Model Algorithm Research based on Python Fast API

Authors

  • Junqiao Chen

DOI:

https://doi.org/10.54691/fse.v3i9.5591

Keywords:

Python; Fast API; Algorithm Model.

Abstract

In recent years, the application of Python programming language in developing web services has gained significant attention, with FASTAPI emerging as a prominent framework for its rapid development and efficient performance. This paper delves into the realm of model algorithm research, leveraging the capabilities of Python's FASTAPI framework. Through this study, we explore the integration of advanced algorithms within the context of web-based applications. By focusing on the seamless amalgamation of algorithmic processes with FASTAPI's structure, we aim to demonstrate the feasibility and advantages of utilizing this combination in various research and practical scenarios. Coupled with illustrative examples, this paper highlights the potential of Python FASTAPI as a robust platform for driving model algorithm research across diverse domains.

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References

ShunpeiYamaguchi;Motoki Nagano;Shunpei Ohira;Ritsuko Oshima;Jun Oshima;Takuya Fujihashi; Shunsuke Saruwatari;Takashi Watanabe. Web Services for Collaboration Analysis with IoT Badges[J]. IEEE Access,2022,Vol.10: 1.

Priya Bansal;Abdelkader Ouda.Study on Integration of FastAPI and Machine Learning for Continuous Authentication of Behavioral Biometrics[A].2022 International Symposium on Networks, Computers and Communications (ISNCC)[C],2022.

Jinbao Song;Jiahui Cai;Ran Li;Yanan Li.Design and Implementation of Scientific Research Achievement Transformation System[A].2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA)[C],2023.

WEBER, ANDREW S; D'AMATO, DANIELLE; ATKINSON, BENJAMIN K.PYTHON REGIUS.[J]. Herpetological Review,2022,Vol.53(4): 632.

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Published

2023-09-21

Issue

Section

Articles

How to Cite

Chen, J. (2023). Model Algorithm Research based on Python Fast API. Frontiers in Science and Engineering, 3(9), 7-10. https://doi.org/10.54691/fse.v3i9.5591