Example Source
>>> from hrflow import Hrflow
>>> client = Hrflow(api_secret="YOUR_API_KEY")
>>> result = client.source.list(name='python', limit=1)
>>> print(result)
{
'code': 200,
'data': [{
'archive': None,
'consent': False,
'consent_url': None,
'created_at': '2020-07-22T09:11:32+0000',
'description': None,
'id': id,
'key': 'source_key',
'members': ['member@hrflow.ai'],
'name': 'sync-php',
'notification': False,
'private': False,
'stats': {'size': '0'},
'status': True,
'subtype': 'php',
'type': 'api',
'updated_at': '2020-07-22T09:11:32+0000',
'user': {
'avatarUrl': '/images/user.png',
'email': 'member@hrflow.ai',
'firstName': None,
'id': id,
'lastName': None,
'locale': 'english',
'phone': None,
'position': None,
'pseudo': None}},
.
.
. ],
'message': 'Source list',
'meta': {'count': 11, 'maxPage': 1, 'page': 1, 'total': 11}}
Example Profile
>>> from hrflow import Hrflow
>>> client = Hrflow(api_secret="YOUR_API_KEY")
>>> result = client.profile.searching.list(source_keys=["source_key"],
page=1, limit=30,
sort_by='created_at',
order_by="desc")
>>> print(result)
{
'code': 200,
'data': {'profiles': [{...},
{...},
{...}]
}
}
Example Job
>>> from hrflow import Hrflow
>>> client = Hrflow(api_secret="YOUR_API_KEY")
>>> result = client.job.searching.list(board_keys=["board_key"], page=1,
limit=30, sort_by='created_at')
>>> print(result)
{
'code': 200,
'data': {'jobs': [{...},
{...},
{...}]
}
}
For any methods that needs key and reference
you need to provide at least one of them but not necessarily both, keep in mind that reference overrides id.
JSON object with 5 required fields: key, reference, info, text_language and text. The JSON contains other optional fields that cannot be listed here. (See the examples above)
This endpoint allows you to parse a resume and make a profile object from it.
📘 Real-time parsing: To use the real-time parsing feature, you must have it enabled for the correponding source. In which case you just need to set
sync_parsingto1.
- Open the file in
binary modeand parse it using this method without reference
>>> with open("path/2/file", "rb") as profile_file:
... response = client.profile.parsing.add_file(
source_key="source_key",
profile_file=profile_file,
sync_parsing=1,
sync_parsing_indexing=1,
webhook_parsing_sending=0,
tags=[{"name": "archive", "value": True}],
)- Or using a reference like this:
>>> with open("path/2/file", "rb") as profile_file:
... response = client.profile.parsing.add_file(
source_key="source_key",
reference="my_resume",
profile_file=profile_file,
sync_parsing=1,
sync_parsing_indexing=1,
webhook_parsing_sending=0,
tags=[{"name": "archive", "value": True}],
)In both cases the output should look like this:
{
"code": 201,
"message": "Profile parsed successfully. Profile extraction finished : 8.00 seconds.",
...
}
Retrieve Parsing information using source key and key/reference.
⚠️ Query parameters:referenceandkeycannot be null at the same time.
- Retrieve parsing information using source key
>>> response = client.profile.parsing.get(source_key="source_key", key="profile_key")- Retrieve parsing information using reference
>>> response = client.profile.parsing.get(source_key="source_key", reference="my_resume")- The output should should look like this
{
"code": 200,
"message": "Profile parsing",
...
}
In order to add a Json profile you can index it using HrFlow search engine
- Index a profile in a source using a JSON file
profile_json
>>> response = client.profile.indexing.add_json(
source_key="source_key", profile_json=profile_json
)- The output should be of this form:
{
"code": 200,
"message": "Profile parsing",
...
}
This enables you to edit the JSON of a profile in a source
📘 JSON profile must include profile's key
- Edit a profile in a source
>>> response = client.profile.indexing.edit(
source_key="source_key", key="profile_key", profile_json=profile_json
)- You should receive as output the following
{
"code": 200,
"message": "Profile edited",
...
}
Allows retrieving the profile information using source key and key/reference.
