1f6d15fa
 tangwang
重构：SPU级别索引、统一索引架构...
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
|
"""
Result formatter for converting ES internal format to external-friendly format.
"""
from typing import List, Dict, Any, Optional
from .models import ProductResult, VariantResult, 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[ProductResult]:
"""
Convert ES hits to ProductResult list.
Args:
es_hits: List of ES hit dictionaries (with _id, _score, _source)
|
|
1f6d15fa
tangwang
重构：SPU级别索引、统一索引架构...
|
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
|
# Extract variants
variants = []
variants_data = source.get('variants', [])
if isinstance(variants_data, list):
for variant_data in variants_data:
variant = VariantResult(
variant_id=str(variant_data.get('variant_id', '')),
title=variant_data.get('title'),
price=variant_data.get('price'),
compare_at_price=variant_data.get('compare_at_price'),
sku=variant_data.get('sku'),
stock=variant_data.get('stock', 0),
options=variant_data.get('options')
)
variants.append(variant)
# Determine in_stock (any variant has stock > 0)
in_stock = any(v.stock > 0 for v in variants) if variants else True
# Build ProductResult
product = ProductResult(
product_id=str(source.get('product_id', '')),
title=source.get('title'),
handle=source.get('handle'),
description=source.get('description'),
vendor=source.get('vendor'),
product_type=source.get('product_type'),
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,
variants=variants,
relevance_score=relevance_score
)
results.append(product)
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.
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():
# 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=field_name,
label=field_name, # 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=field_name,
label=field_name,
type="range",
values=values
)
facets.append(facet)
return facets
@staticmethod
def generate_suggestions(
query: str,
results: List[ProductResult]
) -> 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[ProductResult]
) -> 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 []
|