def test_auto_terms(self, app, current_term_index):
     all_term_ids = set(berkeley.reverse_term_ids(include_future_terms=True, include_legacy_terms=True))
     canvas_integrated_term_ids = set(berkeley.reverse_term_ids())
     assert canvas_integrated_term_ids < all_term_ids
     assert berkeley.current_term_id() == '2182'
     assert berkeley.future_term_id() == '2188'
     assert berkeley.s3_canvas_data_path_current_term() == 'canvas-data/term/spring-2018'
Exemple #2
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    def test_term_id_lists(self, app):
        all_term_ids = set(
            berkeley.reverse_term_ids(include_future_terms=True,
                                      include_legacy_terms=True))
        canvas_integrated_term_ids = set(berkeley.reverse_term_ids())
        future_term_ids = set(berkeley.future_term_ids())
        legacy_term_ids = set(berkeley.legacy_term_ids())
        assert canvas_integrated_term_ids < all_term_ids
        assert berkeley.sis_term_id_for_name(
            app.config['EARLIEST_LEGACY_TERM']) in all_term_ids
        assert berkeley.sis_term_id_for_name(
            app.config['EARLIEST_TERM']) in all_term_ids
        assert berkeley.sis_term_id_for_name(
            app.config['CURRENT_TERM']) in all_term_ids
        assert berkeley.sis_term_id_for_name(
            app.config['FUTURE_TERM']) in all_term_ids

        assert berkeley.current_term_id() in canvas_integrated_term_ids
        assert berkeley.earliest_term_id() in canvas_integrated_term_ids

        assert future_term_ids.isdisjoint(canvas_integrated_term_ids)
        assert future_term_ids < all_term_ids
        assert berkeley.future_term_id() in future_term_ids

        assert legacy_term_ids.isdisjoint(canvas_integrated_term_ids)
        assert legacy_term_ids < all_term_ids
        assert berkeley.earliest_legacy_term_id() in berkeley.legacy_term_ids()
def app_config():
    def _to_api_key(key):
        chunks = key.split('_')
        return f"{chunks[0].lower()}{''.join(chunk.title() for chunk in chunks[1:])}"

    return tolerant_jsonify(
        {
            **dict((_to_api_key(key), app.config[key] if key in app.config else None) for key in PUBLIC_CONFIGS),
            **{
                'currentEnrollmentTerm': current_term_name(),
                'currentEnrollmentTermId': int(current_term_id()),
                'futureTermId': int(future_term_id()),
            },
        }, )
Exemple #4
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def app_config():
    current_term_name = berkeley.current_term_name()
    current_term_id = berkeley.current_term_id()
    future_term_id = berkeley.future_term_id()
    return tolerant_jsonify({
        'currentEnrollmentTerm':
        current_term_name,
        'currentEnrollmentTermId':
        int(current_term_id),
        'futureTermId':
        int(future_term_id),
        'ebEnvironment':
        app.config['EB_ENVIRONMENT']
        if 'EB_ENVIRONMENT' in app.config else None,
        'nessieEnv':
        app.config['NESSIE_ENV'],
    })
Exemple #5
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    def generate_feeds(self):
        # Translation between canvas_user_id and UID/SID is needed to merge Canvas analytics data and SIS enrollment-based data.
        advisees_by_canvas_id = {}
        advisees_by_sid = {}
        self.successes = []
        self.failures = []
        profile_tables = self.generate_student_profile_tables(
            advisees_by_canvas_id, advisees_by_sid)
        if not profile_tables:
            raise BackgroundJobError(
                'Failed to generate student profile tables.')

        feed_path = app.config['LOCH_S3_BOAC_ANALYTICS_DATA_PATH'] + '/feeds/'
        s3.upload_json(advisees_by_canvas_id,
                       feed_path + 'advisees_by_canvas_id.json')

        upload_student_term_maps(advisees_by_sid)

        # Avoid processing Canvas analytics data for future terms and pre-CS terms.
        for term_id in (future_term_ids() + legacy_term_ids()):
            enrollment_term_map = s3.get_object_json(
                feed_path + f'enrollment_term_map_{term_id}.json')
            if enrollment_term_map:
                GenerateMergedEnrollmentTerm().refresh_student_enrollment_term(
                    term_id, enrollment_term_map)

        canvas_integrated_term_ids = reverse_term_ids()
        app.logger.info(
            f'Will queue analytics generation for {len(canvas_integrated_term_ids)} terms on worker nodes.'
        )
        result = queue_merged_enrollment_term_jobs(self.job_id,
                                                   canvas_integrated_term_ids)
        if not result:
            raise BackgroundJobError('Failed to queue enrollment term jobs.')

        refresh_all_from_staging(profile_tables)
        self.update_redshift_academic_standing()
        self.update_rds_profile_indexes()

        app.logger.info(
            'Profile generation complete; waiting for enrollment term generation to finish.'
        )

        while True:
            sleep(1)
            enrollment_results = get_merged_enrollment_term_job_status(
                self.job_id)
            if not enrollment_results:
                raise BackgroundJobError('Failed to refresh RDS indexes.')
            any_pending_job = next(
                (row for row in enrollment_results
                 if row['status'] == 'created' or row['status'] == 'started'),
                None)
            if not any_pending_job:
                break

        app.logger.info('Exporting analytics data for archival purposes.')
        unload_enrollment_terms([current_term_id(), future_term_id()])

        app.logger.info('Refreshing enrollment terms in RDS.')
        with rds.transaction() as transaction:
            if self.refresh_rds_enrollment_terms(None, transaction):
                transaction.commit()
                app.logger.info('Refreshed RDS enrollment terms.')
            else:
                transaction.rollback()
                raise BackgroundJobError(
                    'Failed to refresh RDS enrollment terms.')

        status_string = f'Generated merged profiles ({len(self.successes)} successes, {len(self.failures)} failures).'
        errored = False
        for row in enrollment_results:
            status_string += f" {row['details']}"
            if row['status'] == 'error':
                errored = True

        truncate_staging_table('student_enrollment_terms')
        if errored:
            raise BackgroundJobError(status_string)
        else:
            return status_string