如何从Python Requests的JSON响应中提取库存与SKU数据？

你可以通过以下步骤从返回的JSON数据中提取目标字段，并将其存入Pandas DataFrame：

步骤说明 #

1. 定位变体数据：从响应的metadata -> input_products[0] -> variants路径获取所有产品变体数组
2. 提取目标字段：遍历每个变体对象，提取sku和inventory_quantity字段
3. 构建DataFrame：将提取的字段数据转换为DataFrame格式，方便后续可视化

修改后的完整代码 #

import requests
import pandas as pd
import json

url = "https://rebuyengine.com/api/v1/custom/id/37597? key=c30f8541bcce849905613e432e4c7c9170829adf&limit=1&url=https%3A%2F%2Fspearmintlove.com%2Fproducts%2Frylee-cru-beach-bucket-hat-laurel-plaid&shopify_product_ids=7599681372332&shopify_variant_ids=&shopify_collection_ids=0&shopify_order_ids=&metafields=yes&variant_metafields=yes&uuid=3f8fc02e-3476-4583-80b4-85f9d6670e2e&cache_key=1678199511"

payload={}
headers = {
'authority': 'rebuyengine.com',
'accept': '*/*',
'accept-language': 'en-GB,en-US;q=0.9,en;q=0.8',
'origin': 'https://spearmintlove.com',
'referer': 'https://spearmintlove.com/',
'sec-ch-ua': '"Google Chrome";v="111", "Not(A:Brand";v="8", "Chromium";v="111"',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"Windows"',
'sec-fetch-dest': 'empty',
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'cross-site',
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)  Chrome/111.0.0.0 Safari/537.36'
}

response = requests.request("GET", url, headers=headers, data=payload)
r = response.json()

# 提取目标字段并构建DataFrame
inventory_data = []
# 先判断input_products是否有数据，避免索引错误
if r.get('metadata', {}).get('input_products'):
    variants = r['metadata']['input_products'][0]['variants']
    for variant in variants:
        inventory_data.append({
            'sku': variant['sku'],
            'inventory_quantity': variant['inventory_quantity']
        })

# 转换为DataFrame
df = pd.DataFrame(inventory_data)
print(df)

输出示例 #

sku  inventory_quantity
0  RCBeachBucketHatLaurelPlaidS/M                   0
1  RCBeachBucketHatLaurelPlaidM/L                   1

处理后你可直接使用df进行后续可视化操作。

内容的提问来源于stack exchange，提问作者cm917