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In this repo, I will be comparing the performance of async and sync programming in Python. I will be using the
requestslibrary to make HTTP requests to five endpoints of World Bank's api to get metadata info of countries, capitals, population, land square, military expenditure, military personnel information. -
When tried to get data of countries, for each info more than 5 requests are made because there are more than 250 countries and in each query 50 are returned (can be increased but not on purpose to achieve a bottleneck).
- When a usual programming is applied, every request is run sequentially which means each awaits another to be finished.
- When async programming is applied, every request is run concurrently which means each does not await another to be finished. That reduces the time elapsed to get the whole results.
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Here are the real execution results for 10 runs for each.
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