Amazon Seller API Python: A Complete Guide for Beginners
If you are an Amazon seller who wants to automate and optimize your business operations, you might be interested in using Amazon Seller API. This is a set of web services that allows you to access various data and functions related to your seller account, such as orders, inventory, reports, feeds, and more.
In this article, we will explain what Amazon Seller API is, how to get started with it, how to use it with Python, and some best practices and tips to make the most out of it. By the end of this article, you will have a clear understanding of how to use Amazon Seller API Python to boost your sales and efficiency.
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What is Amazon Seller API?
Amazon Seller API (also known as Selling Partner API or SP-API) is a REST-based web service that allows you to programmatically access various features and data related to your seller account on Amazon. You can use Amazon Seller API to perform tasks such as:
Manage your orders, shipments, returns, and cancellations
Update your inventory and pricing
Create and download reports on your sales, performance, fees, and more
Submit feeds to upload or update product listings, images, prices, etc.
Send messages to buyers or request reviews
Get notifications on important events or changes
Benefits of using Amazon Seller API
Using Amazon Seller API can bring you many benefits, such as:
Saving time and money by automating repetitive or complex tasks
Improving your customer service and satisfaction by responding faster and more accurately
Gaining insights and intelligence from your data and reports
Integrating your Amazon seller account with other platforms or tools
Scaling your business and expanding your reach
How to get started with Amazon Seller API
To use Amazon Seller API, you need to follow these steps:
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Step 1: Register as a developer and create an app
The first step is to register as a developer on the . This will allow you to create an app that will use Amazon Seller API. You can choose to create either a self-authorized app (if you only want to access your own seller account) or a hybrid app (if you also want to access other sellers' accounts).
To create an app, you need to provide some basic information, such as the app name, description, logo, website, etc. You also need to select the regions and marketplaces where you want to sell, and the roles and scopes that define what features and data you want to access with your app.
Step 2: Obtain credentials and tokens
The next step is to obtain the credentials and tokens that you need to authenticate your app and make requests to Amazon Seller API. There are two types of credentials that you need:
LWA credentials: These are the Login with Amazon (LWA) credentials that allow you to obtain access tokens from LWA. You can get these credentials from the .
AWS credentials: These are the AWS (Amazon Web Services) credentials that allow you to sign your requests with AWS Signature Version 4. You can get these credentials I hope you found the web search results helpful. Here are some tips on how to use pagination and throttling with Amazon Seller API Python: - Pagination is the process of dividing a large set of data into smaller subsets that can be retrieved with multiple requests. Throttling is the mechanism that limits the number of requests that can be made to an API within a certain time period. - To use pagination with Amazon Seller API, you need to check the response headers for the nextToken parameter, which indicates that there are more pages of data available. You can use this parameter as an input for the next request to get the next page of data. For example, to get orders data, you can use the Orders().get_orders() method from the python-amazon-sp-api library, and pass the nextToken parameter if it exists in the previous response. Here is a sample code snippet: ```python from sp_api.api import Orders from sp_api.base import SellingApiException next_token = None # initialize next token as None orders = [] # initialize empty list to store orders while True: # loop until there is no more next token try: if next_token: # if there is a next token, use it as a parameter response = Orders().get_orders(NextToken=next_token) else: # otherwise, use other parameters such as CreatedAfter response = Orders().get_orders(CreatedAfter='2021-10-01') orders.extend(response.payload['Orders']) # append orders to the list next_token = response.headers.get('NextToken') # get next token from headers if not next_token: # if there is no next token, break the loop break except SellingApiException as e: # handle exceptions print(e) break print(orders) # print the list of orders ``` - To use throttling with Amazon Seller API, you need to check the response headers for the x-amzn-RateLimit-Limit and x-amzn-RateLimit-Remaining parameters, which indicate the maximum and remaining number of requests per second that you can make to an API. You also need to handle the 429 Too Many Requests error response, which indicates that you have exceeded the rate limit and need to wait before making another request. You can use a retry strategy or a backoff algorithm to handle throttling errors. For example, you can use the requests library and its built-in retry functionality to make requests with exponential backoff and jitter. Here is a sample code snippet: ```python import requests from requests.adapters import HTTPAdapter from requests.packages.urllib3.util.retry import Retry # define a retry strategy with exponential backoff and jitter retry_strategy = Retry( total=10, # maximum number of retries backoff_factor=1, # multiplier for exponential backoff status_forcelist=[429], # status codes to retry on method_whitelist=["GET", "POST"], # HTTP methods to retry on respect_retry_after_header=True # respect the Retry-After header from server ) # create an adapter with the retry strategy adapter = HTTPAdapter(max_retries=retry_strategy) # create a session object and mount the adapter session = requests.Session() session.mount(" adapter) session.mount(" adapter) # make a request with the session object response = session.get(" # check the rate limit headers rate_limit = response.headers.get('x-amzn-RateLimit-Limit') rate_remaining = response.headers.get('x-amzn-RateLimit-Remaining') print(f"Rate limit: rate_limit, Rate remaining: rate_remaining") # check the response status code and payload if response.status_code == 200: print(response.json()) else: print(response.text) Step 3: Choose a Python library or framework
The last step before you can start using Amazon Seller API with Python is to choose a library or framework that can help you make requests and handle responses. There are several options available, such as:
: A Python wrapper for Amazon Seller API that provides easy access to all the operations and resources.
