在电商数据分析和竞品监控领域，获取亚马逊商品详情页的实时数据是一项核心需求。本文将详细介绍如何通过亚马逊 API 接口开发来获取这些有价值的数据，包括接入流程、认证机制和代码实现。
亚马逊 API 简介
亚马逊提供了多种 API 接口，其中最常用的是亚马逊产品广告 API（Amazon Product Advertising API）和亚马逊市场卖家 API（Amazon Marketplace Web Service, MWS）。本文主要围绕产品广告 API 展开，该 API 允许开发者访问亚马逊商品信息、价格、评论等数据。
接入准备工作
在开始开发前，需要完成以下准备工作：
- 注册账户（Associates Program）
- 获取 API 密钥（Access Key 和 Secret Key）
- 注册 AWS 账户（如果需要）
- 了解 API 调用限制和费用（部分功能需要付费）
认证机制
亚马逊 API 使用 HMAC-SHA256 算法进行请求签名认证，主要包含以下步骤：
- 构建规范化请求字符串
- 创建待签名字符串
- 计算签名
- 将签名添加到请求参数中
下面是一个完整的 Python 实现，展示如何构建和发送请求到亚马逊 API：
import hashlib
import hmac
import time
import urllib.parse
import requests
from datetime import datetime
class AmazonAPIClient:
def __init__(self, access_key, secret_key, associate_tag, region='US'):
"""初始化亚马逊API客户端"""
self.access_key = access_key
self.secret_key = secret_key
self.associate_tag = associate_tag
self.region = region
# 根据不同区域设置端点
self.endpoints = {
'US': 'webservices.amazon.com',
'CA': 'webservices.amazon.ca',
'UK': 'webservices.amazon.co.uk',
'DE': 'webservices.amazon.de',
'FR': 'webservices.amazon.fr',
'IT': 'webservices.amazon.it',
'ES': 'webservices.amazon.es',
'JP': 'webservices.amazon.co.jp',
'CN': 'webservices.amazon.cn',
'IN': 'webservices.amazon.in'
}
self.endpoint = self.endpoints.get(region, self.endpoints['US'])
def get_timestamp(self):
"""获取当前时间戳，格式为ISO 8601"""
return datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%SZ')
def sign_request(self, params):
"""使用HMAC-SHA256算法对请求进行签名"""
# 添加必需的参数
params['AWSAccessKeyId'] = self.access_key
params['AssociateTag'] = self.associate_tag
params['Timestamp'] = self.get_timestamp()
params['Version'] = '2013-08-01'
# 按照字典序排序参数
sorted_params = sorted(params.items(), key=lambda x: x[0])
# 构建规范化请求字符串
canonical_query_string = '&'.join([f"{k}={urllib.parse.quote_plus(str(v))}" for k, v in sorted_params])
# 创建待签名字符串
string_to_sign = f"GET\n{self.endpoint}\n/onca/xml\n{canonical_query_string}"
# 计算签名
signature = hmac.new(
self.secret_key.encode('utf-8'),
string_to_sign.encode('utf-8'),
hashlib.sha256
).digest()
# 将签名转换为Base64编码
signature = urllib.parse.quote_plus(signature.hex())
# 添加签名到参数中
params['Signature'] = signature
return params
def get_item_info(self, asin, response_group='ItemAttributes,Offers,Images,Reviews'):
"""获取单个商品的详细信息"""
params = {
'Operation': 'ItemLookup',
'ItemId': asin,
'ResponseGroup': response_group
}
# 签名请求
signed_params = self.sign_request(params)
# 构建请求URL
query_string = '&'.join([f"{k}={urllib.parse.quote_plus(str(v))}" for k, v in signed_params.items()])
url = f"https://{self.endpoint}/onca/xml?{query_string}"
# 发送请求
try:
response = requests.get(url)
response.raise_for_status()
return response.text
except requests.exceptions.RequestException as e:
print(f"请求出错: {e}")
return None
def search_items(self, keywords, search_index='All', response_group='ItemAttributes,Offers,Images'):
"""搜索商品"""
params = {
'Operation': 'ItemSearch',
'Keywords': keywords,
'SearchIndex': search_index,
'ResponseGroup': response_group
}
# 签名请求
signed_params = self.sign_request(params)
# 构建请求URL
query_string = '&'.join([f"{k}={urllib.parse.quote_plus(str(v))}" for k, v in signed_params.items()])
