def extract_document()

in src/olympia/addons/indexers.py [0:0]

• 87 lines of code
• 20 McCabe index (conditional complexity)

    def extract_document(cls, obj):
        """Extract indexable attributes from an add-on."""
        from olympia.addons.models import Preview

        attrs = (
            'id',
            'average_daily_users',
            'bayesian_rating',
            'contributions',
            'created',
            'default_locale',
            'guid',
            'hotness',
            'icon_hash',
            'icon_type',
            'is_disabled',
            'is_experimental',
            'last_updated',
            'modified',
            'requires_payment',
            'slug',
            'status',
            'type',
            'weekly_downloads',
        )
        data = {attr: getattr(obj, attr) for attr in attrs}

        data['colors'] = None
        # Extract dominant colors from static themes.
        if obj.type == amo.ADDON_STATICTHEME:
            if obj.current_previews:
                data['colors'] = obj.current_previews[0].colors

        data['app'] = [app.id for app in obj.compatible_apps.keys()]
        # Boost by the number of users on a logarithmic scale.
        data['boost'] = float(data['average_daily_users'] ** 0.2)
        # Quadruple the boost if the add-on is public.
        if (
            obj.status == amo.STATUS_APPROVED
            and not obj.is_experimental
            and 'boost' in data
        ):
            data['boost'] = float(max(data['boost'], 1) * 4)
        # We can use all_categories because the indexing code goes through the
        # transformer that sets it.
        data['category'] = [cat.id for cat in obj.all_categories]
        data['current_version'] = cls.extract_version(obj, obj.current_version)
        data['listed_authors'] = [
            {'name': a.name, 'id': a.id, 'username': a.username}
            for a in obj.listed_authors
        ]

        data['has_eula'] = bool(obj.eula)
        data['has_privacy_policy'] = bool(obj.privacy_policy)

        data['is_recommended'] = any(
            PROMOTED_GROUP_CHOICES.RECOMMENDED == promotion.group_id
            for promotion in obj.publicly_promoted_groups
        )

        data['previews'] = [
            {
                'id': preview.id,
                'modified': preview.modified,
                'sizes': preview.sizes,
                'position': preview.position,
            }
            for preview in obj.current_previews
        ]

        data['promoted'] = [
            {
                'group_id': promotion.group_id,
                # store the app approvals because .approved_applications needs it.
                'approved_for_apps': [
                    app.id for app in obj.approved_applications_for(promotion)
                ],
            }
            for promotion in obj.publicly_promoted_groups
        ]

        data['ratings'] = {
            'average': obj.average_rating,
            'count': obj.total_ratings,
            'text_count': obj.text_ratings_count,
        }
        # We can use tag_list because the indexing code goes through the
        # transformer that sets it (attach_tags).
        data['tags'] = getattr(obj, 'tag_list', [])

        # Handle localized fields.
        # First, deal with the 3 fields that need everything:
        for field in ('description', 'name', 'summary'):
            data.update(cls.extract_field_api_translations(obj, field))
            data.update(
                cls.extract_field_search_translation(obj, field, obj.default_locale)
            )
            data.update(cls.extract_field_analyzed_translations(obj, field))

        # Then add fields that only need to be returned to the API without
        # contributing to search relevancy.
        for field in ('developer_comments', 'homepage', 'support_email', 'support_url'):
            data.update(cls.extract_field_api_translations(obj, field))
        if obj.type != amo.ADDON_STATICTHEME:
            # Also do that for preview captions, which are set on each preview
            # object.
            attach_trans_dict(Preview, obj.current_previews)
            for i, preview in enumerate(obj.current_previews):
                data['previews'][i].update(
                    cls.extract_field_api_translations(preview, 'caption')
                )

        return data