
"location_street_address": true,
"possible_location_names": [
"<string>"
],
"job_company_facebook_url": "<string>",
"job_company_linkedin_url": "<string>",
"job_company_location_geo": "<string>",
"inferred_years_experience": 123,
"job_company_location_name": "<string>",
"job_onet_broad_occupation": "<string>",
"possible_street_addresses": [
"<unknown>"
],
"job_company_employee_count": 123,
"job_company_location_metro": "<string>",
"recommended_personal_email": true,
"job_company_location_region": "<string>",
"job_company_inferred_revenue": "<string>",
"job_company_location_country": "<string>",
"job_onet_specific_occupation": "<string>",
"job_company_location_locality": "<string>",
"job_company_location_continent": "<string>",
"job_company_location_postal_code": "<string>",
"job_company_total_funding_raised": 123,
"job_company_location_address_line_2": "<string>",
"job_company_location_street_address": "<string>",
"job_onet_specific_occupation_detail": "<string>",
"job_company_12mo_employee_growth_rate": 123
},
"status": 123,
"likelihood": 123,
"matched": [
"<string>"
]
}People Data Labs
Enrich person data
<!-- aisa-pricing:start -->
按用量计费；默认请求预估费用：$0.2803 USD（不是固定价格）。 声明的单位费率：每 provider_credit $0.000001 USD。 最终费用以账户适用价格及实际结算为准。
<!-- aisa-pricing:end -->
POST
https://api.aisa.one
/
apis
/
v1
/
people-data-labs
/
enrich-person-data
Reference example
# Fixed reference example. Playground inputs do not update this sample.
curl --request POST \
--url https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"email": "john.doe@example.com"
}'curl --request POST \
--url https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"email": "john.doe@example.com"
}
'import requests
url = "https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data"
payload = { "email": "john.doe@example.com" }
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({email: 'john.doe@example.com'})
};
fetch('https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'email' => 'john.doe@example.com'
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data"
payload := strings.NewReader("{\n \"email\": \"john.doe@example.com\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"email\": \"john.doe@example.com\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"email\": \"john.doe@example.com\"\n}"
response = http.request(request)
puts response.read_body{
"data": {
"id": "<string>",
"sex": "<string>",
"emails": true,
"phones": [
{
"number": "<string>",
"last_seen": "<string>",
"first_seen": "<string>",
"num_sources": 123
}
],
"skills": [
"<string>"
],
"regions": true,
"summary": "<string>",
"headline": "<string>",
"industry": "<string>",
"profiles": [
{
"id": "<string>",
"url": "<string>",
"network": "<string>",
"username": "<string>",
"last_seen": "<string>",
"first_seen": "<string>",
"num_sources": 123
}
],
"countries": [
"<string>"
],
"education": [
{
"gpa": 123,
"raw": [
"<string>"
],
"majors": [
"<string>"
],
"minors": [
"<string>"
],
"school": {
"id": "<string>",
"raw": [
"<string>"
],
"name": "<string>",
"type": "<string>",
"domain": "<string>",
"website": "<string>",
"location": {
"geo": "<string>",
"name": "<string>",
"metro": "<string>",
"region": "<string>",
"country": "<string>",
"locality": "<string>",
"continent": "<string>",
"last_seen": "<string>",
"first_seen": "<string>",
"num_sources": 123,
"postal_code": "<string>",
"address_line_2": "<string>",
"street_address": "<string>"
},
"linkedin_id": "<string>",
"twitter_url": "<string>",
"facebook_url": "<string>",
"linkedin_url": "<string>"
},
"degrees": [
"<string>"
],
"summary": "<string>",
"end_date": "<string>",
"start_date": "<string>"
}
],
"full_name": "<string>",
"interests": [
"<string>"
],
"job_title": "<string>",
"languages": [
{
"name": "<string>",
"proficiency": 123
}
],
"last_name": "<string>",
"last_seen": "<string>",
"birth_date": true,
"birth_year": true,
"experience": [
{
"title": {
"raw": [
"<string>"
],
"name": "<string>",
"role": "<string>",
"class": "<string>",
"levels": [
"<string>"
],
"sub_role": "<string>"
},
"company": {
"id": "<string>",
"raw": [
"<string>"
],
"name": "<string>",
"size": "<string>",
"type": "<string>",
"ticker": "<string>",
"founded": 123,
"website": "<string>",
"industry": "<string>",
"location": {
"geo": "<string>",
"name": "<string>",
"metro": "<string>",
"region": "<string>",
"country": "<string>",
"locality": "<string>",