url = f"https://{self.endpoint}/onca/xml?{query_string}"
# 发送请求
try:
response = requests.get(url)
response.raise_for_status()
return response.text
except requests.exceptions.RequestException as e:
print(f"请求出错: {e}")
return None
# 使用示例
if __name__ == "__main__":
# 替换为你的API凭证
ACCESS_KEY = "YOUR_ACCESS_KEY"
SECRET_KEY = "YOUR_SECRET_KEY"
ASSOCIATE_TAG = "YOUR_ASSOCIATE_TAG"
# 创建API客户端
client = AmazonAPIClient(ACCESS_KEY, SECRET_KEY, ASSOCIATE_TAG)
# 获取单个商品信息
asin = "B07HGGYFZ6" # 示例ASIN
item_info = client.get_item_info(asin)
print(f"商品 {asin} 的信息:\n{item_info}")
# 搜索商品
search_keywords = "wireless headphones"
search_results = client.search_items(search_keywords)
print(f"搜索关键词 '{search_keywords}' 的结果:\n{search_results}")
解析 API 响应数据
亚马逊 API 返回的是 XML 格式的数据，我们可以使用 Python 的 ElementTree 库来解析：
import xml.etree.ElementTree as ET
class AmazonResponseParser:
def __init__(self):
# 定义命名空间
self.ns = {
'a': 'http://webservices.amazon.com/AWSECommerceService/2013-08-01'
}
def parse_item_info(self, xml_response):
"""解析商品信息响应"""
root = ET.fromstring(xml_response)
# 检查是否有错误
error = root.find('.//a:Error', self.ns)
if error is not None:
error_code = error.find('a:Code', self.ns).text
error_message = error.find('a:Message', self.ns).text
return {'error': f"{error_code}: {error_message}"}
# 提取商品信息
item = root.find('.//a:Item', self.ns)
if item is None:
return {'error': 'No item found'}
result = {
'asin': item.find('a:ASIN', self.ns).text,
'title': item.find('.//a:Title', self.ns).text,
'url': item.find('.//a:DetailPageURL', self.ns).text,
'price': None,
'currency': None,
'image_url': None
}
# 提取价格信息
offer = item.find('.//a:Offer', self.ns)
if offer is not None:
price_element = offer.find('.//a:FormattedPrice', self.ns)
if price_element is not None:
result['price'] = price_element.text
# 提取货币符号
currency_element = offer.find('.//a:CurrencyCode', self.ns)
if currency_element is not None:
result['currency'] = currency_element.text
# 提取主图URL
image = item.find('.//a:LargeImage', self.ns)
if image is not None:
image_url = image.find('a:URL', self.ns)
if image_url is not None:
result['image_url'] = image_url.text
# 提取评分信息
reviews = item.find('.//a:CustomerReviews', self.ns)
if reviews is not None:
rating = reviews.find('.//a:AverageRating', self.ns)
if rating is not None:
result['average_rating'] = rating.text
review_count = reviews.find('.//a:TotalReviews', self.ns)
if review_count is not None:
result['review_count'] = review_count.text
return result
def parse_search_results(self, xml_response):
"""解析搜索结果响应"""
root = ET.fromstring(xml_response)
# 检查是否有错误
error = root.find('.//a:Error', self.ns)
if error is not None:
error_code = error.find('a:Code', self.ns).text
error_message = error.find('a:Message', self.ns).text
return {'error': f"{error_code}: {error_message}"}
# 提取搜索结果
items = root.findall('.//a:Item', self.ns)
if not items:
return {'error': 'No items found'}
results = []
for item in items:
result = {
'asin': item.find('a:ASIN', self.ns).text,
'title': item.find('.//a:Title', self.ns).text,
'url': item.find('.//a:DetailPageURL', self.ns).text,
'price': None,
'currency': None,
'image_url': None
}
