Dissertations / Theses on the topic 'Python programming language'

The current trend in computation is one of concurrency and multiprocessors. Large supercomputers have long been eclipsed in popularity by cheaper clusters of small computers. In recent years, desktop processors with multiple cores have become commonplace. A plethora of languages, tools, and techniques for dealing with concurrency already exist. Where concurrency and multiprocessors meet modern, highly dynamic languages, however, is uncharted territory. Traditional distributed systems, however complex, tend to be simplified by assumptions of type consistency. Even in systems where types and not merely instances and primitive objects can be serialised and distributed, it is usually the case that such types are assumed to be static. The Python programming language, as an example of a modern language with highly dynamic types, presents novel challenges, in that classes may be altered at runtime, both through the addition, removal, or modification of attributes such as member variables and methods, and through modifications to the type's inheritance hierarchy. This thesis presents a system called PyRemote which aims to explore some of the issues surrounding type semantics in this environment.<br>Science, Faculty of<br>Computer Science, Department of<br>Graduate

With diminishing gains in processing power from successive generations of hardware development, there is a new focus on using advances in computer science and parallel programming to build faster, more efficient software. As computers trend toward including multiple and multicore processors, parallel computing serves as a promising option for optimizing the next generation of software applications. However, models for implementing parallel programs remain highly opaque due to their reliance on languages such as Fortran, C, and C++. In this paper I investigate Python an option for implementing parallel programming techniques in application development. I analyze the efficiency and accessibility of MPI for Python and IPython Parallel packages by calculating in parallel using a Monte Carlo simulation and comparing their speeds to the sequential calculation. While MPI for Python offers the core functionality of MPI and C-like syntax in Python, IPython Parallel's architecture provides a truly unique model.

L'avvento dell'era digitale ha contribuito allo sviluppo di nuovi settori tecnologici, i quali, per diretta conseguenza, hanno portato alla richiesta di nuove figure professionali capaci di assumere un ruolo chiave nel processo d'innovazione tecnologica. L'aumento di questa richiesta ha interessato particolarmente il settore dello sviluppo del software, a seguito della nascita di nuovi linguaggi di programmazione e nuovi campi a cui applicarli. La componente principale di cui è composto un software, infatti, è il codice sorgente, il quale può essere rappresentato come un archivio di uno o più file testuali contenti una serie d'istruzioni scritte in uno o più linguaggi di programmazione. Nonostante molti di questi vengano utilizzati in diversi settori tecnologici, spesso accade che due o più di questi condividano una struttura sintattica e semantica molto simile. Chiaramente questo aspetto può generare confusione nell'identificazione di questo all'interno di un frammento di codice, soprattutto se consideriamo l'eventualità che non sia specificata nemmeno l'estensione dello stesso file. Infatti, ad oggi, la maggior parte del codice disponibile online contiene informazioni relative al linguaggio di programmazione specificate manualmente. All'interno di questo elaborato ci concentreremo nel dimostrare che l'identificazione del linguaggio di programmazione di un file `generico' di codice sorgente può essere effettuata in modo automatico utilizzando algoritmi di Machine Learning e non usando nessun tipo di assunzione `a priori' sull'estensione o informazioni particolari che non riguardino il contenuto del file. Questo progetto segue la linea dettata da alcune ricerche precedenti basate sullo stesso approccio, confrontando tecniche di estrazione delle features differenti e algoritmi di classificazione con caratteristiche molto diverse, cercando di ottimizzare la fase di estrazione delle features in base al modello considerato.

With the amount of programming languages currently available there is a high risk of confusion anddoubtfulness in aspiring programmers of which to choose. It may be motivating for a beginner tochoose “the perfect language” when starting, to avoid learning multiple languages. This thesiscompares three popular languages on three separate aspects, their syntax, usefulness in differentareas, and performance in terms of speed. Syntax wise the results varied with some aspects beingvery similar across all three languages to completely different in others. In terms of usefulness inspecific areas the languages flexibility allowed them to develop applications in most fields, while beingdominant in different areas. The speed comparison resulted in python being the slowest across alltests, with Java and Javascript (running inside Nodejs) competing for first place.

