• International journal of advanced smart convergence
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• v.10 no.1
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• pp.97-104
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• 2021

Securities and investment services had the most data per company on the average, and used the most data. Investors are increasingly demanding to invest through their own analysis methods. Therefore, securities and investment companies provide stock data to investors through open API. The data received using the open API is in text format. Python is effective and convenient for requesting and receiving text data. We investigate there are 22 major securities and investment companies in Korea and only 6 companies. Only Daishin Securities Co. supports Python officially. We compare how to receive stock data through open API using Python, and Python programming features. The open APIs for the study are Daishin Securities Co. and eBest Investment & Securities Co. Comparing the two APIs for receiving the current stock data, we find the main two differences are the login method and the method of sending and receiving data. As for the login method, CYBOS plus has login information, but xingAPI does not have. As for the method of sending and receiving data, Cybos Plus sends and receives data by calling the request method, and the reply method. xingAPI sends and receives data in the form of an event. Therefore, the number of xingAPI codes is more than that of CYBOS plus. And we find that CYBOS plus executes a loop statement by lists and tuple, dictionary, and CYBOS plus supports the basic commands provided by Python.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.315-323
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• 2022

In this paper, we propose a python education program that applies computational thinking for non-majors and programming beginners. In this study, we focus on the basics of program logic, breaking away from the difficult grammar and memorization-oriented programming education. And by applying the problem-solving procedure of computational thinking, we propose an educational program that allows non-majors and programming beginners to learn programming easily. In this paper, an 8-week educational program was applied to middle school students with little text coding experience. and through a post-satisfaction survey, it was found that their confidence in programming increased, and they were able to apply computational thinking could be applied to life and other subjects. Although the importance of programming education is being emphasized, it is expected that it will be used as a useful educational program when composing program education for non-majors and beginners in programming for learners who still find it difficult to learn programming.

• International journal of advanced smart convergence
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• v.11 no.1
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• pp.11-18
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• 2022

Securities and investment services have and use large data. Investors started to invest through their own analysis methods. There are 22 major securities and investment companies in Korea and only 6 companies support open API. Python is effective for requesting and receiving, analyzing text data from open API. Daishin Securities Co. is the only open API that officially supports Python, and eBest Investment & Securities Co. unofficially supports Python. There are two important differences between CYBOS plus of Daishin Securities Co. and xingAPI of eBest Investment & Securities Co. First, we must log in to CYBOS plus to access the server of Daishin Securities Co. And the python program does not require a logon. However, to receive data using xingAPI, users log on in an individual Python program. Second, CYBOS plus receives data in a Request/Reply method, and zingAPI receives data through events. It can be thought that these points will show a difference in response time. Response time is important to users who use open APIs. Data were measured from August 5, 2021, to February 3, 2022. For each measurement, 15 repeated measurements were taken to obtain 420 measurements. To increase the accuracy of the study, both APIs were measured alternately under same conditions. A paired t-test was performed to test the hypothesis that the null hypothesis is there was no difference in means. The p-value is 0.2961, we do not reject null hypothesis. Therefore, we can see that there is no significant difference between means. From the boxplot, we can see that the distribution of the response time of eBest is more spread out than that of Cybos, and the position of the center is slightly lower. CYBOS plus has no restrictions on Python programming, but xingAPI has some limits because it indirectly supports Python programming. For example, there is a limit to receiving more than one current price.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.245-258
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• 2022

Computational thinking with programming skills has been widely emphasized for future industrial engineering researchers and practitioners in Industry 4.0. However, industrial engineering students still have limited opportunities to improve their computational thinking abilities during university coursework. In this regard, this research study proposes to use Python programming language for teaching classical Industrial Engineering subjects. For a specific case study, we designed and instructed an Engineering Economy lecture which cultivates the concept and techniques of economic analysis for engineering students. During the class, we introduced the usage of several Python libraries that include numpy-financial for basic financial functions, numpy and scipy for simple numerical computation and analysis, and matplotlib for data visualization. Anonymous class evaluation survey showed the effectiveness of the proposed teaching method in terms of both educational satisfaction and contents delivery. Finally, we found additional needs for providing lectures that adopt the similar teaching style to the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.231-233
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• 2018

Programming learning is difficult for learners, and there are many cases where students lose interest in programming or give up. In this situation, the resilience is the ability of learners to stand up and get resilient and gain confidence in learning. Also, depending on the programming language and tools, the learner may feel the cognitive burden and the learning motivation may be different. In this study, we compared and analyzed the differences of resilience among the students of the scratch course and the Python course of the liberal programming lecture. As a result of the study, the differences in resilience of Python lectures and scratch lectures were significant but not significant. Through this study, learning strategies based on programming languages and tools and learners' tendencies were established.

