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Use new recommendation endpoints · deric/python-api-client@896aada · GitHub
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OndraFiedlerOndraFiedler
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Use new recommendation endpoints
1 parent b73bd70 commit 896aada

12 files changed

Lines changed: 35 additions & 41 deletions

‎README.rst‎

Lines changed: 14 additions & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -32,10 +32,10 @@ Basic example
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from recombee_api_client.api_client import RecombeeClient
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from recombee_api_client.exceptions import APIException
35-
from recombee_api_client.api_requests import AddPurchase, UserBasedRecommendation, Batch
35+
from recombee_api_client.api_requests import AddPurchase, RecommendItemsToUser, Batch
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import random
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38-
client = RecombeeClient('client-test', 'jGGQ6ZKa8rQ1zTAyxTc0EMn55YPF7FJLUtaMLhbsGxmvwxgTwXYqmUk5xVZFw98L')
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client = RecombeeClient('--my-database-id--', '--my-secret-token--'')
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#Generate some random purchases of items by users
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PROBABILITY_PURCHASED = 0.1
@@ -55,29 +55,29 @@ Basic example
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client.send(Batch(purchase_requests))
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# Get recommendations for user 'user-25'
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recommended = client.send(UserBasedRecommendation('user-25', 5))
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recommended = client.send(RecommendItemsToUser('user-25', 5))
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print("Recommended items: %s" % recommended)
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except APIException as e:
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print(e)
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---------------------
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Using property values
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---------------------
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.. code-block:: python
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from recombee_api_client.api_client import RecombeeClient
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from recombee_api_client.api_requests import AddItemProperty, SetItemValues, AddPurchase
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from recombee_api_client.api_requests import ItemBasedRecommendation, Batch, ResetDatabase
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from recombee_api_client.api_requests import RecommendItemsToItem, Batch, ResetDatabase
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import random
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NUM = 100
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PROBABILITY_PURCHASED = 0.1
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80-
client = RecombeeClient('client-test', 'jGGQ6ZKa8rQ1zTAyxTc0EMn55YPF7FJLUtaMLhbsGxmvwxgTwXYqmUk5xVZFw98L')
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client = RecombeeClient('--my-database-id--', '--my-secret-token--'')
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#Clear the entire database
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client.send(ResetDatabase())
@@ -124,23 +124,21 @@ Using property values
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client.send(Batch(requests))
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# Get 5 recommendations for user-42, who is currently viewing computer-6
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recommended = client.send(ItemBasedRecommendation('computer-6', 5, target_user_id='user-42'))
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recommended = client.send(RecommendItemsToItem('computer-6', 'user-42', 5))
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print("Recommended items: %s" % recommended)
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# Get 5 recommendations for user-42, but recommend only computers that
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# have at least 3 cores
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# Recommend only computers that have at least 3 cores
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recommended = client.send(
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ItemBasedRecommendation('computer-6', 5, target_user_id='user-42', filter="'num-cores'>=3")
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RecommendItemsToItem('computer-6', 'user-42', 5, filter="'num-cores'>=3")
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)
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print("Recommended items with at least 3 processor cores: %s" % recommended)
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137-
# Get 5 recommendations for user-42, but recommend only items that
138-
# are more expensive then currently viewed item (up-sell)
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# Recommend only items that are more expensive then currently viewed item (up-sell)
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recommended = client.send(
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ItemBasedRecommendation('computer-6', 5, target_user_id='user-42', filter="'price' > context_item[\"price\"]")
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RecommendItemsToItem('computer-6', 'user-42', 5, filter="'price' > context_item[\"price\"]")
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)
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print("Recommended up-sell items: %s" % recommended)
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------------------
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Exception handling
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------------------
@@ -155,11 +153,11 @@ Example:
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try:
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recommended = client.send(
158-
ItemBasedRecommendation('computer-6', 5,target_user_id='user-42', filter="'price' > context_item[\"price\"]")
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RecommendItemsToItem('computer-6', 'user-42', 5, filter="'price' > context_item[\"price\"]")
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)
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except ResponseException as e:
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#Handle errorneous request => use fallback
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except ApiTimeoutException as e:
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#Handle timeout => use fallback
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except APIException as e:
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#APIException is parent of both ResponseException and ApiTimeoutException
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#APIException is parent of both ResponseException and ApiTimeoutException

