How to obtain the shipping region data of the overseas version? What are the methods and ways?

Data acquisition of overseas shipping areas in cross-border e-commerce and system development

In the development of cross-border e-commerce platforms or systems, accurate data on overseas shipments is crucial. This article provides some ideas on how to obtain and integrate these data.

Recently, a netizen asked a question on a technical question-and-answer platform, hoping to obtain regional data similar to Taobao's global shopping (including countries, provinces, and cities) so that it can be directly applied to its system.

Some developers suggest that first clarify the needs: whether to fully consistent data with specific e-commerce platforms (such as Taobao), or just a database covering major regions around the world is needed.

If only a common global regional database is needed, it is recommended to search for relevant data sets on open source platforms such as GitHub. Keywords such as "global regions data" or "world countries cities data" can help you find open source data provided in CSV or JSON format, making it easy to import into the system.

However, if it is necessary to be exactly consistent with the data of a specific e-commerce platform, there is no ready-made solution. At this time, you can consider the following two ways:

1. Data crawling: Get data from the target e-commerce platform by writing a crawler program. However, it should be noted that this method requires compliance with relevant laws and regulations and website robots agreements to avoid copyright infringement or violation of the terms of use.

2. Purchase professional data services: Some data providers provide high-quality global regional data and ensure data accuracy and timeliness. Purchasing such services can save development time and resources, but requires corresponding fees.

Which method to choose depends on your technical capabilities, time budget and requirements for data accuracy. For projects with limited resources or low requirements for data accuracy, open source data sets on GitHub are good choices; for data that requires high precision and compatible with specific platforms, it is recommended to consider data crawling or purchasing professional data services.

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