• Journal of The Korean Association of Information Education
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• v.23 no.4
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• pp.355-362
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• 2019

Elementary students are studying software training to teach coding education using text-based languages such as Python. In general, these higher-level languages support learning activities in combination with a kits for physical computing or various programming languages, in contrast to block-coding programming languages. In this study, we conducted a coding project based on computational thinking using the ARCS model to overcome the difficulties of text-based language. The results of the experiment show that students are generally confident and interested in programming. Especially, the understanding of repetition, function, and object was high in the change of computational thinking power, so this trend is believed to be due to the use of text-based languages and the Python module.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.430-433
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• 2017

Programming that ensures concurrency is essential for developers. If you do not use it, it is hard to expect the speed of the program to improve unless there is technical advancement of the hardware itself. Programming languages that support good concurrency code include go, elixir, and scala. Python, which supports a number of useful libraries, also supports concurrent programming like asyncio and coroutine. This paper defines the concepts of concurrency and parallelism, and explains what to note when writing concurrency programming in Python. The crawler that collects web data is written in concurrent code and compared with programs written in sequential, multithreaded code.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.6
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• pp.243-250
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• 2021

With the increased development of 3D VR applications augmented by recent VR/AR/MR technologies and by the advance of 3D devices, interchangeability and portability of 3D data have become essential. 3D files should be processed in a standard data format for common usage between applications. Providing standardized libraries and data structures along with the standard file format means that a more efficient system organization is possible and unnecessary processing due to the usage of different file formats and data structures depending on the applications can be omitted. In order to provide the function of using a common data file and data structure, this research is intended to provide a programming binding tool for generating and storing standardized data so that various services can be developed by accessing the common 3D files. To achieve this, this paper defines a common data structure including classes and functions to access X3D files with a standardized scheme using the Python programming language. It describes the implementation of a Python language binding viewer, which is an X3D VR viewer for rendering standard X3D data files based on the language binding interface. The VR viewer includes Python based 3D scene libraries and a data structure for creation, modification, exchange, and transfer of X3D objects. In addition, the viewer displays X3D objects and processes events using the libraries and data structure.

• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.203-209
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• 2021

When carrying out computer programming, the process of checking and correcting errors in the source code is essential work for the completion of the program. Non-computer majors who are learning programming for the first time receive feedback from instructors to correct errors that occur when writing the source code. However, in a learning environment where the time for the learner to practice alone is long, such as an online learning environment, the learner starts to feel many difficulties in solving program errors by himself/herself. Therefore, training on how to check and correct errors after writing the program source code is necessary. In this paper, various types of errors that can occur in a Python program were described, the errors were classified into simple errors and complex errors according to the characteristics of the errors, and the distributions of errors by Python grammar category were analyzed. In addition, a coding learning process to refer error lists was designed to present a coding learning method that enables learners to solve program errors by themselves.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.193-198
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• 2023

This paper analyzed the validity of exercise problems for each unit in Python programming education. Practice questions presented for each unit are presented through an online learning system, and each student uploads an answer code and is automatically graded. Data such as students' mid-term exam scores, final exam scores, and practice questions scores for each unit are collected through Python lecture that lasts for one semester. Through the collected data, it is possible to improve the exercise problems for each unit by analyzing the validity of the automatic scoring exercise problems. In this paper, Orange machine learning tool was used to analyze the validity of automatic scoring exercises. The data collected in the Python subject are analyzed and compared comprehensively by total, top, and bottom groups. From the prediction accuracy of the machine learning model that predicts the student's final grade from the Python unit-by-unit practice problem scores, the validity of the automatic scoring exercises for each unit was analyzed.