"continent": "<string>",
"last_seen": "<string>",
"first_seen": "<string>",
"num_sources": 123,
"postal_code": "<string>",
"address_line_2": "<string>",
"street_address": "<string>"
},
"fuzzy_match": true,
"industry_v2": "<string>",
"linkedin_id": "<string>",
"twitter_url": "<string>",
"facebook_url": "<string>",
"linkedin_url": "<string>"
},
"summary": "<string>",
"end_date": "<string>",
"last_seen": "<string>",
"first_seen": "<string>",
"is_primary": true,
"start_date": "<string>",
"num_sources": 123,
"location_names": [
"<string>"
]
}
],
"first_name": "<string>",
"first_seen": "<string>",
"github_url": "<string>",
"work_email": true,
"facebook_id": "<string>",
"job_history": [
"<unknown>"
],
"job_summary": "<string>",
"linkedin_id": "<string>",
"middle_name": "<string>",
"num_records": 123,
"num_sources": 123,
"twitter_url": "<string>",
"facebook_url": "<string>",
"last_initial": "<string>",
"linkedin_url": "<string>",
"location_geo": true,
"mobile_phone": true,
"name_aliases": [
"<string>"
],
"first_initial": "<string>",
"job_onet_code": "<string>",
"location_name": true,
"phone_numbers": true,
"certifications": [
{
"name": "<string>",
"end_date": "<string>",
"start_date": "<string>",
"organization": "<string>"
}
],
"job_company_id": "<string>",
"job_start_date": "<string>",
"job_title_role": "<string>",
"location_metro": true,
"location_names": true,
"middle_initial": "<string>",
"dataset_version": "<string>",
"github_username": "<string>",
"inferred_salary": "<string>",
"job_title_class": "<string>",
"location_region": true,
"personal_emails": true,
"possible_emails": [
"<unknown>"
],
"possible_phones": [
"<unknown>"
],
"facebook_friends": 123,
"job_company_name": "<string>",
"job_company_size": "<string>",
"job_company_type": "<string>",
"job_last_changed": "<string>",
"job_title_levels": [
"<string>"
],
"location_country": "<string>",
"street_addresses": true,
"twitter_username": "<string>",
"facebook_username": "<string>",
"job_last_verified": "<string>",
"linkedin_username": "<string>",
"location_locality": true,
"possible_profiles": [
"<unknown>"
],
"job_company_ticker": "<string>",
"job_title_sub_role": "<string>",
"location_continent": "<string>",
"job_company_founded": 123,
"job_company_website": "<string>",
"job_company_industry": "<string>",
"job_onet_major_group": "<string>",
"job_onet_minor_group": "<string>",
"linkedin_connections": 123,
"location_postal_code": true,
"possible_birth_dates": [
"<string>"
],
"location_last_updated": "<string>",
"job_company_industry_v2": "<string>",
"job_company_linkedin_id": "<string>",
"job_company_twitter_url": "<string>",
"location_address_line_2": "<string>",
"location_street_address": true,
"possible_location_names": [
"<string>"
],
"job_company_facebook_url": "<string>",
"job_company_linkedin_url": "<string>",
"job_company_location_geo": "<string>",
"inferred_years_experience": 123,
"job_company_location_name": "<string>",
"job_onet_broad_occupation": "<string>",
"possible_street_addresses": [
"<unknown>"
],
"job_company_employee_count": 123,
"job_company_location_metro": "<string>",
"recommended_personal_email": true,
"job_company_location_region": "<string>",
"job_company_inferred_revenue": "<string>",
"job_company_location_country": "<string>",
"job_onet_specific_occupation": "<string>",
"job_company_location_locality": "<string>",
"job_company_location_continent": "<string>",
"job_company_location_postal_code": "<string>",
"job_company_total_funding_raised": 123,
"job_company_location_address_line_2": "<string>",
"job_company_location_street_address": "<string>",
"job_onet_specific_occupation_detail": "<string>",
"job_company_12mo_employee_growth_rate": 123
},
"status": 123,
"likelihood": 123,
"matched": [
"<string>"
]
}请求规范
- 方法与路径: POST /apis/v1/people-data-labs/enrich-person-data
- 可用状态: enabled
- 请求 URL 模板:
https://api.aisa.one/apis/v1/people-data-labs/enrich-person-data - Runtime 事实版本: d9aafd76ae02b9bcd98e168c52eb69aba6e12890a1eed8da421910f394e8200a
{
"operationId": "people-data-labs.enrich-person-data",
"method": "POST",
"path": "/apis/v1/people-data-labs/enrich-person-data",
"servers": [
{
"url": "https://api.aisa.one"
}
],
"parameters": [],
"security": [
{
"bearerAuth": []
}
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"type": "object",
"properties": {
"lid": {
"type": "string",
"examples": [
"123456789"
],
"description": "LinkedIn ID."
