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| import time, csv, os, re, json, threading
from collections import Counter
from concurrent.futures import ThreadPoolExecutor, as_completed
import requests
from lxml import html
from datetime import datetime
import psutil
HEADERS = {"User-Agent": "Mozilla/5.0 ..."}
MAX_WORKERS = 5
REQUESTS_PER_SECOND = 5
BATCH_WRITE_SIZE = 500
PROGRESS_REPORT_INTERVAL = 100
REQUEST_TIMEOUT = (5, 15)
MAX_RETRIES = 2
class RateLimiter:
def __init__(self, rate):
self.rate = rate
self.tokens = rate
self.last_update = time.time()
self.lock = threading.Lock()
def acquire(self):
with self.lock:
now = time.time()
self.tokens = min(self.rate, self.tokens + (now - self.last_update) * self.rate)
self.last_update = now
if self.tokens >= 1:
self.tokens -= 1
return True
return (1 - self.tokens) / self.rate
rate_limiter = RateLimiter(REQUESTS_PER_SECOND)
def check_ids(ids):
invalid, dup = [], Counter(ids)
duplicates = {i:c for i,c in dup.items() if c>1}
for idx, i in enumerate(ids, 1):
if not i.startswith("HMDB"):
invalid.append((idx, i))
return invalid, duplicates
def clean_text(s):
s = re.sub(r'[\x00-\x1F\u200B-\u200D\uFEFF]', '', s or '')
s = re.sub(r'\s+', ' ', s)
return s.strip()
def fetch(hmdb_id):
url = f"https://hmdb.ca/metabolites/{hmdb_id}"
wait = rate_limiter.acquire()
if wait is not True:
time.sleep(wait)
rate_limiter.acquire()
resp = requests.get(url, headers=HEADERS, timeout=REQUEST_TIMEOUT)
resp.raise_for_status()
return html.fromstring(resp.content)
def parse(tree, hmdb_id):
data = {"HMDB_ID": hmdb_id}
cf = tree.xpath('//th[text()="Chemical Formula"]/following-sibling::td[1]')
data["Chemical_Formula"] = ''.join(cf[0].xpath('.//text()')) if cf else ""
return data
def should_retry(exc, status=None):
import requests as R
if isinstance(exc, R.exceptions.Timeout): return True
if isinstance(exc, R.exceptions.ConnectionError): return True
if isinstance(exc, R.exceptions.HTTPError):
if status in [429, 502, 503, 504]: return True
if status in [404, 400, 403]: return False
return True
return True
def get_with_retry(hmdb_id, retries=MAX_RETRIES):
last = None
for attempt in range(retries):
try:
tree = fetch(hmdb_id)
return parse(tree, hmdb_id)
except requests.exceptions.HTTPError as e:
last, status = e, (e.response.status_code if e.response else None)
if not should_retry(e, status): break
if attempt < retries - 1:
wait = 2 ** attempt
ra = e.response.headers.get('Retry-After') if e.response else None
if ra:
try: wait = max(wait, int(ra))
except: pass
time.sleep(wait)
except Exception as e:
last = e
if not should_retry(e): break
if attempt < retries - 1: time.sleep(2 ** attempt)
print(f"[{hmdb_id}] 重试失败: {last}")
return None
def mem_mb():
try: return psutil.Process().memory_info().rss / 1024 / 1024
except: return 0
def write_csv(rows, file, mode='a'):
cols = [
'HMDB_ID','Common_Name','Description','Synonyms','Chemical_Formula',
'Average_Molecular_Weight','Monoisotopic_Molecular_Weight','IUPAC_Name',
'Traditional_Name','CAS_Registry_Number','SMILES','Kingdom','Super_Class',
'Class','Sub_Class','Direct_Parent','Experimental_Molecular_Properties',
'Predicted_Molecular_Properties','Pathways','Normal_Concentrations',
'Abnormal_Concentrations','Disease_References','Associated_OMIM_IDs',