This thesis is concerned by programming language Python and its suitability of his assignment to the tuition. The work is divided into three dominant parts. The first part describes programming language Python, its elementary characteristics and features. The purpose is to introduce its properties to the reader so that he could estimate if there is point in the deeper concern. There are elements of object-oriented programming in description, too. The second part analyses programming language Python on the basis of ten criteria which are defined considering applicability of the language in preliminary courses of programming. The purpose is to review if the Python is appropriate in these courses. The third part considers the possibilities of the Python tuition at the University of Economics in Prague. The main contribution of the thesis is to give opinion on the fundamental description of the language, to define framework and to pass judgment on the potential chance of use in preliminary courses of programming.

In today’s society computers are getting a much more important role. To get a computer to work as intended it has to be programmed. A computer program is written with programming languages. There is an abundance of programming languages available today and there are many differences and similarities between them. The different languages have their advantages and their disadvantages where some of them are intended for fast performance, some to be cheap on memory usage, and some are developed to be easy to program on. In our thesis we have chosen to compare four of todays most common languages, C, C++, Java and Python. These languages were chosen because we have worked with three of them during our study period (C, C++ and Java). Python was chosen because it is an interpreted language and not a compiled one. It also have a very different syntax compared to the other languages which makes it interesting. Our comparison, which focuses on performance, has its foundation in the tests we have made, but also on results from a research survey that we also made. I this survey forty software developers, from Swedish companies, have participated. The tests we have made measure the languages performance, regarding time, by implementing and running two common algorithms. During these tests vi have also chosen to register the amount of memory these algorithms use during runtime. The results we have extracted from our tests and our survey are compiled, and these results are then analysed to be able to compare the four programming languages to each other. The tests that have been done show that Java is the language that performs best, with C and C ++ second best and then Python performing the worst. Our survey answers, on the other hand, indicates that C and C++ should have outperformed Java.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2017-10-16T11:41:10Z No. of bitstreams: 2 Dissertação - Giovanna Moreno Parizotto - 2017.pdf: 2790011 bytes, checksum: 84424125a05214d9b7536300c92cae6b (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-10-16T11:42:54Z (GMT) No. of bitstreams: 2 Dissertação - Giovanna Moreno Parizotto - 2017.pdf: 2790011 bytes, checksum: 84424125a05214d9b7536300c92cae6b (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Made available in DSpace on 2017-10-16T11:42:54Z (GMT). No. of bitstreams: 2 Dissertação - Giovanna Moreno Parizotto - 2017.pdf: 2790011 bytes, checksum: 84424125a05214d9b7536300c92cae6b (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-09-14<br>In this qualitative research with case study elements, we discuss why the use of notions of structured programming in Python language constituted as a manipulation of the play culture for the teaching of Physics in the first year of the High School, at night. Manipulation in this case, refers us to aspects related to notions of game and characteristics related to the game, recognizing the game as a place of emergency of the ludic culture. This theme is related to the teacher training of the researcher, who seeks to enrich the student's playful culture in which she has greater didactic difficulty. In the course of the research, the researchers find several characteristics of the games during the interventions. This process is discussed as to the characteristics of the philosophical game proposed by Brougère (1998) and also to the typical behaviors of them, considered as primary impulses by Caillois (1990), related to the term game. We also relate corruption characteristics of these primary impulses to the lubricant ludic term.<br>Nesta pesquisa qualitativa com elementos de estudo de caso discutimos por que o uso de noções de programação estruturada em linguagem Python constituiu-se como uma manipulação da cultura lúdica para o ensino de Física no primeiro ano do Ensino Médio noturno. Manipulação neste caso, remete-nos a aspectos ligados a noções de jogo e características relacionadas ao jogos, reconhecendo o jogo como lugar de emergência da cultura lúdica. Tal temática está de encontro a formação docente da pesquisadora, que busca enriquecer a cultura lúdica do alunado no qual possui maior dificuldade didática. No decorrer da pesquisa, os pesquisadores encontram várias características dos jogos durante as intervenções. Tal processo é discutido quanto as características do jogo filosófico propostas por Brougère (1998) e também aos comportamentos típicos dos mesmos, tidos como impulsões primárias por Caillois (1990), relacionado ao termo jogo. Relacionamos ainda características de corrupções destas impulsões primárias ao termo lúdico lúbrico.