- Retrieve a profile object from a source this method
>>> response = client.profile.indexing.get(source_key="source_key", key="profile_key")- The output should be
{
"code": 200,
"message": "Profile details",
...
}
- Retrieve a profile's attachment list from a source
>>> response = client.profile.attachment.list(source_key="source_key", key="profile_key")- You should receive as output
{
"code": 200,
"message": "Profile's attachment list",
...
}
This endpoint allows you to search profiles.
- Search a profile using sources' keys
>>> response = client.profile.searching.list(
source_keys=["source_key"],
page=1,
limit=30,
sort_by="created_at",
order_by="desc",
text_keywords=["python"],
created_at_min="2020-07-09T13:35:11+0000",
)- The output should look like this
{
"code": 200,
"message": "Profile's searching results",
...
}
This endpoint allows you to Score Profiles for a job.
- Score a profile using a list of
source_key, aboard_key, and ajob_key
>>> response = client.profile.scoring.list(
source_keys=["source_key"],
board_key="board_key",
job_key="job_key",
use_agent=1,
page=1,
limit=30,
sort_by="created_at",
order_by=None,
text_keywords=["python"],
)JSON object with 5 required fields: key, reference, name, location and sections . It contains other optional fields that cannot be listed here.
Here is what a job JSON looks like:
{
"name": "Data Engineer",
"agent_key": "agent_key",
"reference": "Job's reference abc",
"url": "https://www.pole-emploi.ai/jobs/data_engineer",
"summary": "As an engineer for the Data Engineering Infrastructure team, you will design, build, scale, and evolve our data engineering platform, services and tooling. Your work will have a critical impact on all areas of business:supporting detailed internal analytics, calculating customer usage, securing our platform, and much more.",
"location": {
"text": "Dampierre en Burly (45)",
"geopoint": {
"lat": 47.7667,
"lon": 2.5167
}
},
"sections": [{
"name": "profile",
"title": "Searched Profile",
"description": "Bac+5"
}
],
"skills": [{
"name": "python",
"value": None
},
{
"name": "spark",
"value": 0.9
}
],
"languages": [{
"name": "english",
"value": 1
},
{
"name": "french",
"value": 1
}
],
"tags": [{
"name": "archive",
"value": True
},
{
"name": "tag example",
"value": "tag"
}
],
"ranges_date": [{
"name": "Dates",
"value_min": "2020-05-18T21:59",
"value_max": "2020-09-15T21:59"
}
],
"ranges_float": [{
"name": "salary",
"value_min": 30,
"value_max": 40,
"unit": "eur"
}
],
"metadatas": [{
"name": "metadata example",
"value": "metadata"
}
]
}This endpoint allows you to Index a Job object.
⚠️ Job Input: If your Job is an unstructured text, make sure to parse it first before indexing it. See how in 🧠 Parse a raw Text.
- Index a job in a board. This action requires a
board_key
>>> response = client.job.indexing.add_json(board_key="board_key", job_json=job_json)- The output should look like this
{
"code": 200,
"message": "Job created",
...
}
This endpoint allows you to edit the of JSON of Job.
- Edit a job already indexed in a board. This action requires a
job_key
>>> response = client.job.indexing.edit(
board_key="board_key", key="job_key", job_json=job_json
)- You should receive the following output
{
"code": 200,
"message": "Job edited",
...
}
This endpoint allows retriving the job object from a board using the corresponding keys
- Retrieve a job indexed in a board
>>> response = client.job.indexing.get(board_key="board_key", key="job_key")- The output
{
"code": 200,
"message": "Job details",
...
}
This endpoint allows you to Search for Jobs.
- Search for jobs among a list of boards
>>> response = client.job.searching.list(
board_keys=["board_key"], page=1, limit=30, sort_by="created_at", order_by=None
)- The output should be
{
"code": 200,
"message": "Job searching list",
...
}
This endpoint allows you to Score Jobs for Profile.
- Score a job for a certain profile
>>> response = client.job.scoring.list(
board_keys=["board_key"],
source_key="source_key",
profile_key="profile_key",
use_agent=1,
agent_key="agent_key",
page=1,
limit=30,
sort_by="created_at",
order_by=None,
)Allows extracting over 50 data point from any raw input text.