# 提取价格信息
offer = item.find('.//a:Offer', self.ns)
if offer is not None:
price_element = offer.find('.//a:FormattedPrice', self.ns)
if price_element is not None:
result['price'] = price_element.text
# 提取货币符号
currency_element = offer.find('.//a:CurrencyCode', self.ns)
if currency_element is not None:
result['currency'] = currency_element.text
# 提取主图URL
image = item.find('.//a:MediumImage', self.ns)
if image is not None:
image_url = image.find('a:URL', self.ns)
if image_url is not None:
result['image_url'] = image_url.text
results.append(result)
# 提取总结果数
total_results = root.find('.//a:TotalResults', self.ns)
if total_results is not None:
return {
'total_results': int(total_results.text),
'items': results
}
return {'items': results}
# 使用示例
if __name__ == "__main__":
# 假设我们已经有了API响应
sample_response = """
<ItemLookupResponse xmlns="http://webservices.amazon.com/AWSECommerceService/2013-08-01">
<OperationRequest>
<HTTPHeaders>
<Header Name="UserAgent" Value="python-requests/2.25.1" />
</HTTPHeaders>
<RequestId>12345678-1234-1234-1234-123456789012</RequestId>
<Arguments>
<Argument Name="Operation" Value="ItemLookup" />
<Argument Name="ResponseGroup" Value="ItemAttributes,Offers,Images,Reviews" />
<Argument Name="ItemId" Value="B07HGGYFZ6" />
<Argument Name="AWSAccessKeyId" Value="AKIAIOSFODNN7EXAMPLE" />
<Argument Name="AssociateTag" Value="yourtag-20" />
<Argument Name="Timestamp" Value="2023-01-01T12:00:00Z" />
<Argument Name="Version" Value="2013-08-01" />
<Argument Name="Signature" Value="EXAMPLE" />
</Arguments>
<RequestProcessingTime>0.0422150000000000</RequestProcessingTime>
</OperationRequest>
<Items>
<Request>
<IsValid>True</IsValid>
<ItemLookupRequest>
<IdType>ASIN</IdType>
<ItemId>B07HGGYFZ6</ItemId>
<ResponseGroup>ItemAttributes,Offers,Images,Reviews</ResponseGroup>
<VariationPage>All</VariationPage>
</ItemLookupRequest>
</Request>
<Item>
<ASIN>B07HGGYFZ6</ASIN>
<DetailPageURL>https://www.amazon.com/dp/B07HGGYFZ6</DetailPageURL>
<ItemAttributes>
<Binding>Electronics</Binding>
<Brand>ExampleBrand</Brand>
<Color>Black</Color>
<Department>Electronics</Department>
<IsAdultProduct>false</IsAdultProduct>
<Label>ExampleLabel</Label>
<ListPrice>
<Amount>12999</Amount>
<CurrencyCode>USD</CurrencyCode>
<FormattedPrice>$129.99</FormattedPrice>
</ListPrice>
<Manufacturer>ExampleManufacturer</Manufacturer>
<Model>EXAMPLE-MODEL</Model>
<NumberOfItems>1</NumberOfItems>
<PackageDimensions>
<Height Units="hundredths-inches">800</Height>
<Length Units="hundredths-inches">600</Length>
<Weight Units="hundredths-pounds">200</Weight>
<Width Units="hundredths-inches">200</Width>
</PackageDimensions>
<PackageQuantity>1</PackageQuantity>
<PartNumber>EXAMPLE-PN</PartNumber>
<ProductGroup>Electronics</ProductGroup>
<ProductTypeName>ELECTRONICS</ProductTypeName>
<Publisher>ExamplePublisher</Publisher>
<ReleaseDate>2019-01-01</ReleaseDate>
<Size>Standard</Size>
<Studio>ExampleStudio</Studio>
<Title>Example Product Title</Title>
<Warranty>1 Year Limited Warranty</Warranty>
</ItemAttributes>
<Offers>
<TotalOffers>2</TotalOffers>
<TotalOfferPages>1</TotalOfferPages>