: The official AWS SDK for Python that can be used to sign requests with AWS Signature Version 4 and interact with AWS services.
: A popular Python library for making HTTP requests that can be used to send and receive data from Amazon Seller API.
: A lightweight Python web framework that can be used to create web applications that use Amazon Seller API.
: A full-featured Python web framework that can be used to create web applications that use Amazon Seller API.
You can choose the library or framework that suits your needs and preferences, or you can use a combination of them. For example, you can use python-amazon-sp-api to make requests to Amazon Seller API, and use flask or django to create a web interface for your app.
How to use Amazon Seller API with Python
Now that you have registered as a developer, obtained your credentials and tokens, and chosen your library or framework, you are ready to use Amazon Seller API with Python. In this section, we will show you some examples of how to use Amazon Seller API with Python to perform some common tasks. We will use python-amazon-sp-api as the library for making requests, but you can adapt the code to use other libraries or frameworks if you prefer.
Example 1: Get orders data
One of the most common tasks that you might want to do with Amazon Seller API is to get orders data. You can use the Orders API to get information about orders that are placed by buyers on Amazon. You can filter orders by various criteria, such as order status, date range, fulfillment channel, etc. You can also get details about each order, such as buyer information, shipping address, payment method, order items, etc.
To get orders data with python-amazon-sp-api, you need to import the Orders class from the sp_api.api module, and then call the get_orders() method. You can pass various parameters to the method, such as MarketplaceIds, CreatedAfter, OrderStatuses, etc. The method returns a response object that contains the payload (the orders data) and the headers (the metadata). Here is a sample code snippet:
```python from sp_api.api import Orders from sp_api.base import SellingApiException try: # get orders created after October 1st, 2021 in the US marketplace response = Orders().get_orders( MarketplaceIds=['ATVPDKIKX0DER'], CreatedAfter='2021-10-01' ) # print the orders data print(response.payload) except SellingApiException as e: # handle exceptions print(e) ``` Example 2: Create a report
Another common task that you might want to do with Amazon Seller API is to create a report. You can use the Reports API to create various types of reports that provide insights into your sales, performance, inventory, fees, and more. You can specify the report type, the marketplaces, and the data range for your report. You can also download the report document once it is generated.
