result_formatter.py
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"""
Result formatter for converting ES internal format to external-friendly format.
"""
from typing import List, Dict, Any, Optional
from .models import SpuResult, SkuResult, FacetResult, FacetValue
class ResultFormatter:
"""Formats ES search results to external-friendly format."""
@staticmethod
def format_search_results(
es_hits: List[Dict[str, Any]],
max_score: float = 1.0
) -> List[SpuResult]:
"""
Convert ES hits to SpuResult list.
Args:
es_hits: List of ES hit dictionaries (with _id, _score, _source)
max_score: Maximum score (unused, kept for compatibility)
Returns:
List of SpuResult objects
"""
results = []
for hit in es_hits:
source = hit.get('_source', {})
score = hit.get('_score')
# Use original ES score directly (no normalization)
# Handle None score (can happen with certain query types or when score is explicitly null)
if score is None:
relevance_score = 0.0
else:
try:
relevance_score = float(score)
except (ValueError, TypeError):
relevance_score = 0.0
# Extract SKUs
skus = []
skus_data = source.get('skus', [])
if isinstance(skus_data, list):
for sku_entry in skus_data:
sku = SkuResult(
sku_id=str(sku_entry.get('sku_id', '')),
title=sku_entry.get('title'),
price=sku_entry.get('price'),
compare_at_price=sku_entry.get('compare_at_price'),
sku=sku_entry.get('sku'),
stock=sku_entry.get('stock', 0),
options=sku_entry.get('options')
)
skus.append(sku)
# Determine in_stock (any sku has stock > 0)
in_stock = any(sku.stock > 0 for sku in skus) if skus else True
# Build SpuResult
spu = SpuResult(
spu_id=str(source.get('spu_id', '')),
title=source.get('title'),
handle=source.get('handle'),
description=source.get('description'),
vendor=source.get('vendor'),
category=source.get('category'),
tags=source.get('tags'),
price=source.get('min_price'),
compare_at_price=source.get('compare_at_price'),
currency="USD", # Default currency
image_url=source.get('image_url'),
in_stock=in_stock,
skus=skus,
relevance_score=relevance_score
)
results.append(spu)
return results
@staticmethod
def format_facets(
es_aggregations: Dict[str, Any],
facet_configs: Optional[List[Any]] = None
) -> List[FacetResult]:
"""
Format ES aggregations to FacetResult list.
支持：
1. 普通terms聚合
2. range聚合
3. specifications嵌套聚合（按name分组，然后按value聚合）
Args:
es_aggregations: ES aggregations response
facet_configs: Facet configurations (optional)
Returns:
List of FacetResult objects
"""
facets = []
for field_name, agg_data in es_aggregations.items():
display_field = field_name[:-6] if field_name.endswith("_facet") else field_name
# 处理specifications嵌套分面
if field_name == "specifications_facet" and 'by_name' in agg_data:
# specifications嵌套聚合：按name分组，每个name下有value_counts
by_name_agg = agg_data['by_name']
if 'buckets' in by_name_agg:
for name_bucket in by_name_agg['buckets']:
name = name_bucket['key']
value_counts = name_bucket.get('value_counts', {})
values = []
if 'buckets' in value_counts:
for value_bucket in value_counts['buckets']:
value = FacetValue(
value=value_bucket['key'],
label=str(value_bucket['key']),
count=value_bucket['doc_count'],
selected=False
)
values.append(value)
# 为每个name创建一个分面结果
facet = FacetResult(
field=f"specifications.{name}",
label=str(name), # 使用name作为label，如"颜色"、"尺寸"
type="terms",
values=values,
total_count=name_bucket['doc_count']
)
facets.append(facet)
continue
# Handle terms aggregation
if 'buckets' in agg_data:
values = []
for bucket in agg_data['buckets']:
value = FacetValue(
value=bucket['key'],
label=bucket.get('key_as_string', str(bucket['key'])),
count=bucket['doc_count'],
selected=False
)
values.append(value)
facet = FacetResult(
field=display_field,
label=display_field, # Can be enhanced with field labels
type="terms",
values=values,
total_count=agg_data.get('sum_other_doc_count', 0) + len(values)
)
facets.append(facet)
# Handle range aggregation
elif 'buckets' in agg_data and any('from' in b or 'to' in b for b in agg_data['buckets']):
values = []
for bucket in agg_data['buckets']:
range_key = bucket.get('key', '')
value = FacetValue(
value=range_key,
label=range_key,
count=bucket['doc_count'],
selected=False
)
values.append(value)
facet = FacetResult(
field=display_field,
label=display_field,
type="range",
values=values
)
facets.append(facet)
return facets
@staticmethod
def generate_suggestions(
query: str,
results: List[SpuResult]
) -> List[str]:
"""
Generate search suggestions.
Args:
query: Original search query
results: Search results
Returns:
List of suggestion strings (currently returns empty list)
"""
# TODO: Implement suggestion generation logic
return []
@staticmethod
def generate_related_searches(
query: str,
results: List[SpuResult]
) -> List[str]:
"""
Generate related searches.
Args:
query: Original search query
results: Search results
Returns:
List of related search strings (currently returns empty list)
"""
# TODO: Implement related search generation logic
return []