<MoreOffersUrl>https://www.amazon.com/gp/offer-listing/B07HGGYFZ6</MoreOffersUrl>
<Offer>
<OfferAttributes>
<Condition>New</Condition>
</OfferAttributes>
<OfferListing>
<Price>
<Amount>12999</Amount>
<CurrencyCode>USD</CurrencyCode>
<FormattedPrice>$129.99</FormattedPrice>
</Price>
<Availability>Usually ships within 24 hours</Availability>
<AvailabilityAttributes>
<AvailabilityType>now</AvailabilityType>
<MinimumHours>0</MinimumHours>
<MaximumHours>0</MaximumHours>
</AvailabilityAttributes>
<IsEligibleForSuperSaverShipping>true</IsEligibleForSuperSaverShipping>
<IsEligibleForPrime>true</IsEligibleForPrime>
<OfferListingId>EXAMPLE-OFFER-LISTING-ID</OfferListingId>
</OfferListing>
</Offer>
</Offers>
<Images>
<LargeImage>
<URL>https://m.media-amazon.com/images/I/81abcdefg-h.jpg</URL>
<Height Units="pixels">500</Height>
<Width Units="pixels">500</Width>
</LargeImage>
<MediumImage>
<URL>https://m.media-amazon.com/images/I/81abcdefg-h._AC_SX300.jpg</URL>
<Height Units="pixels">300</Height>
<Width Units="pixels">300</Width>
</MediumImage>
<SmallImage>
<URL>https://m.media-amazon.com/images/I/81abcdefg-h._AC_SX150.jpg</URL>
<Height Units="pixels">150</Height>
<Width Units="pixels">150</Width>
</SmallImage>
</Images>
<CustomerReviews>
<IFrameURL>https://www.amazon.com/reviews/iframe?akid=AKIAIOSFODNN7EXAMPLE&alinkCode=xm2&asin=B07HGGYFZ6&atag=yourtag-20&encoding=UTF8&collapsed=0&format=embedded&language=en_US&showViewpoints=1&sortBy=recent</IFrameURL>
<AverageRating>4.8 out of 5 stars</AverageRating>
<TotalReviews>245</TotalReviews>
</CustomerReviews>
</Item>
</Items>
</ItemLookupResponse>
"""
parser = AmazonResponseParser()
result = parser.parse_item_info(sample_response)
print("解析结果:")
for key, value in result.items():
print(f"{key}: {value}")
实际应用案例
下面是一个简单的应用示例，展示如何使用上述代码获取商品信息并进行分析：
import time
import csv
import os
from datetime import datetime
from amazon_api_client import AmazonAPIClient
from amazon_response_parser import AmazonResponseParser
class AmazonPriceTracker:
def __init__(self, access_key, secret_key, associate_tag, region='US'):
"""初始化价格追踪器"""
self.client = AmazonAPIClient(access_key, secret_key, associate_tag, region)
self.parser = AmazonResponseParser()
self.tracked_items = {}
self.data_dir = "amazon_data"
# 创建数据目录
if not os.path.exists(self.data_dir):
os.makedirs(self.data_dir)
def add_item(self, asin, name=None):
"""添加要追踪的商品"""
# 获取商品信息
xml_response = self.client.get_item_info(asin)
if not xml_response:
print(f"无法获取商品 {asin} 的信息")
return False
# 解析响应
item_info = self.parser.parse_item_info(xml_response)
# 检查是否有错误
if 'error' in item_info:
print(f"获取商品信息时出错: {item_info['error']}")
return False
# 使用商品名称或提供的名称
item_name = name or item_info['title']
# 添加到追踪列表
self.tracked_items[asin] = {
'name': item_name,
'price_history': []
}
print(f"已添加商品 '{item_name}' (ASIN: {asin}) 到追踪列表")
return True
def track_price(self, asin):
"""追踪单个商品的价格"""
if asin not in self.tracked_items:
print(f"商品 {asin} 不在追踪列表中")
return False
# 获取商品信息
xml_response = self.client.get_item_info(asin)
if not xml_response:
print(f"无法获取商品 {asin} 的信息")
return False
# 解析响应
item_info = self.parser.parse_item_info(xml_response)
# 检查是否有错误
if 'error' in item_info:
print(f"获取商品信息时出错: {item_info['error']}")
return False
# 记录价格
current_price = item_info.get('price')
current_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
if current_price:
self.tracked_items[asin]['price_history'].append({
'time': current_time,
'price': current_price
})
print(f"已记录商品 '{self.tracked_items[asin]['name']}' 的价格: {current_price}")
return True
else:
print(f"无法获取商品 '{self.tracked_items[asin]['name']}' 的价格")
return False
def track_all(self):
"""追踪所有商品的价格"""
success_count = 0
for asin in self.tracked_items:
if self.track_price(asin):
success_count += 1
return success_count
def export_data(self, asin=None):
"""导出价格历史数据到CSV文件"""
if asin:
if asin not in self.tracked_items:
print(f"商品 {asin} 不在追踪列表中")
return False
# 导出单个商品的数据
item = self.tracked_items[asin]
filename = f"{self.data_dir}/{asin}_{item['name'][:50].replace(' ', '_')}.csv"
with open(filename, 'w', newline='') as csvfile:
fieldnames = ['时间', '价格']
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
for record in item['price_history']:
writer.writerow({
'时间': record['time'],
'价格': record['price']
})
print(f"已导出商品 '{item['name']}' 的价格历史到 {filename}")
return True
else:
# 导出所有商品的数据
for asin, item in self.tracked_items.items():
if item['price_history']:
filename = f"{self.data_dir}/{asin}_{item['name'][:50].replace(' ', '_')}.csv"
with open(filename, 'w', newline='') as csvfile:
fieldnames = ['时间', '价格']
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
for record in item['price_history']:
writer.writerow({
'时间': record['time'],
'价格': record['price']
})
print(f"已导出商品 '{item['name']}' 的价格历史到 {filename}")
return True
def run_scheduled_tracking(self, interval_seconds=3600, max_iterations=None):
"""运行定时追踪任务"""
iteration = 0
while max_iterations is None or iteration < max_iterations:
print(f"\n=== 开始第 {iteration + 1} 轮追踪 ===")
success_count = self.track_all()
print(f"=== 完成第 {iteration + 1} 轮追踪，成功记录 {success_count} 个商品的价格 ===")
# 导出数据
self.export_data()
iteration += 1
# 如果不是最后一轮，则等待指定时间
if max_iterations is None or iteration < max_iterations:
print(f"\n等待 {interval_seconds} 秒后进行下一轮追踪...")
time.sleep(interval_seconds)
# 使用示例
if __name__ == "__main__":
# 替换为你的API凭证
ACCESS_KEY = "YOUR_ACCESS_KEY"
SECRET_KEY = "YOUR_SECRET_KEY"
ASSOCIATE_TAG = "YOUR_ASSOCIATE_TAG"
# 创建价格追踪器
tracker = AmazonPriceTracker(ACCESS_KEY, SECRET_KEY, ASSOCIATE_TAG)
# 添加要追踪的商品
tracker.add_item("B07HGGYFZ6", "Example Product 1")
tracker.add_item("B07HGGYFZ7", "Example Product 2")
# 运行一次追踪
tracker.track_all()
# 导出数据
tracker.export_data()
# 或者，运行定时追踪任务（每小时一次，运行3次）
# tracker.run_scheduled_tracking(interval_seconds=3600, max_iterations=3)
最佳实践与注意事项
-
API 调用限制：亚马逊对 API 调用有严格的限制，免费账户通常每分钟最多 1 个请求，每小时最多 60 个请求。商业账户有更高的限制。
-
请求频率控制：实现请求队列和重试机制，避免超出限制导致账户被封禁。
-
数据缓存：对于不经常变化的数据，如商品标题和描述，可以设置合理的缓存策略。
-
错误处理：完善的错误处理机制，包括网络错误、API 错误和超时处理。
-
数据存储：考虑使用数据库存储大量数据，方便后续分析和查询。
-
遵守亚马逊政策：在使用 API 获取的数据时，要遵守亚马逊的服务条款，特别是关于数据使用和展示的限制。
结语
通过亚马逊 API 接口开发，我们可以获取商品详情页的实时数据，这对于电商数据分析、价格监控和竞品分析都非常有价值。本文详细介绍了接入流程、认证机制和代码实现，希望能帮助开发者顺利完成亚马逊 API 的集成开发。
记住，在实际应用中要合理控制 API 调用频率，做好数据处理和存储，同时遵守亚马逊的服务条款，确保应用的稳定性和合规性。
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