All URIs are relative to https://api.inda.ai
| Method | HTTP request | Description |
|---|---|---|
| full_text_search_on_jobads_post | POST /hr/v2/index/{indexname}/jobads/search/full-text/ | Full-Text Search on JobAds |
| search_applications_post | POST /hr/v2/index/{indexname}/resume/{resume_id}/applications/jobads/search/ | Search Applications |
FoundJobAdsResponse full_text_search_on_jobads_post(indexname)
Full-Text Search on JobAds
This is the most common way to search a text document through the job advertisements stored in the index indexname. This function takes as input a list of objects containing the terms you wish to search for, please consider that tokens (individual words) grouped together in the same QueryTerms element will be queried separately in an OR clause, whereas different QueryTerms elements will be joined by an AND clause. To put it in words, the query will retrieve documents that match at least one word from each element in QueryTerms. This behaviour can be modified in one of two ways: + The default_operator query parameter, which defaults to OR, can be set to AND in order to only find documents that contain ALL of the tokens in a given query_terms element. + The " (double quotes) operator, which can be used to wrap strings made up of multiple tokens in order to find documents that contain those words exactly in the order they are presented (sentence match). Remember to escape double quotes in your JSON inputs with a backslash. Each QueryTerms element can be negated with the parameter Exclude set to true. This is equivalent to setting it in a NOT clause. It's also possible to use wildcards to perform jolly searches, the supported wildcards are: + \*: Can be used to match any number of characters in the middle (ad\ment) or at the end (doc\) of a word. + ?: Can be used to match a single character in any position (?xample). All queries are case-insensitive and have some amount of fuzziness by default, meaning that typos and character transpositions will be included in the matches. Additionally, filters can be added to form boolean queries on indexed fields. For a comprehensive list and explanation of filters, see the Query Filters section, the structure is the same. Query parameters are used to specify the offset and size of the search. The method uses cache = true by default, meaning that it will cache automatically each search for cache_time seconds. When caching is active, offset is ignored; in order to navigate or scroll the entire search response (in chunks of size size, as specified in the first search), this method should be used through the search_id. When search_id is provided, other query parameters are ignored, except cache_time. The use of caching is highly recommended to improve the performances. Note that a new search_id is provided for every scroll. Search IDs are not unique but it is strongly recommended to update the search_id at every call of this method with the SearchID of the last response. If the SearchID is missing or equal to null, the scroll has ended. Beware that the scroll can ONLY go forward in the search cache because it is meant to review large searches.
- Bearer Authentication (APIKey):
import time
import inda_hr
from inda_hr.api import job_ad_search_api
from inda_hr.model.error_model import ErrorModel
from inda_hr.model.found_job_ads_response import FoundJobAdsResponse
from inda_hr.model.http_validation_error import HTTPValidationError
from inda_hr.model.job_ad_full_text_search import JobAdFullTextSearch
from pprint import pprint
# Defining the host is optional and defaults to https://api.inda.ai
# See configuration.py for a list of all supported configuration parameters.
configuration = inda_hr.Configuration(
host = "https://api.inda.ai"
)
# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.
# Configure Bearer authorization: APIKey
configuration = inda_hr.Configuration(
access_token = 'YOUR_BEARER_TOKEN'
)
# Enter a context with an instance of the API client
with inda_hr.ApiClient(configuration) as api_client:
# Create an instance of the API class
api_instance = job_ad_search_api.JobAdSearchApi(api_client)
indexname = "indexname_example" # str |
default_operator = "OR" # str | Optional. Change this to *AND* if you wish documents to match ALLof the tokens in a single query_terms element. (optional) if omitted the server will use the default value of "OR"
cache = True # bool | Optional. Whether the search results should be cached or not. (optional) if omitted the server will use the default value of True
cache_time = 300 # int | Optional. Seconds. Ignored if *cache* is <code style='color: #333333; opacity: 0.9'>false</code>. (optional) if omitted the server will use the default value of 300
size = 50 # int | Optional. Number of documents to return. (optional) if omitted the server will use the default value of 50
offset = 0 # int | Optional. Number of documents to skip. Ignored if *cache* is <code style='color: #333333; opacity: 0.9'>true</code>. (optional) if omitted the server will use the default value of 0
min_score = 0 # float | Optional. Minimum pertinence score. (optional) if omitted the server will use the default value of 0
search_id = "search_id_example" # str | Both the initial search request and each subsequent scroll request returns a *SearchID*. The *SearchID* may or may not change between requests; however, only the most recently received *SearchID* should be used. (optional)
job_ad_full_text_search = JobAdFullTextSearch(
query_terms=[
JobadRequestsSimpleTerm(
term="term_example",
exclude=False,
),
],
query_filters=QueryFilters(
must=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
should=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
must_not=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
filter=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
),
) # JobAdFullTextSearch | (optional)
# example passing only required values which don't have defaults set
try:
# Full-Text Search on JobAds
api_response = api_instance.full_text_search_on_jobads_post(indexname)
pprint(api_response)
except inda_hr.ApiException as e:
print("Exception when calling JobAdSearchApi->full_text_search_on_jobads_post: %s\n" % e)
# example passing only required values which don't have defaults set
# and optional values
try:
# Full-Text Search on JobAds
api_response = api_instance.full_text_search_on_jobads_post(indexname, default_operator=default_operator, cache=cache, cache_time=cache_time, size=size, offset=offset, min_score=min_score, search_id=search_id, job_ad_full_text_search=job_ad_full_text_search)
pprint(api_response)
except inda_hr.ApiException as e:
print("Exception when calling JobAdSearchApi->full_text_search_on_jobads_post: %s\n" % e)| Name | Type | Description | Notes |
|---|---|---|---|
| indexname | str | ||