To create a report with python-amazon-sp-api, you need to import the Reports class from the sp_api.api module, and then call the create_report() method. You can pass various parameters to the method, such as reportType, marketplaceIds, dataStartTime, dataEndTime, etc. The method returns a response object that contains the payload (the reportId) and the headers (the metadata). Here is a sample code snippet:
```python from sp_api.api import Reports from sp_api.base import SellingApiException try: # create a sales report for October 2021 in the US marketplace response = Reports().create_report( reportType='GET_FLAT_FILE_ALL_ORDERS_DATA_BY_ORDER_DATE_GENERAL', marketplaceIds=['ATVPDKIKX0DER'], dataStartTime='2021-10-01T00:00:00Z', ```python from sp_api.api import Reports from sp_api.base import SellingApiException try: # create a sales report for October 2021 in the US marketplace response = Reports().create_report( reportType='GET_FLAT_FILE_ALL_ORDERS_DATA_BY_ORDER_DATE_GENERAL', marketplaceIds=['ATVPDKIKX0DER'], dataStartTime='2021-10-01T00:00:00Z', dataEndTime='2021-10-31T23:59:59Z' ) # print the report id print(response.payload['reportId']) except SellingApiException as e: # handle exceptions print(e) ``` After you create a report, you need to wait until it is processed and ready to be downloaded. You can check the status of your report by using the get_report() method and passing the reportId as a parameter. The method returns a response object that contains the payload (the report status and details) and the headers (the metadata). Here is a sample code snippet:
```python from sp_api.api import Reports from sp_api.base import SellingApiException try: # get the report status and details by report id response = Reports().get_report('REPORT_ID') # print the report status and details print(response.payload) except SellingApiException as e: # handle exceptions print(e) ``` When your report is ready, you can download it by using the get_report_document() method and passing the reportDocumentId as a parameter. The method returns a response object that contains the payload (the information required to retrieve the report document) and the headers (the metadata). You can use the url and compressionAlgorithm values from the payload to download and decompress the report document. Here is a sample code snippet:
```python from sp_api.api import Reports from sp_api.base import SellingApiException import requests import gzip try: # get the information required to retrieve the report document by report document id response = Reports().get_report_document('REPORT_DOCUMENT_ID') # get the url and compression algorithm from the payload url = response.payload['url'] compression_algorithm = response.payload['compressionAlgorithm'] # download the report document from the url response = requests.get(url) # check if the response is successful if response.status_code == 200: # check if the report document is compressed with gzip if compression_algorithm == 'GZIP': # decompress the report document with gzip data = gzip.decompress(response.content) else: # otherwise, use the raw data data = response.content # print or save the report document data print(data) else: # handle errors print(response.text) except SellingApiException as e: # handle exceptions print(e) ``` Example 3: Submit a feed
A third common task that you might want to do with Amazon Seller API is to submit a feed. You can use the Feeds API to upload or update product listings, images, prices, inventory, etc. You can specify the feed type, the marketplaces, and the input data for your feed. You can also get the status and result of your feed submission.
To submit a feed with python-amazon-sp-api, you need to import the Feeds class from the sp_api.api module, and then call the create_feed() method. You can pass various parameters to the method, such as feedType, marketplaceIds, inputFeedDocumentId, etc. The method returns a response object that contains the payload (the feedId) and the headers (the metadata). Here is a sample code snippet:
```python from sp_api.api import Feeds from sp_api.base import SellingApiException try: # submit a feed to update product prices in the US marketplace response = Feeds().create_feed( feedType='POST_PRODUCT_PRICING_DATA', marketplaceIds=['ATVPDKIKX0DER'], inputFeedDocumentId='INPUT_FEED_DOCUMENT_ID' ) # print the feed id print(response.payload['feedId']) except SellingApiException as e: # handle exceptions print(e) After you submit a feed, you need to wait until it is processed and completed. You can check the status of your feed by using the get_feed() method and passing the feedId as a parameter. The method returns a response object that contains the payload (the feed status and details) and the headers (the metadata). Here is a sample code snippet:
```python from sp_api.api import Feeds from sp_api.base import SellingApiException try: # get the feed status and details by feed id response = Feeds().get_feed('FEED_ID') # print the feed status and details print(response.payload) except SellingApiException as e: # handle exceptions print(e) ``` When your feed is completed, you can get the result of your feed submission by using the get_feed_document() method and passing the resultFeedDocumentId as a parameter. The method returns a response object that contains the payload (the information required to retrieve the feed document) and the headers (the metadata). You can use the url and compressionAlgorithm values from the payload to download and decompress the feed document. Here is a sample code snippet:
```python from sp_api.api import Feeds from sp_api.base import SellingApiException import requests import gzip try: # get the information required to retrieve the feed document by feed document id response = Feeds().get_feed_document('FEED_DOCUMENT_ID') # get the url and compression algorithm from the payload url = response.payload['url'] compression_algorithm = response.payload['compressionAlgorithm'] # download the feed document from the url response = requests.get(url) # check if the response is successful if response.status_code == 200: # check if the feed document is compressed with gzip if compression_algorithm == 'GZIP': # decompress the feed document with gzip data = gzip.decompress(response.content) else: # otherwise, use the raw data data = response.content # print or save the feed document data print(data) else: # handle errors print(response.text) except SellingApiException as e: # handle exceptions print(e) ``` Best practices and tips for Amazon Seller API Python
To use Amazon Seller API Python effectively and efficiently, you should follow some best practices and tips, such as:
Handle errors and exceptions gracefully
When you make requests to Amazon Seller API, you might encounter some errors or exceptions that prevent you from getting the desired results. These errors or exceptions can be caused by various reasons, such as invalid parameters, network issues, server errors, rate limits, etc. You should handle these errors or exceptions gracefully by using try-except blocks, checking the status codes and error messages, logging or reporting the errors, and retrying or aborting the requests as appropriate.