‎recombee_api_client/api_client.py‎

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Original file line numberDiff line numberDiff line change
@@ -63,7 +63,7 @@ def send(self, request):
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@staticmethod
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def __get_http_headers(additional_headers=None):
66-
headers = {'User-Agent': 'recombee-python-api-client/1.6.0'}
66+
headers = {'User-Agent': 'recombee-python-api-client/2.0.0'}
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if additional_headers:
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headers.update(additional_headers)
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return headers

‎recombee_api_client/api_requests/item_based_recommendation.py‎

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Original file line numberDiff line numberDiff line change
@@ -5,6 +5,8 @@
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class ItemBasedRecommendation(Request):
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"""
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Deprecated since version 2.0.0. Use RecommendItemsToItem request instead.
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Recommends set of items that are somehow related to one given item, *X*. Typical scenario for using item-based recommendation is when user *A* is viewing *X*. Then you may display items to the user that he might be also interested in. Item-recommendation request gives you Top-N such items, optionally taking the target user *A* into account.
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It is also possible to use POST HTTP method (for example in case of very long ReQL filter) - query parameters then become body parameters.

‎recombee_api_client/api_requests/recommend_items_to_item.py‎

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Original file line numberDiff line numberDiff line change
@@ -5,8 +5,6 @@
55

66
class RecommendItemsToItem(Request):
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"""
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This feature is currently in beta.
9-
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Recommends set of items that are somehow related to one given item, *X*. Typical scenario is when user *A* is viewing *X*. Then you may display items to the user that he might be also interested in. Recommend items to item request gives you Top-N such items, optionally taking the target user *A* into account.
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It is also possible to use POST HTTP method (for example in case of very long ReQL filter) - query parameters then become body parameters.
@@ -41,9 +39,9 @@ def __init__(self, item_id, target_user_id, count, user_impact=DEFAULT, filter=D
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Do not create some special dummy user for getting recommendations,
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as it could cause mislead the recommendation models,
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as it could mislead the recommendation models,
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leading to wrong recommendations.
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and result in wrong recommendations.
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For anonymous/unregistered users it is possible to use for example their session ID.
@@ -73,7 +71,7 @@ def __init__(self, item_id, target_user_id, count, user_impact=DEFAULT, filter=D
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E{lb}
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76-
"recommId": "8ac80708afe9148130528757ebf6aaba",
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"recommId": "0c6189e7-dc1a-429a-b613-192696309361",
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"recomms":
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@@ -126,7 +124,7 @@ def __init__(self, item_id, target_user_id, count, user_impact=DEFAULT, filter=D
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127125
E{lb}
128126
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"recommId": "c7dbfc503d262b80b77b4949ee9855fb",
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"recommId": "6842c725-a79f-4537-a02c-f34d668a3f80",
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"recomms":
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‎recombee_api_client/api_requests/recommend_items_to_user.py‎

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Original file line numberDiff line numberDiff line change
@@ -5,8 +5,6 @@
55

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class RecommendItemsToUser(Request):
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"""
8-
This feature is currently in beta.
9-
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Based on user's past interactions (purchases, ratings, etc.) with the items, recommends top-N items that are most likely to be of high value for a given user.
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1210
It is also possible to use POST HTTP method (for example in case of very long ReQL filter) - query parameters then become body parameters.
@@ -39,7 +37,7 @@ def __init__(self, user_id, count, filter=DEFAULT, booster=DEFAULT, cascade_crea
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E{lb}
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42-
"recommId": "1644e7b31759a08480da5f3b0a13045b",
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"recommId": "ce52ada4-e4d9-4885-943c-407db2dee837",
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"recomms":
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@@ -92,7 +90,7 @@ def __init__(self, user_id, count, filter=DEFAULT, booster=DEFAULT, cascade_crea
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E{lb}
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"recommId": "e3ba43af1a4e59dd08a00adced1729a7",
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"recommId": "a86ee8d5-cd8e-46d1-886c-8b3771d0520b",
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"recomms":
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‎recombee_api_client/api_requests/recommend_users_to_item.py‎