| default_operator | str | Optional. Change this to AND if you wish documents to match ALLof the tokens in a single query_terms element. | [optional] if omitted the server will use the default value of "OR" |
| cache | bool | Optional. Whether the search results should be cached or not. | [optional] if omitted the server will use the default value of True |
| cache_time | int | Optional. Seconds. Ignored if cache is <code style='color: #333333; opacity: 0.9'>false</code>. | [optional] if omitted the server will use the default value of 300 |
| size | int | Optional. Number of documents to return. | [optional] if omitted the server will use the default value of 50 |
| offset | int | Optional. Number of documents to skip. Ignored if cache is <code style='color: #333333; opacity: 0.9'>true</code>. | [optional] if omitted the server will use the default value of 0 |
| min_score | float | Optional. Minimum pertinence score. | [optional] if omitted the server will use the default value of 0 |
| search_id | str | Both the initial search request and each subsequent scroll request returns a SearchID. The SearchID may or may not change between requests; however, only the most recently received SearchID should be used. | [optional] |
| job_ad_full_text_search | JobAdFullTextSearch | [optional] |
- Content-Type: application/json
- Accept: application/json
| Status code | Description | Response headers |
|---|---|---|
| 200 | Successful Response | - |
| 415 | Unsupported Media Type | - |
| 400 | Bad Request | - |
| 422 | Validation Error | - |
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FoundJobAdsResponse search_applications_post(indexname, resume_id)
Search Applications
This method is meant to return those job advertisements that the resume of ID resume_id have applied to, if they respect the given query. Users may specify query filters to apply on both Applications and JobAds indexed fields. Query parameters are used to specify the cache_time and size of the search. The method will automatically cache each search for cache_time seconds. In order to navigate or scroll the entire search response (in chunks of size size, as specified in the first search), this method should be used through the search_id. When search_id is provided, other query parameters are ignored, except cache_time. Note that a new search_id is provided for every scroll. Search IDs are not unique but it is strongly recommended to update the search_id at every call of this method with the SearchID of the last response. If the SearchID is missing or equal to null, the scroll has ended. Beware that the scroll can ONLY go forward in the search cache because it is meant to review large searches.
- Bearer Authentication (APIKey):
import time
import inda_hr
from inda_hr.api import job_ad_search_api
from inda_hr.model.error_model import ErrorModel
from inda_hr.model.job_ad_search_query import JobAdSearchQuery
from inda_hr.model.found_job_ads_response import FoundJobAdsResponse
from inda_hr.model.http_validation_error import HTTPValidationError
from pprint import pprint
# Defining the host is optional and defaults to https://api.inda.ai
# See configuration.py for a list of all supported configuration parameters.
configuration = inda_hr.Configuration(
host = "https://api.inda.ai"
)
# The client must configure the authentication and authorization parameters
# in accordance with the API server security policy.
# Examples for each auth method are provided below, use the example that
# satisfies your auth use case.
# Configure Bearer authorization: APIKey
configuration = inda_hr.Configuration(
access_token = 'YOUR_BEARER_TOKEN'
)
# Enter a context with an instance of the API client
with inda_hr.ApiClient(configuration) as api_client:
# Create an instance of the API class
api_instance = job_ad_search_api.JobAdSearchApi(api_client)
indexname = "indexname_example" # str |
resume_id = "resume_id_example" # str |
cache_time = 300 # int | Optional. Seconds. (optional) if omitted the server will use the default value of 300
size = 50 # int | Optional. Number of documents to return. (optional) if omitted the server will use the default value of 50
search_id = "search_id_example" # str | Both the initial search request and each subsequent scroll request returns a *SearchID*. The *SearchID* may or may not change between requests; however, only the most recently received *SearchID* should be used. (optional)
job_ad_search_query = JobAdSearchQuery(
query_filters=BaseJobAdSearchQuery(
application=QueryFilters(
must=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
should=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
must_not=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
filter=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
),
job_ad=QueryFilters(
must=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
should=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
must_not=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
filter=[
FilterField(
field="field_example",
type="type_example",
value={},
),
],
),
),
) # JobAdSearchQuery | (optional)
# example passing only required values which don't have defaults set
try:
# Search Applications
api_response = api_instance.search_applications_post(indexname, resume_id)
pprint(api_response)
except inda_hr.ApiException as e:
print("Exception when calling JobAdSearchApi->search_applications_post: %s\n" % e)
# example passing only required values which don't have defaults set
# and optional values
try:
# Search Applications
api_response = api_instance.search_applications_post(indexname, resume_id, cache_time=cache_time, size=size, search_id=search_id, job_ad_search_query=job_ad_search_query)
pprint(api_response)
except inda_hr.ApiException as e:
print("Exception when calling JobAdSearchApi->search_applications_post: %s\n" % e)| Name | Type | Description | Notes |
|---|---|---|---|
| indexname | str | ||
| resume_id | str | ||
| cache_time | int | Optional. Seconds. | [optional] if omitted the server will use the default value of 300 |
| size | int | Optional. Number of documents to return. | [optional] if omitted the server will use the default value of 50 |
| search_id | str | Both the initial search request and each subsequent scroll request returns a SearchID. The SearchID may or may not change between requests; however, only the most recently received SearchID should be used. | [optional] |
| job_ad_search_query | JobAdSearchQuery | [optional] |
- Content-Type: application/json
- Accept: application/json
| Status code | Description | Response headers |
|---|---|---|
| 200 | Successful Response | - |
| 404 | Not Found | - |
| 415 | Unsupported Media Type | - |
| 400 | Bad Request | - |
| 422 | Validation Error | - |
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