For many years symmetry has been a useful concept in the study of the spatial organization of atoms in molecules or solids. The presence of symmetry elements in a given molecular structure gives a valuable information about its properties and chemical behaviour. However, it has been demonstrated that most molecules in nature tend to adopt shapes which are not fully symmetric, presenting small distortions from the ideal symmetric model structures used to rationalize the stereochemical knowledge. Continuous symmetry measures (CSMs) were developed precisely to quantify the amount of asymmetry of a given object by comparing a distorted structure with an ideal symmetric reference. This methodology has been very helpful to classify, for example, the shape of the coordination environment of transition metal atoms in several coordination complexes. In the present thesis, we present an overview of the formalism of CSMs, describing the computational methodologies that had been developed in the past. The main aim of the present thesis is the development of Cosymlib, a Python library englobing all previous algorithms within a unified computational framework that allows a seamless computation of different CSMs for a given molecule using a unified format. Extensive discussion of the advantage of implementing modern programming techniques such as object-oriented programming in the development of a unified computational approach to CSMs will be given in a second methodological chapter. Afterwards, the use of the different tools included in Cosymlib for the symmetry analysis of the molecular structure will be illustrated by applying it to different stereochemical problems related to organometallic coordination complexes, the effect of temperature on the shape of several polyhedral cage molecules and, the effect of temperature and the crystal environment on the shape of phosphate anions.<br>Durant anys, la simetria ha esdevingut una eina molt útil en l’estudi de l’organització d’àtoms i molècules en sòlids. La presencia d’elements de simetria en una estructura molecular dona informació important sobre les seves propietats i el seu comportament químic. Tot i això, s’ha demostrat que la majoria de molècules a la natura tendeixen a tenir formes que no son totalment simètriques, presentant petites distorsions en el model ideal simètric que s’utilitza per entendre l’estereoquímica d’un compost. Les mesures de simetria en continu (CSMs) es van desenvolupar per tal de quantificar amb precisió com d’asimètric pot ser un objecte comparant una estructura distorsionada amb una referencia amb simetria ideal. Fins ara, aquesta metodologia ha estat útil per classificar, per exemple, la forma de l’entorn de coordinació dels metalls de transició en diversos complexes de coordinació. En aquesta tesis es presenta de manera general el formalisme de les CSMs, descrivint els mètodes computacionals que es van desenvolupar en el passat. L’objectiu principal d’aquesta tesi es el desenvolupament del programa Cosymlib, un llibreria escrita en Python que engloba tots els algoritmes anteriors i els unifica en un sol marc que permet dins del mateix programa calcular diferents CSMs per a una mateixa molècula en un sol format. A més a més, en un segon capítol, s’exemplifica l’avantatge de implementat tècniques de programació modernes, com el llenguatge orientat a objectes, en el desenvolupament d’un programa unificat encarat a les CSMs. Posteriorment, l’ús de les diferents eines que inclou el programa Cosymlib per l’anàlisi de simetria d’una estructura molecular s’il·lustrarà aplicant-lo a diferents problemes d’estereoquímica relacionats amb els complexes de coordinació organometàl·lics, l’efecte de la temperatura en la forma d’un conjunt de molècules polièdriques i, en l’efecte de la temperatura i de l’entorn cristal·lí en la forma de l’anió fosfat.

Scientists are trending towards usage of high-level programming languages such as Python. The convenience of these languages often have a performance cost. As the amount of data being processed increases this can make using these languages unfeasible. Parallelism is a means to achieve better performance, but many users are unaware of it, or find it difficult to work with. This thesis presents ParForPy, a means for loop-parallelization to to simplify usage of parallelism in Python for users. Discussion is included for determining when parallelism matches well with the problem. Results are given that indicate that ParForPy is both capable of improving program execution time and perceived to be a simpler construct to understand than other techniques for parallelism in Python.