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Original file line numberDiff line numberDiff line change
@@ -5,8 +5,6 @@
55

66
class RecommendUsersToItem(Request):
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"""
8-
This feature is currently in beta.
9-
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Recommend users that are likely to be interested in a given item.
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It is also possible to use POST HTTP method (for example in case of very long ReQL filter) - query parameters then become body parameters.
@@ -39,7 +37,7 @@ def __init__(self, item_id, count, filter=DEFAULT, booster=DEFAULT, cascade_crea
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E{lb}
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42-
"recommId": "9eeebc318508302529e3241f4570834d",
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"recommId": "039b71dc-b9cc-4645-a84f-62b841eecfce",
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"recomms":
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E{lb}
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87-
"recommId": "d4c826635efc3e01a83470008c5697f1",
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"recommId": "b2b355dd-972a-4728-9c6b-2dc229db0678",
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"recomms":
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@@ -133,7 +131,7 @@ def __init__(self, item_id, count, filter=DEFAULT, booster=DEFAULT, cascade_crea
133131
self.included_properties = included_properties
134132
self.diversity = diversity
135133
self.expert_settings = expert_settings
136-
self.timeout = 3000
134+
self.timeout = 50000
137135
self.ensure_https = False
138136
self.method = 'post'
139137
self.path = "/recomms/items/%s/users/" % (self.item_id)

‎recombee_api_client/api_requests/recommend_users_to_user.py‎

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Original file line numberDiff line numberDiff line change
@@ -5,8 +5,6 @@
55

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class RecommendUsersToUser(Request):
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"""
8-
This feature is currently in beta.
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Get similar users as some given user, based on the user's past interactions (purchases, ratings, etc.) and values of properties.
119
1210
It is also possible to use POST HTTP method (for example in case of very long ReQL filter) - query parameters then become body parameters.
@@ -39,7 +37,7 @@ def __init__(self, user_id, count, filter=DEFAULT, booster=DEFAULT, cascade_crea
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4038
E{lb}
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42-
"recommId": "32fc671480eb29d843e47def43503992",
40+
"recommId": "9cb9c55d-50ba-4478-84fd-ab456136156e",
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"recomms":
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@@ -84,7 +82,7 @@ def __init__(self, user_id, count, filter=DEFAULT, booster=DEFAULT, cascade_crea
8482
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E{lb}
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87-
"recommId": "27d81ade643621f45cc6ba5d30d7d683",
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"recommId": "b326d82d-5d57-4b45-b362-c9d6f0895855",
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"recomms":
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@@ -145,7 +143,7 @@ def __init__(self, user_id, count, filter=DEFAULT, booster=DEFAULT, cascade_crea
145143
self.rotation_rate = rotation_rate
146144
self.rotation_time = rotation_time
147145
self.expert_settings = expert_settings
148-
self.timeout = 3000
146+
self.timeout = 50000
149147
self.ensure_https = False
150148
self.method = 'post'
151149
self.path = "/recomms/users/%s/users/" % (self.user_id)

‎recombee_api_client/api_requests/user_based_recommendation.py‎

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Original file line numberDiff line numberDiff line change
@@ -5,6 +5,8 @@
55

66
class UserBasedRecommendation(Request):
77
"""
8+
Deprecated since version 2.0.0. Use RecommendItemsToUser request instead.
9+
810
Based on user's past interactions (purchases, ratings, etc.) with the items, recommends top-N items that are most likely to be of high value for a given user.
911
1012
It is also possible to use POST HTTP method (for example in case of very long ReQL filter) - query parameters then become body parameters.

‎setup.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -11,7 +11,7 @@
1111
setup(
1212
name='recombee-api-client',
1313

14-
version='1.6.0',
14+
version='2.0.0',
1515

1616
description='Client for Recombee recommendation API',
1717
long_description=long_description,

‎tests/test_cases/add_entity.py‎

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@@ -19,7 +19,7 @@ def test_add_entity(self):
1919
req = self.create_request('valid_id')
2020
resp = self.client.send(req)
2121
# it 'fails with invalid entity id'
22-
req = self.create_request('...not_valid...')
22+
req = self.create_request('$$$not_valid$$$')
2323
try:
2424
self.client.send(req)
2525
self.assertFail()

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