Merge pull request #174 from openedx/saleem-latif/ENT-7234-updates

fix: Fixed some implementation issues in job recommendation logic.

Author: saleem-latif

CHANGELOG.rst

@@ -13,6 +13,10 @@ Change Log
 
 Unreleased
 
+[1.43.3] - 2023-08-02
+---------------------
+* fix: Fixed some implementation issues in job recommendation logic.
+
 [1.43.2] - 2023-08-01
 ---------------------
 * perf: Further performance enhancements for the algolia index command.

taxonomy/__init__.py

@@ -15,6 +15,6 @@
 # 2. MINOR version when you add functionality in a backwards compatible manner, and
 # 3. PATCH version when you make backwards compatible bug fixes.
 # More details can be found at https://semver.org/
-__version__ = '1.43.2'
+__version__ = '1.43.3'
 
 default_app_config = 'taxonomy.apps.TaxonomyConfig'  # pylint: disable=invalid-name

taxonomy/algolia/constants.py

@@ -16,6 +16,7 @@
         'searchable(skills.name)',
         'searchable(industry_names)',
         'searchable(b2c_opt_in)'
+        'searchable(job_sources)'
     ],
 }
 

taxonomy/algolia/utils.py

@@ -113,16 +113,16 @@ def calculate_job_recommendations(jobs_data):
     Note: `jobs_data` will be treated as mutable (instead of creating a new dict to return)
         to reduce memory footprint of this function.
 
-    Args:
+    Arguments:
         jobs_data (dict<str: dict>): A dictionary containing jobs data like skills. key of the dict is jobs name and
             the value dict should at-least contain a set of skills against `skills` key.
 
     Returns:
         (dict<str: dict>): The same dict from the argument, with `similar_jobs` added against each job.
     """
     SIMILAR_JOBS_COUNT = 3
-    job_recommendations = deque([], maxlen=SIMILAR_JOBS_COUNT)
     for job_name, job in jobs_data.items():
+        job_recommendations = deque([], maxlen=SIMILAR_JOBS_COUNT)
         for candidate_job_name, candidate_job in jobs_data.items():
             if job_name == candidate_job_name:
                 continue
@@ -131,7 +131,7 @@ def calculate_job_recommendations(jobs_data):
 
             insert_item_in_ordered_queue(
                 queue=job_recommendations,
-                item=JobRecommendation(job_name, jaccard_similarity),
+                item=JobRecommendation(candidate_job_name, jaccard_similarity),
                 key=lambda item: item.similarity,
             )