- Parse a raw text given as argument
>>> response = client.document.parsing.post(text="Your text here")- It should return
{
"code": 200,
"message": "Parsing results,
...
}
Predict likely missing skills in a text
- Predict the skills using the method below
>>> response = client.document.revealing.post(text="hello")- The output should look like this:
{
"code": 200,
"message": "Revealing results,
...
}
This endpoint allows profile/job 's embedding, it returns embedding encoded as base64.
In order to retrieve Item embeddings, you must decode response's body, and reshape the output as shown in below example.
>>> import base64
>>> import numpy as np
>>> dfloat32 = np.dtype(">f4")
>>> response = client.document.embedding.post(
item_type="profile", item=profile_json, return_sequences=True
)
>>> embeddings_reponse = response.get("data")
>>> embeddings_decoded = base64.b64decode(embeddings_reponse)
>>> embeddings_as_np = np.frombuffer(embeddings_decoded, dtype=dfloat32)
>>> embeddings = np.reshape(embeddings_as_np, (-1, 1024)).tolist() >>> response = client.document.linking.post(text="python", top_n=20)A JSON object with a key, a name, a description, a type and a subtype and other optional fields.
Retrieve all sources for a given team account
- List sources using this method
>>> response = client.source.list(name='async')- It should output something like this
{
"code": 200,
"message": "Source list",
...
}
Retrieve source's information with a source key
- Get a source's information for a given key using
>>> response = client.source.get(key=key)- The output should contain this message
{
"code": 200,
"message": "Source info",
...
}
A JSON object representing a board containing many fields: a key, a name, ``description, a description`, a `type` and a `subtype`
Retrieve all boads for given team account
- Get all boards for given team account using this method
>>> response = client.board.list(name='compaign')- The output should be as follows:
{
"code": 200,
"message": "Board list",
...
}
Retrieve board's information for a given key.
- Get the board's information using this method
>>> response = client.board.get(key=key)- The output should be the same as below:
{
"code": 200,
"message": "Board info",
...
}
Checks weither your webhook integration is enabled and works.
- Check if it is enabled using a
urland atype
>>> response = client.webhooks.check("url","type")- The output should look like this
{
"code": 200,
"message": "Parsing results,
...
}
Add an handler of a webhook event
- To set a handler, use the method below
>>> response = client.webhooks.setHandler(event_name, callback)
⚠️ event_nameandcallbackare required.
- Check if a callback is bind to an event
>>> response = client.webhooks.isHandlerPresent(event_name)
⚠️ event_nameandcallbackare required.
Remove the handler for a webhook
- To do so, use the method below
>>> response = client.webhooks.removeHandler(event_name)
⚠️ event_nameandcallbackare required.
Start the handler for the given webhook request.
>>> response = client.webhooks.handle(request_headers, signature_header)request_headers the headers of the webhook request while signature_header is the HTTP-hrflow-SIGNATURE header only, one of them is required.
event_name is required
Here is an example on how to handle webhooks
from hrflow import Hrflow
def func_callback(event_name, webhook_data):
print("{} {}".format(event_name, webhook_data))
client = Hrflow(api_secret="YOUR_API_KEY", webhook_secret="webhook_key")
# Set an handler for webhook event.
callback = func_callback
resp = client.webhooks.setHandler("profile.parsing.success", callback)
# Get the header of the request sent by the webhook.
encoded_header = {HTTP - hrflow - SIGNATURE: "some encoded datas"}
# Handle the webhook
client.webhooks.handle(request_headers=encoded_header)- Here an example on how to get help:
>>> from hrflow.profile.parsing import ProfileParsing
>>> help(ProfileParsing.get)
#Help on function get in module hrflow.profile.parsing:
get(self, source_key=None, key=None, reference=None, email=None)
#Retrieve Parsing information.
#Args:
source_key: <string>
source_key
key: <string>
key
reference: <string>
profile_reference
email: <string>
profile_email
#Returns
Get information- More help ? see hrflow API Docs