keepa 1.3.10

要求

此库与Python >= 3.8兼容，需要

• numpy

• aiohttp

• matplotlib

• tqdm

当安装了matplotlib时，可以从原始数据中绘制产品历史记录。

与keepa接口需要访问密钥和来自Keepa API的月度订阅。

安装

可以从PyPi安装模块

pip install keepa

源代码也可以从GitHub下载，并使用以下方式安装

cd keepa
pip install .

简要示例

import keepa
accesskey = 'XXXXXXXXXXXXXXXX' # enter real access key here
api = keepa.Keepa(accesskey)

# Single ASIN query
products = api.query('B0088PUEPK') # returns list of product data

# Plot result (requires matplotlib)
keepa.plot_product(products[0])

使用异步的简要示例

以下是一个示例，使用keepa.AsyncKeepa类获取产品并绘制其价格和报价历史记录。

>>> import asyncio
>>> import keepa
>>> product_parms = {'author': 'jim butcher'}
>>> async def main():
...     key = '<REAL_KEEPA_KEY>'
...     api = await keepa.AsyncKeepa().create(key)
...     return await api.product_finder(product_parms)
>>> asins = asyncio.run(main())
>>> asins
['B000HRMAR2',
 '0578799790',
 'B07PW1SVHM',
...
 'B003MXM744',
 '0133235750',
 'B01MXXLJPZ']

使用异步Keepa接口查询产品，产品ASIN为'B0088PUEPK'。

>>> import asyncio
>>> import keepa
>>> async def main():
...     key = '<REAL_KEEPA_KEY>'
...     api = await keepa.AsyncKeepa().create(key)
...     return await api.query('B0088PUEPK')
>>> response = asyncio.run(main())
>>> response[0]['title']
'Western Digital 1TB WD Blue PC Internal Hard Drive HDD - 7200 RPM,
SATA 6 Gb/s, 64 MB Cache, 3.5" - WD10EZEX'

详细示例

导入接口并建立与服务器的连接

import keepa
accesskey = 'XXXXXXXXXXXXXXXX' # enter real access key here
api = keepa.Keepa(accesskey)

单个ASIN查询

products = api.query('059035342X')

# See help(api.query) for available options when querying the API

您也可以使用async/await的keepa

import keepa
accesskey = 'XXXXXXXXXXXXXXXX' # enter real access key here
api = await keepa.AsyncKeepa.create(accesskey)

单个ASIN查询（异步）

products = await api.query('059035342X')

从列表中查询多个ASIN

asins = ['0022841350', '0022841369', '0022841369', '0022841369']
products = api.query(asins)

从numpy数组中查询多个ASIN

asins = np.asarray(['0022841350', '0022841369', '0022841369', '0022841369'])
products = api.query(asins)

产品是包含产品数据的列表，每个成功结果来自Keepa服务器。每个条目都是一个包含与Amazon相同产品数据的字典。

# Available keys
print(products[0].keys())

# Print ASIN and title
print('ASIN is ' + products[0]['asin'])
print('Title is ' + products[0]['title'])

原始数据包含在每个产品结果中。原始数据以字典形式存储，每个键与其相关的时间历史记录相匹配。

# Access new price history and associated time data
newprice = products[0]['data']['NEW']
newpricetime = products[0]['data']['NEW_time']

# Can be plotted with matplotlib using:
import matplotlib.pyplot as plt
plt.step(newpricetime, newprice, where='pre')

# Keys can be listed by
print(products[0]['data'].keys())

如果已安装matplotlib，还可以从模块中绘制产品历史。

keepa.plot_product(products[0])

您可以使用offers参数获取ASIN（或多个ASIN）的报价历史。有关详细信息，请参阅请求产品文档。

products = api.query(asins, offers=20)
product = products[0]
offers = product['offers']

# each offer contains the price history of each offer
offer = offers[0]
csv = offer['offerCSV']

# convert these values to numpy arrays
times, prices = keepa.convert_offer_history(csv)

# for a list of active offers, see
indices = product['liveOffersOrder']

# with this you can loop through active offers:
indices = product['liveOffersOrder']
offer_times = []
offer_prices = []
for index in indices:
    csv = offers[index]['offerCSV']
    times, prices = keepa.convert_offer_history(csv)
    offer_times.append(times)
    offer_prices.append(prices)

# you can aggregate these using np.hstack or plot at the history individually
import matplotlib.pyplot as plt
for i in range(len(offer_prices)):
    plt.step(offer_times[i], offer_prices[i])
plt.show()

如果您计划进行大量并发查询，您可能希望使用wait=False参数来加快查询速度。

products = await api.query('059035342X', wait=False)

>>> import keepa
>>> key = '<REAL_KEEPA_KEY>'
>>> api = keepa.Keepa(key)
>>> response = api.query('B0088PUEPK', offers=20)
>>> product = response[0]
>>> buybox_info = product['buyBoxUsedHistory']
>>> df = keepa.process_used_buybox(buybox_info)
               datetime         user_id         condition  isFBA
0   2022-11-02 16:46:00  A1QUAC68EAM09F   Used - Like New   True
1   2022-11-13 10:36:00  A18WXU4I7YR6UA  Used - Very Good  False
2   2022-11-15 23:50:00   AYUGEV9WZ4X5O   Used - Like New  False
3   2022-11-17 06:16:00  A18WXU4I7YR6UA  Used - Very Good  False
4   2022-11-17 10:56:00   AYUGEV9WZ4X5O   Used - Like New  False
..                  ...             ...               ...    ...
115 2023-10-23 10:00:00   AYUGEV9WZ4X5O   Used - Like New  False
116 2023-10-25 21:14:00  A1U9HDFCZO1A84   Used - Like New  False
117 2023-10-26 04:08:00   AYUGEV9WZ4X5O   Used - Like New  False
118 2023-10-27 08:14:00  A1U9HDFCZO1A84   Used - Like New  False
119 2023-10-27 12:34:00   AYUGEV9WZ4X5O   Used - Like New  False

贡献

通过以开发模式安装此存储库来为此存储库做出贡献，方法是使用fork此存储库

git clone https://github.com/<USERNAME>/keepa
pip install -e .[test]

然后，您可以添加您的功能或提交您的错误修复，然后运行您的单元测试

pytest

单元测试将自动强制执行最低代码覆盖率标准。

接下来，为了确保您的代码符合最低代码风格标准，运行

pre-commit run --all-files

最后，从您的fork创建拉取请求，我将确保对其进行审查。

致谢

此Python模块由Alex Kaszynski和几位贡献者编写，基于Marius Johann（Keepa的首席执行官）编写的Java代码。Java源代码可在keepacom/api_backend找到。

许可证

Apache许可证，请参阅许可证文件。工作归功于Alex Kaszynski和Marius Johann。