'KEGG_Compound_ID','PubChem_Compound'
]
exists = os.path.isfile(file)
with open(file, mode, newline='', encoding='utf-8-sig') as f:
w = csv.DictWriter(f, fieldnames=cols, quoting=csv.QUOTE_ALL)
if not exists or mode == 'w': w.writeheader()
w.writerows(rows)
def save_failed(failed, file='失败.txt'):
with open(file, 'w', encoding='utf-8') as f:
for i, err in failed: f.write(f"{i}\t{err}\n")
def save_progress(done, file='progress.json'):
data = {'processed_ids': list(done), 'timestamp': datetime.now().isoformat(), 'count': len(done)}
with open(file, 'w', encoding='utf-8') as f: json.dump(data, f, ensure_ascii=False, indent=2)
def load_progress(file='progress.json'):
if os.path.exists(file):
try:
with open(file, 'r', encoding='utf-8') as f: return set(json.load(f).get('processed_ids', []))
except: pass
return set()
def process_ids(hmdb_ids):
done = load_progress()
remain = [i for i in hmdb_ids if i not in done]
if not remain:
print("所有ID都已处理完成！")
return len(hmdb_ids), 0, []
results, failed = {}, []
total, curr, ok, bad = len(hmdb_ids), len(done), len(done), 0
start = time.time()
with ThreadPoolExecutor(max_workers=MAX_WORKERS) as ex:
fut = {ex.submit(get_with_retry, i): i for i in remain}
for f in as_completed(fut):
i = fut[f]; curr += 1
try:
d = f.result()
if d:
results[i] = d; done.add(i); ok += 1
else:
failed.append((i, "数据获取失败")); bad += 1
except Exception as e:
failed.append((i, str(e))); bad += 1
if curr % PROGRESS_REPORT_INTERVAL == 0 or curr == total:
left = total - curr
pct = curr / total * 100
print(f"进度: {curr}/{total} ({pct:.1f}%) | 剩余: {left} | 成功: {ok} | 失败: {bad} | 内存: {mem_mb():.1f}MB")
if len(results) >= BATCH_WRITE_SIZE:
ordered = []
for _id in hmdb_ids:
if _id in results:
ordered.append(results[_id]); del results[_id]
if ordered: write_csv(ordered, '代谢物数据_最终.csv', 'a')
save_progress(done)
if results:
ordered = []
for _id in hmdb_ids:
if _id in results: ordered.append(results[_id])
if ordered: write_csv(ordered, '代谢物数据_最终.csv', 'a')
if failed: save_failed(failed)
save_progress(done)
return ok, bad, failed
def sort_by_original_order(original_ids, csv_file):
try:
import pandas as pd
df = pd.read_csv(csv_file, encoding='utf-8-sig')
if df.empty or 'HMDB_ID' not in df.columns: return
order = {i: idx for idx, i in enumerate(original_ids)}
df['sort_key'] = df['HMDB_ID'].map(order)
df.sort_values('sort_key').drop('sort_key', axis=1).to_csv(csv_file, index=False, encoding='utf-8-sig')
except ImportError:
print("提示：未安装 pandas，跳过最终排序。")
except Exception as e:
print(f"排序异常: {e}")
def main():
print("="*80); print("HMDB代谢物数据提取工具"); print("="*80)
if not os.path.exists('id.txt'):
print("错误：缺少 id.txt"); input("回车退出..."); return
with open('id.txt', 'r', encoding='utf-8') as f:
ids = f.read().splitlines()
invalid, duplicates = check_ids(ids)
valid = [i for i in ids if i.startswith("HMDB")]
unique = list(dict.fromkeys(valid))
if not os.path.exists('progress.json'):
write_csv([], '代谢物数据_最终.csv', 'w')
ok, bad, failed = process_ids(unique)
print("\n按原始ID顺序整理 CSV...")
sort_by_original_order(unique, '代谢物数据_最终.csv')
print("="*80); print(f"总计: {len(unique)} | 成功: {ok} | 失败: {bad}"); print("输出: 代谢物数据_最终.csv"); print("="*80)
if __name__ == "__main__":
main()
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