File size: 5,572 Bytes
7edb85f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 | from datetime import datetime, timezone
from html import unescape
import re
from typing import Any
import requests
from config import STACKEXCHANGE_API
def _unix_to_iso(timestamp: int | None) -> str | None:
if timestamp is None:
return None
try:
return datetime.fromtimestamp(
timestamp,
tz=timezone.utc,
).isoformat()
except (TypeError, ValueError, OSError):
return None
def _normalize_text(text: str) -> str:
"""
Karşılaştırma için metni sadeleştirir.
"""
return re.sub(
r"[^a-z0-9\s]",
" ",
text.lower(),
)
def _calculate_relevance_score(
query: str,
title: str,
tags: list[str],
) -> int:
"""
Sorgu kelimeleriyle başlık ve etiketler arasındaki
basit eşleşme puanını hesaplar.
"""
ignored_words = {
"the",
"a",
"an",
"is",
"in",
"of",
"to",
"and",
"or",
"python",
"typeerror",
"error",
}
normalized_query = _normalize_text(query)
normalized_title = _normalize_text(title)
query_words = {
word
for word in normalized_query.split()
if len(word) > 2 and word not in ignored_words
}
title_words = set(normalized_title.split())
normalized_tags = {
tag.lower()
for tag in tags
}
title_matches = len(
query_words.intersection(title_words)
)
tag_matches = len(
query_words.intersection(normalized_tags)
)
exact_phrase_bonus = (
5
if normalized_query in normalized_title
else 0
)
return (
title_matches * 3
+ tag_matches * 2
+ exact_phrase_bonus
)
def search_stackoverflow(
query: str,
limit: int = 5,
) -> dict[str, Any]:
"""
Stack Overflow üzerinde verilen sorguyla ilgili
soruları arar.
"""
query = query.strip()
if not query:
raise ValueError(
"Stack Overflow arama sorgusu boş olamaz."
)
limit = max(1, min(limit, 10))
url = f"{STACKEXCHANGE_API}/search/advanced"
# Nihai limitten daha fazla sonuç alıp
# kendi relevance sıralamamızı uyguluyoruz.
candidate_limit = min(limit * 4, 40)
params = {
"site": "stackoverflow",
"q": query,
"sort": "relevance",
"order": "desc",
"pagesize": candidate_limit,
"filter": "withbody",
}
try:
response = requests.get(
url,
params=params,
timeout=20,
)
response.raise_for_status()
except requests.Timeout:
return {
"success": False,
"query": query,
"error": (
"Stack Overflow API isteği zaman aşımına uğradı."
),
}
except requests.RequestException as exc:
return {
"success": False,
"query": query,
"error": (
"Stack Overflow API isteği başarısız oldu: "
f"{exc}"
),
}
try:
data = response.json()
except ValueError:
return {
"success": False,
"query": query,
"error": (
"Stack Overflow API geçerli bir JSON "
"yanıtı döndürmedi."
),
}
if "error_message" in data:
return {
"success": False,
"query": query,
"error_id": data.get("error_id"),
"error_name": data.get("error_name"),
"error": data.get("error_message"),
}
questions = []
for item in data.get("items", []):
owner_data = item.get("owner") or {}
tags = item.get("tags", [])
title = unescape(item.get("title", ""))
relevance_score = _calculate_relevance_score(
query=query,
title=title,
tags=tags,
)
questions.append(
{
"question_id": item.get("question_id"),
"title": title,
"link": item.get("link"),
"score": item.get("score", 0),
"relevance_score": relevance_score,
"answer_count": item.get("answer_count", 0),
"is_answered": item.get("is_answered", False),
"accepted_answer_id": item.get(
"accepted_answer_id"
),
"view_count": item.get("view_count", 0),
"tags": tags,
"owner": owner_data.get("display_name"),
"body": item.get("body"),
"creation_date": _unix_to_iso(
item.get("creation_date")
),
"last_activity_date": _unix_to_iso(
item.get("last_activity_date")
),
}
)
questions.sort(
key=lambda question: (
question["relevance_score"],
question["score"],
),
reverse=True,
)
selected_questions = questions[:limit]
return {
"success": True,
"query": query,
"returned_count": len(selected_questions),
"candidate_count": len(questions),
"has_more": data.get("has_more", False),
"quota_remaining": data.get("quota_remaining"),
"quota_max": data.get("quota_max"),
"backoff": data.get("backoff"),
"questions": selected_questions,
} |