The Generalized Finite Element Method (GFEM) is a numerical method based on the Partition of Unity (PU) concept and inspired on both the Partition of Unity Method (PUM) and the hp-Cloud method. According to the GFEM, the PU is provided by first-degree Lagragian interpolation functions, defined over a mesh of elements similar to the Finite Element Method (FEM) meshes. In fact, the GFEM can be considered an extension of the FEM to which enrichment functions can be applied in specific regions of the problem domain to improve the solution. This technique has been successfully employed to solve problems presenting discontinuities and singularities, like those that arise in Fracture Mechanics. However, most publications on the method are related to linear analyses. The present thesis is a contribution to the few studies of nonlinear analyses of Solid Mechanics by means of the GFEM. One of its main topics is the derivation of a segment-to-segment generalized contact element based on the mortar method. Material and kinematic nonlinear phenomena are also considered in the numerical models. An Object-Oriented design was developed for the implementation of a GFEM nonlinear analyses framework written in Python programming language. The results validated the formulation and demonstrate the gains and possible drawbacks observed for the GFEM nonlinear approach.<br>O Método dos Elementos Finitos Generalizados (MEFG) é um método numérico baseado no conceito de partição da unidade (PU) e inspirado no Método da Partição da Unidade (MPU) e o método das Nuvens-hp. De acordo com o MEFG, a PU é obtida por meio de funções de interpolação Lagragianas de primeiro grau, definidas sobre uma rede de elementos similar àquela do Método dos Elementos Finitos (MEF). De fato, o MEFG pode ser considerado uma extensão do MEF para a qual se pode aplicar enriquecimentos em regiões específicas do domínio, buscando melhorias na solução. Esta técnica já foi aplicada com sucesso em problemas com descontinuidades e singularidades, como os originários da Mecânica da Fratura. Apesar disso, a maioria das publicações sobre o método está relacionada a análises lineares. A presente tese é uma contribuição aos poucos estudos relacionados a análises não-lineares de Mecânica dos Sólidos por meio do MEFG. Um de seus principais tópicos é o desenvolvimento de um elemento de contato generalizado do tipo segmento a segmento baseado no método mortar. Fenômenos não lineares devidos ao material e à cinemática também são considerados nos modelos numéricos. Um projeto de orientação a objetos para a implementação de uma plataforma de análises não-lineares foi desenvolvido, escrito em linguagem de programação Python. Os resultados validam a formulação e demonstram os ganhos e possíveis desvantagens da abordagem a problemas não lineares por meio do MEFG.

This dissertation undertakes to establish the feasibility of using MyHDL as a basis on which to develop an FPGA-based DSP tool-ow to target CASPER hardware. MyHDL is an open-source package which enables Python to be used as a hardware definition and verification language. As Python is a high-level language, hardware designers can use it to model and simulate designs, without needing detailed knowledge of the underlying hardware. MyHDL has the ability to convert designs to Verilog or VHDL allowing it to integrate into the more traditional design-ow. The CASPER tool- ow exhibits limitations such as design environment instability and high licensing fees. These shortcomings are addressed by MyHDL. To enable CASPER to take advantage of its powerful features, MyHDL is incorporated into a next generation tool-ow which enables high-level designs to be fully simulated and implemented on the CASPER hardware architectures.

Testing code is important, but writing test cases can be time consuming, particularly for beginning programmers who are already struggling to write an implementation. We present TestBuilder, a system for test case generation which uses an SMT solver to generate inputs to reach specified lines in a function, and asks the user what the expected outputs would be for those inputs. The resulting test cases check the correctness of the output, rather than merely ensuring the code does not crash. Further, by querying the user for expectations, TestBuilder encourages the programmer to think about what their code ought to do, rather than assuming that whatever it does is correct. We demonstrate, using mutation testing of student projects, that tests generated by TestBuilder perform better than merely compiling the code using Python’s built-in compile function, although they underperform the tests students write when required to achieve 100% test coverage.

The aim of this thesis is to graphically interpret navigation messages from a prototype of global navigation satellite system. The resulting application is implemented in Python programming language for Windows operating system and follows requests from researchers developing the prototype. Necessary terminology together with graphical user interface programming possibilities of object-oriented language Python is a base for theoretical background of this text. Practical part of this research describes a solution for receiving generated messages from the prototype as well as their storing and filtering into useful information. Further, the design of graphical user interface of the application for prototype interactions and other tools used for its configuration are included.

Programming languages like Python, JavaScript, and Ruby are becoming increasingly popular due to their dynamic capabilities. These languages are often much easier to learn than other, statically type checked, languages such as C++ or Rust. Unfortunately, these dynamic languages come at the cost of losing compile-time optimizations. Python is arguably the most popular language for data scientists and researchers in the artificial intelligence and machine learning communities. As this research becomes increasingly popular, and the problems these researchers face become increasingly computationally expensive, questions are being raised about the performance of languages like Python. Language features found in Python, more specifically dynamic typing and run-time modification of object attributes, preclude common static analysis optimizations that often yield improved performance. This thesis attempts to quantify the cost of dynamic features in Python. Namely, the run-time modification of objects and scope as well as the dynamic type system. We introduce Cannoli, a Python 3.6.5 compiler that enforces restrictions on the language to enable opportunities for optimization. The Python code is compiled into an intermediate representation, Rust, which is further compiled and optimized by the Rust pipeline. We show that the analyzed features cause a significant reduction in performance and we quantify the cost of these features for language designers to consider.