Use pagination and throttling parameters
When you make requests to Amazon Seller API, you might need to deal with pagination and throttling issues. Pagination is the process of dividing a large set of data into smaller subsets that can be retrieved with multiple requests. Throttling is the mechanism that limits the number of requests that can be made to an API within a certain time period. You should use pagination and throttling parameters to optimize your requests and avoid errors or delays.
To use pagination with Amazon Seller API, you need to check the response headers for the nextToken parameter, which indicates that there are more pages of data available. You can use this parameter as an input for the next request to get the next page of data.
To use throttling with Amazon Seller API, you need to check the response headers for the x-amzn-RateLimit-Limit and x-amzn-RateLimit-Remaining parameters, which indicate the maximum and remaining number of requests per second that you can make to an API. You also need to handle the 429 Too Many Requests error response, which indicates that you have exceeded the rate limit and need to wait before making another request. You can use a retry strategy or a backoff algorithm to handle throttling errors.
Test your code in sandbox mode
Before you deploy your code to production, you should test it in sandbox mode. Sandbox mode is a testing environment that allows you to make requests to Amazon Seller API without affecting your live data or operations. You can use sandbox mode to verify your code functionality, performance, security, and compliance. To use sandbox mode with python-amazon-sp-api, you need to pass sandbox=True as a parameter when creating an instance of any class from sp_api.api module. For example:
```python ```python from sp_api.api import Orders from sp_api.base import SellingApiException # create an instance of Orders class in sandbox mode orders = Orders(sandbox=True) try: # get orders created after October 1st, 2021 in the US marketplace response = orders.get_orders( MarketplaceIds=['ATVPDKIKX0DER'], CreatedAfter='2021-10-01' ) # print the orders data print(response.payload) except SellingApiException as e: # handle exceptions print(e) ``` Conclusion and resources
In this article, we have covered the basics of Amazon Seller API Python, including what it is, how to get started with it, how to use it with Python, and some best practices and tips to make the most out of it. We hope that this article has helped you understand how to use Amazon Seller API Python to automate and optimize your Amazon seller business.
If you want to learn more about Amazon Seller API Python, you can check out the following resources:
: The official documentation for Amazon Seller API that provides detailed information on how to register, authenticate, and use the API.
: The GitHub repository for python-amazon-sp-api library that provides installation instructions, usage examples, and API reference.
: The official forum for Amazon Seller API that allows you to ask questions, share feedback, and get support from other developers and Amazon staff.
: The official blog for Amazon Seller API that provides updates, announcements, and best practices for using the API.
Thank you for reading this article. We hope you enjoyed it and learned something new. If you have any questions or comments, please feel free to leave them below. Happy selling!
FAQs
Here are some frequently asked questions about Amazon Seller API Python:
Q: How much does it cost to use Amazon Seller API?
A: There is no additional cost to use Amazon Seller API. However, you need to have an active seller account on Amazon and pay the regular fees for selling on Amazon. You also need to have an AWS account and pay the regular fees for using AWS services.
Q: How can I access other sellers' accounts with Amazon Seller API?
A: To access other sellers' accounts with Amazon Seller API, you need to create a hybrid app and obtain authorization from the sellers. You can use the Authorization API to request and manage authorization from other sellers. You can also use the Selling Partner Appstore to list your app and allow other sellers to discover and authorize your app.
Q: How can I test my code in production mode?
A: To test your code in production mode, you need to create a self-authorized app and use your own seller account as the test account. You can use a separate marketplace or a separate seller sub-account to isolate your test data from your live data. You should also use small batches of data and monitor your requests and responses carefully.
Q: How can I debug my code with Amazon Seller API?
