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在需要并行请求多个 HTTP 接口的场景中，并且每个接口的查询参数（query）都不同时，可以结合 Python 的 concurrent.futures.ThreadPoolExecutor 来实现高效的并行请求处理。下面是一个示例代码，展示如何为每个接口配置不同的查询参数，并执行并行请求：

import requests
from concurrent.futures import ThreadPoolExecutor, as_completed

定义接口的 URL 列表

urls = [
“http://1”,
“http://2/search”,
“http://3/search”,
“http://4/search”,
“http://5:8/search”
]

定义每个请求的 query 参数

queries = [
“query_1”,
“query_2”,
“query_3”,
“query_4”,
“query_5”
]

请求头

headers = {
“Content-Type”: “application/json”
}

定义请求函数

# 定义请求函数
def post_request(url, query):data = {"serviceVersion": "6","request": {"query": query},"skipCache": True,"serviceId": "game-predicte-intention","fetchResultNodeIds": ["12"]}try:response = requests.post(url, json=data, headers=headers)response.raise_for_status()  # 检查请求是否成功result = response.json().get('result', {})return url, resultexcept requests.RequestException as e:return url, f"Request failed: {e}"

使用多线程进行并行请求

# 使用多线程进行并行请求
def parallel_requests(urls, queries):results = {}with ThreadPoolExecutor(max_workers=len(urls)) as executor:# 提交每个 (url, query) 对应的请求future_to_request = {executor.submit(post_request, url, query): (url, query) for url, query in zip(urls, queries)}for future in as_completed(future_to_request):url, query = future_to_request[future]try:url, result = future.result()results[(url, query)] = resultprint(f"URL: {url}, Query: {query}, Result: {result}")except Exception as e:print(f"Error processing URL {url} with Query {query}: {e}")return results

执行并行请求

result_set = parallel_requests(urls, queries)