Readme
Official Python client for the People Data Labs API.
Install from PyPi using pip, a package manager for Python.
pip install peopledatalabs
Sign up for a free PDL API key.
Set your API key in the PDL_API_KEY environment variable.
First, create the PDLPY client:
from peopledatalabs import PDLPY
# specifying an API key
client = PDLPY(
api_key="YOUR API KEY",
)
# or leave blank if you have PDL_API_KEY set in your environment or .env file
client = PDLPY()
Note: You can provide your API key directly in code, or alternatively set a PDL_API_KEY variable in your environment or .env file.
Then, send requests to any PDL API Endpoint.
result = client.person.enrichment(
phone="4155688415",
pretty=True,
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code};"
f"\nReason: {result.reason};"
f"\nMessage: {result.json()['error']['message']};"
)
result = client.person.bulk(
required="emails AND profiles",
requests=[
{
"metadata": {
"user_id": "123"
},
"params": {
"profile": ["linkedin.com/in/seanthorne"],
"location": ["SF Bay Area"],
"name": ["Sean F. Thorne"],
}
},
{
"metadata": {
"user_id": "345"
},
"params": {
"profile": ["https://www.linkedin.com/in/haydenconrad/"],
"first_name": "Hayden",
"last_name": "Conrad",
}
}
]
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
es_query = {
"query": {
"bool": {
"must": [
{"term": {"location_country": "mexico"}},
{"term": {"job_title_role": "health"}},
]
}
}
}
data = {
"query": es_query,
"size": 10,
"pretty": True,
"dataset": "phone, mobile_phone",
}
result = client.person.search(**data)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
sql_query = (
"SELECT * FROM person"
" WHERE location_country='mexico'"
" AND job_title_role='health'"
" AND phone_numbers IS NOT NULL;"
)
data = {
"sql": sql_query,
"size": 10,
"pretty": True,
"dataset": "phone, mobile_phone",
}
result = client.person.search(**data)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
PDL_ID (Retrieve API)result = client.person.retrieve(
person_id="qEnOZ5Oh0poWnQ1luFBfVw_0000",
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
result = client.person.enrichment(
name="sean thorne",
pretty=True,
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
result = client.company.enrichment(
website="peopledatalabs.com",
pretty=True,
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
result = client.company.bulk(
requests=[
{
"metadata": {
"company_id": "123"
},
"params": {
"profile": "linkedin.com/company/peopledatalabs",
}
},
{
"metadata": {
"company_id": "345"
},
"params": {
"profile": "https://www.linkedin.com/company/apple/",
}
}
]
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
es_query = {
"query": {
"bool": {
"must": [
{"term": {"tags": "big data"}},
{"term": {"industry": "financial services"}},
{"term": {"location.country": "united states"}},
]
}
}
}
data = {
"query": es_query,
"size": 10,
"pretty": True,
}
result = client.company.search(**data)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
sql_query = (
"SELECT * FROM company"
" WHERE tags='big data'"
" AND industry='financial services'"
" AND location.country='united states';"
)
data = {
"sql": sql_query,
"size": 10,
"pretty": True,
}
result = client.company.search(**data)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
result = client.autocomplete(
field="title",
text="full",
size=10,
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
result = client.company.cleaner(
name="peOple DaTa LabS",
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
result = client.location.cleaner(
location="455 Market Street, San Francisco, California 94105, US",
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
result = client.school.cleaner(
name="university of oregon",
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
result = client.job_title(
job_title="data scientist",
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
result = client.skill(
skill="c++",
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code}"
f"\nReason: {result.reason}"
f"\nMessage: {result.json()['error']['message']}"
)
result = client.ip(
ip="72.212.42.169",
)
if result.ok:
print(result.text)
else:
print(
f"Status: {result.status_code};"
f"\nReason: {result.reason};"
f"\nMessage: {result.json()['error']['message']};"
)
PDLPY(sandbox=True)
Person Endpoints
| API Endpoint | PDLPY Function |
|---|---|
| Person Enrichment API | PDLPY.person.enrichment(**params) |
| Person Bulk Enrichment API | PDLPY.person.bulk(**params) |
| Person Search API | PDLPY.person.search(**params) |
| Person Retrieve API | PDLPY.person.retrieve(**params) |
| Person Identify API | PDLPY.person.identify(**params) |
Company Endpoints
| API Endpoint | PDLPY Function |
|---|---|
| Company Enrichment API | PDLPY.company.enrichment(**params) |
| Company Bulk Enrichment API | PDLPY.company.bulk(**params) |
| Company Search API | PDLPY.company.search(**params) |
Supporting Endpoints
| API Endpoint | PDLJS Function |
|---|---|
| Autocomplete API | PDLPY.autocomplete(**params) |
| Company Cleaner API | PDLPY.company.cleaner(**params) |
| Location Cleaner API | PDLPY.location.cleaner(**params) |
| School Cleaner API | PDLPY.school.cleaner(**params) |
| Job Title Enrichment API | PDLPY.job_title(**params) |
| Skill Enrichment API | PDLPY.skill(**params) |
| IP Enrichment API | PDLPY.ip(**params) |
All of our API endpoints are documented at: https://docs.peopledatalabs.com/
These docs describe the supported input parameters, output responses and also provide additional technical context.
As illustrated in the Endpoints section above, each of our API endpoints is mapped to a specific method in the PDLPY class. For each of these class methods, all function inputs are mapped as input parameters to the respective API endpoint, meaning that you can use the API documentation linked above to determine the input parameters for each endpoint.
As an example:
The following is valid because name is a supported input parameter to the Person Identify API:
PDLPY().person.identify({"name": "sean thorne"})
Conversely, this would be invalid because fake_parameter is not an input parameter to the Person Identify API:
PDLPY().person.identify({"fake_parameter": "anything"})
NOTE: When upgrading to v2.X.X from vX.X.X and below, the minimum required python version is now 3.8.
NOTE: When upgrading to v3.X.X from vX.X.X and below, the minimum required pydantic version is now 2.
FAQs
Official Python client for the People Data Labs API
We found that peopledatalabs demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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