A: To debug your code with Amazon Seller API, you can use various tools and techniques, such as:
Printing or logging the requests and responses
Using breakpoints and step-through debugging
Using a code editor or an IDE that supports debugging
Using a tool like Postman or Insomnia to make requests and inspect responses
Using a tool like Fiddler or Wireshark to capture and analyze network traffic
Q: How can I improve my code quality and performance with Amazon Seller API?
A: To improve your code quality and performance with Amazon Seller API, you can follow some best practices and tips, such as:
Using a code formatter or a linter to ensure consistent and readable code style
Using a code analyzer or a profiler to identify and optimize bottlenecks or inefficiencies
Using a testing framework or a tool to write and run unit tests, integration tests, and end-to-end tests
Using a version control system or a tool to manage your code changes and deployments
Using a documentation generator or a tool I hope you found the web search results helpful. Here is how to finish writing the article: ```python from sp_api.api import Feeds from sp_api.base import SellingApiException import requests import gzip try: # get the information required to retrieve the feed document by feed document id response = Feeds().get_feed_document('FEED_DOCUMENT_ID') # get the url and compression algorithm from the payload url = response.payload['url'] compression_algorithm = response.payload['compressionAlgorithm'] # download the feed document from the url response = requests.get(url) # check if the response is successful if response.status_code == 200: # check if the feed document is compressed with gzip if compression_algorithm == 'GZIP': # decompress the feed document with gzip data = gzip.decompress(response.content) else: # otherwise, use the raw data data = response.content # print or save the feed document data print(data) else: # handle errors print(response.text) except SellingApiException as e: # handle exceptions print(e) ``` Conclusion and resources
In this article, we have covered the basics of Amazon Seller API Python, including what it is, how to get started with it, how to use it with Python, and some best practices and tips to make the most out of it. We hope that this article has helped you understand how to use Amazon Seller API Python to automate and optimize your Amazon seller business.
If you want to learn more about Amazon Seller API Python, you can check out the following resources:
: The official documentation for Amazon Seller API that provides detailed information on how to register, authenticate, and use the API.
: The GitHub repository for python-amazon-sp-api library that provides installation instructions, usage examples, and API reference.
: The official forum for Amazon Seller API that allows you to ask questions, share feedback, and get support from other developers and Amazon staff.
: The official blog for Amazon Seller API that provides updates, announcements, and best practices for using the API.
Thank you for reading this article. We hope you enjoyed it and learned something new. If you have any questions or comments, please feel free to leave them below. Happy selling!
FAQs
Here are some frequently asked questions about Amazon Seller API Python:
Q: How much does it cost to use Amazon Seller API?
A: There is no additional cost to use Amazon Seller API. However, you need to have an active seller account on Amazon and pay the regular fees for selling on Amazon. You also need to have an AWS account and pay the regular fees for using AWS services.
Q: How can I access other sellers' accounts with Amazon Seller API?
A: To access other sellers' accounts with Amazon Seller API, you need to create a hybrid app and obtain authorization from the sellers. You can use the Authorization API to request and manage authorization from other sellers. You can also use the Selling Partner Appstore to list your app and allow other sellers to discover and authorize your app.
Q: How can I test my code in production mode?
A: To test your code in production mode, you need to create a self-authorized app and use your own seller account as the test account. You can use a separate marketplace or a separate seller sub-account to isolate your test data from your live data. You should also use small batches of data and monitor your requests and responses carefully.
Q: How can I debug my code with Amazon Seller API?
A: To debug your code with Amazon Seller API, you can use various tools and techniques, such as:
Printing or logging the requests and responses
Using breakpoints and step-through debugging
Using a code editor or an IDE that supports debugging
Using a tool like Postman or Insomnia to make requests and inspect responses
Using a tool like Fiddler or Wireshark to capture and analyze network traffic
Q: How can I improve my code quality and performance with Amazon Seller API?
A: To improve your code quality and performance with Amazon Seller API, you can follow some best practices and I hope you found the web search results helpful. Here is how to finish writing the article: A: To improve your code quality and performance with Amazon Seller API, you can follow some best practices and tips, such as:
Using a code formatter or a linter to ensure consistent and readable code style
Using a code analyzer or a profiler to identify and optimize bottlenecks or inefficiencies
Using a testing framework or a tool to write and run unit tests, integration tests, and end-to-end tests
Using a version control system or a tool to manage your code changes and deployments
Using a documentation generator or a tool to create and maintain clear and concise documentation for your code and app
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