掌握USDA食品数据API分页获取完整营养信息教程

import requests import JSon import pandas as pd  def get_all_usda_foods(query_term, api_key, page_size=200):     """     从USDA食品数据API分页获取所有符合查询条件的食品数据。      参数:     query_term (str): 查询的食品名称或关键词。     api_key (str): USDA API的授权密钥。     page_size (int): 每页返回的结果数量，最大为200。      返回:     list: 包含所有食品数据字典的列表，如果发生错误则返回None。     """     all_foods = []     # 构造初始URL，设置每页大小     base_url = f"https://api.nal.usda.gov/fdc/v1/foods/search?api_key={api_key}&query={query_term}&pageSize={page_size}"      with requests.Session() as session:  # 使用requests.Session保持连接，提高效率         try:             # 第一次请求，获取总页数             print(f"Fetching initial page for query: '{query_term}'")             response = session.get(base_url, timeout=10)             response.raise_for_status()  # 检查HTTP请求是否成功             api_response = response.json()              # 检查API响应结构，确保'foods'和'totalPages'存在             if "foods" not in api_response or "totalPages" not in api_response:                 print("Error: 'foods' or 'totalPages' not found in initial API response.")                 return None              all_foods.extend(api_response["foods"])             total_pages = api_response["totalPages"]             print(f"Total pages to fetch: {total_pages}")              # 从第二页开始循环获取所有数据             for page_num in range(2, total_pages + 1):                 print(f"Fetching page {page_num}/{total_pages}...")                 page_url = f"{base_url}&pageNumber={page_num}"                 page_response = session.get(page_url, timeout=10)                 page_response.raise_for_status()                 page_api_response = page_response.json()                  if "foods" in page_api_response:                     all_foods.extend(page_api_response["foods"])                 else:                     print(f"Warning: 'foods' not found in response for page {page_num}.")                     break # 如果某一页没有'foods'，可能表示数据结束或API行为异常          except requests.exceptions.HTTPError as http_err:             print(f"HTTP error occurred: {http_err} - Status Code: {http_err.response.status_code}")             return None         except requests.exceptions.ConnectionError as conn_err:             print(f"Connection error occurred: {conn_err}")             return None         except requests.exceptions.Timeout as timeout_err:             print(f"Request timed out: {timeout_err}")             return None         except requests.exceptions.RequestException as req_err:             print(f"An unexpected request error occurred: {req_err}")             return None         except json.JSONDecodeError as json_err:             print(f"Failed to decode JSON response: {json_err}")             print(f"Response content: {response.text[:500]}...") # 打印部分响应内容辅助调试             return None         except Exception as e:             print(f"An unexpected error occurred: {e}")             return None      return all_foods  # 使用示例 if __name__ == "__main__":     API_KEY = "YOUR_USDA_API_KEY" # 替换为你的USDA API密钥     search_term = "raw fruit" # 示例查询词      print(f"Starting data retrieval for '{search_term}'...")     food_items_data = get_all_usda_foods(search_term, API_KEY)      if food_items_data:         print(f"nSuccessfully retrieved {len(food_items_data)} food items.")          # 将数据转换为Pandas DataFrame并导出到excel         processed_data = []         for item in food_items_data:             row = {"Description": item.get("description", "N/A")}             for nutrient in item.get("foodNutrients", []):                 nutrient_name = nutrient.get("nutrientName")                 nutrient_value = nutrient.get("value")                 if nutrient_name and nutrient_value is not None:                     row[nutrient_name] = nutrient_value             processed_data.append(row)          df = pd.DataFrame(processed_data)          # 清理列名，处理重复营养素（如果存在）         # 这里只是一个简单的处理，实际应用中可能需要更复杂的逻辑         df = df.loc[:,~df.columns.duplicated()]           output_filename = f'{search_term.replace(" ", "_")}_nutritional_facts.xlsx'         df.to_excel(output_filename, index=False)         print(f"Data exported to {output_filename}")     else:         print("Failed to retrieve food data.")