},
"name": {
"type": "string",
"examples": [
"John Michael Doe"
],
"description": "Full name."
},
"email": {
"type": "string",
"description": "Email address.",
"examples": [
"john.doe@example.com"
]
},
"phone": {
"type": "string",
"examples": [
"+14155552671"
],
"description": "Phone number; E.164 format recommended."
},
"pdl_id": {
"type": "string",
"examples": [
"qEnxS5T1G2YvasA1x24qoA_0000"
],
"description": "People Data Labs unique record ID."
},
"pretty": {
"type": "boolean",
"default": true,
"description": "Format JSON response with indentation for readability."
},
"region": {
"type": "string",
"examples": [
"CA"
],
"description": "State, province, or region of residence."
},
"school": {
"type": "string",
"examples": [
"Stanford University"
],
"description": "School name attended."
},
"company": {
"type": "string",
"examples": [
"Acme Corporation"
],
"description": "Company name where person has worked."
},
"country": {
"type": "string",
"examples": [
"US",
"United States"
],
"description": "Country of residence (ISO 3166-1 alpha-2 code or full name)."
},
"profile": {
"type": "string",
"examples": [
"https://www.linkedin.com/in/john-doe",
"https://www.facebook.com/jane.doe"
],
"description": "Social profile URL (e.g., LinkedIn, Facebook)."
},
"locality": {
"type": "string",
"examples": [
"San Francisco"
],
"description": "City or locality of residence."
},
"location": {
"type": "string",
"examples": [
"San Francisco, CA, USA"
],
"description": "General location (e.g., city, state, country)."
},
"required": {
"type": "string",
"examples": [
"emails AND phone_numbers",
"education AND (emails OR phone_numbers)",
"job_title AND job_company_name",
"experience AND work_email"
],
"description": "Boolean expression of top-level fields required in enriched profile for match. Use AND/OR operators and parentheses for logic (e.g., 'emails AND phone_numbers', 'education AND (emails OR phone_numbers)'). Valid fields: emails, phone_numbers, experience, education, job_title, job_company_name, full_name, location_country, work_email, personal_emails, mobile_phone, linkedin_url, profiles, skills, etc."
},
"last_name": {
"type": "string",
"examples": [
"Doe"
],
"description": "Last name."
},
"birth_date": {
"type": "string",
"examples": [
"1990-01-15"
],
"description": "Birth date (YYYY-MM-DD format)."
},
"email_hash": {
"type": "string",
"examples": [
"d41d8cd98f00b204e9800998ecf8427e",
"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"
],
"description": "SHA-256 or MD5 hash of an email, for matching without exposing the raw email."
},
"first_name": {
"type": "string",
"examples": [
"John"
],
"description": "First name."
},
"postal_code": {
"type": "string",
"examples": [
"94107"
],
"description": "Postal or ZIP code of residence."
},
"data_include": {
"type": "string",
"examples": [
"emails,phones,profiles",
"jobs,education"
],
"description": "Comma-separated data fields to include in response (e.g., 'emails,phones'). Refer to People Data Labs docs for all fields."
},
"min_likelihood": {
"type": "integer",
"default": 2,
"maximum": 10,
"minimum": 0,
"examples": [
0,
5,
10
],
"description": "Minimum confidence score (0-10) for a match to be returned; higher is stricter."
},
"street_address": {
"type": "string",
"examples": [
"123 Main St"
],
"description": "Street address."
},
"include_if_matched": {
"type": "boolean",
"default": false,
"description": "Include input parameters used for matching in the response if true."
}
},
"required": [
"email"
]
}
}
}
},
"x-aisa-status": "enabled",
"x-aisa-pricing": {
"cost_contract": "response_units",
"customer_multiplier": 1.0,
"customer_pricing": "provider_cost_multiplier",
"default_request_estimate_usd": 0.2803,
"estimate_source": "profile_seed",
"evidence_source": "response_body",
"maximum_units": 10000000,
"unit": "provider_credit",
"unit_rate_usd": 1e-06
},
"components": {
"securitySchemes": {
"bearerAuth": {
"scheme": "bearer",
"type": "http"
}
}
}
}
费用与请求规则
按用量计费；默认请求预估费用：$0.2803 USD（不是固定价格）。 声明的单位费率：每 provider_credit $0.000001 USD。 最终费用以账户适用价格及实际结算为准。 公开参考值不是你的账户报价或最终扣费。对于支持 X-AISA-Cost-Mode: quote 的接口，执行前请针对完整请求获取免费报价；执行后通过响应费用元数据和 Usage Logs 核对结算费用。1 USD 等于 1,000,000 个整数 micro-USD。- 默认请求参考估价（USD）: 0.2803
- 声明的单位费率（USD）: 1e-06
- 计费单位: provider_credit
- 计费依据: response_units
- 公开参考倍率: 1.0
- 声明的最大计数或单位数: 10000000
- 结算证据来源: response_body
授权
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
请求体
application/json
Email address.
示例:
"john.doe@example.com"
LinkedIn ID.
示例:
"123456789"
Full name.
示例:
"John Michael Doe"
Phone number; E.164 format recommended.
示例:
"+14155552671"
People Data Labs unique record ID.
示例:
"qEnxS5T1G2YvasA1x24qoA_0000"
Format JSON response with indentation for readability.
State, province, or region of residence.
示例:
"CA"
School name attended.
示例:
"Stanford University"
Company name where person has worked.
示例:
"Acme Corporation"
Country of residence (ISO 3166-1 alpha-2 code or full name).
示例:
"US"
"United States"
Social profile URL (e.g., LinkedIn, Facebook).
示例:
"https://www.linkedin.com/in/john-doe"
"https://www.facebook.com/jane.doe"
City or locality of residence.
示例:
"San Francisco"
General location (e.g., city, state, country).
示例:
"San Francisco, CA, USA"
Boolean expression of top-level fields required in enriched profile for match. Use AND/OR operators and parentheses for logic (e.g., 'emails AND phone_numbers', 'education AND (emails OR phone_numbers)'). Valid fields: emails, phone_numbers, experience, education, job_title, job_company_name, full_name, location_country, work_email, personal_emails, mobile_phone, linkedin_url, profiles, skills, etc.
示例:
"emails AND phone_numbers"
"education AND (emails OR phone_numbers)"
"job_title AND job_company_name"
"experience AND work_email"
Last name.
示例:
"Doe"
Birth date (YYYY-MM-DD format).
示例:
"1990-01-15"
SHA-256 or MD5 hash of an email, for matching without exposing the raw email.
示例:
"d41d8cd98f00b204e9800998ecf8427e"
"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"
First name.
示例:
"John"
Postal or ZIP code of residence.
示例:
"94107"
Comma-separated data fields to include in response (e.g., 'emails,phones'). Refer to People Data Labs docs for all fields.
示例:
"emails,phones,profiles"
"jobs,education"
Minimum confidence score (0-10) for a match to be returned; higher is stricter.
必填范围:
0 <= x <= 10示例:
0
5
10
Street address.
示例:
"123 Main St"
Include input parameters used for matching in the response if true.