As GPGPU computing becomes more popular, it will be used to tackle a wider range of problems. However, due to the current state of GPGPU programming, programmers are typically required to be familiar with the architecture of the GPU in order to effectively program it. Fortunately, there are software packages that attempt to simplify GPGPU programming in higher-level languages such as Java and Python. However, these software packages do not attempt to abstract the GPU-acceleration process completely. Instead, they require programmers to be somewhat familiar with the traditional GPGPU programming model which involves some understanding of GPU threads and kernels. In addition, prior to using these software packages, programmers are required to transform the data they would like to operate on into arrays of primitive data. Typically, such software packages restrict the use of object-oriented programming when implementing the code to operate on this data. This thesis presents GPUMap, which is a proof-of-concept GPU-accelerated map function for Python. GPUMap aims to hide all the details of the GPU from the programmer, and allows the programmer to accelerate programs written in normal Python code that operate on arbitrarily nested objects using a majority of Python syntax. Using GPUMap, certain types of Python programs are able to be accelerated up to 100 times over normal Python code. There are also software packages that provide simplified GPU acceleration to distributed computing frameworks such as MapReduce and Spark. Unfortunately, these packages do not provide a completely abstracted GPU programming experience, which conflicts with the purpose of the distributed computing frameworks: to abstract the underlying distributed system. This thesis also presents GPU-accelerated RDD (GPURDD), which is a type of Spark Resilient Distributed Dataset (RDD) which incorporates GPUMap into its map, filter, and foreach methods in order to allow Spark applicatons to make use of the abstracted GPU acceleration provided by GPUMap.

碩士<br>國立臺灣師範大學<br>資訊教育研究所<br>104<br>Programming is a fundamental ability for Computer Science majors. Most programming lectures use traditional languages, such as C, C++, or Java, as the first learning language for novices, which are effective for designing real applications and therefore are popular in industry. However, the complex syntax of these languages is challenging for novices, which becomes an obstacle to novices’ learning. Python has simpler syntax and high-level data structures to enable succinct programs. The multiple paradigms of Python also provide learners opportunities to learn various features of programming languages. Therefore, Python gradually becomes a new option of the first language for learning. This study investigates the features of the first learning programming language by comparing Python with the popular learning language Java. An inventory study was conducted on the students whose first programming language was Java (the Java group) or Python (the Python group), who had learnt both langues, and the insturctors who had taught both languagesto understand how the features of languages affect students’ learning from the aspects of program translation and execution (interpretation vs. compilation), involvng varous programming elements (e.g, variable declaration,the syntax of control structures, and the object-oriented syntaxes). The inventory questions were designed to understand whether and how the language features in this aspect influence program comprehension and program implementation. The research findings are as follows: 1. Program comprehension: the students whose first programming languge was Python performed significantly better in program comprehension than those whose first language was Java in terms of all programming elements or constructs except I/O, data types, and varibles. 2. Perception of program comprehension/implementation difficulty The research results show that students in the Java and Python groups had similar perception about implemetation difficulty of programming. Howerver, students in the Python group had higher pwhose first language was Python had more positive perception about the comprehension difficulty of programming in terms of the object-oriented concepts and constructs. That is, the Python group students were more confident in comprehending object-oriented statements. This might be because although Java is an inherent object-oriented language, it has too complex syntax for novice learners. 3. Comparisons of Java and Python: The comparison inventory was conducted on the students and instructors who had learnt or taught Java and Python before this study. The results show that both instructors and students thought Python was easier in terms of I/O, loops, and functions because of its simple syntax. Howerver, both instructors and students agreed with the difficulty of comprehending and implementing variable and assignment statements by using Python because its dynamic variables. The research results can give instructors suggestions for selecting suitable learning languages in their lectures and designing adaptive instructional strategies/materials based on the features of the selected language.

This research work focuses on machine learning algorithms in order to make predictions in financial markets. The foremost objective is to test whether the two machine learning algorithms: SVM and LSTM are capable of predicting the price movement in different time-frames and then develop a comparison analysis. In this research work, it is applied supervised machine learning with different input features. The practical and software component of this thesis applies Python programming language to test the hypothesis and act as proof of concept. The financial data quotes were obtained through online financial databases. The results demonstrate that SVM is capable of predicting the direction of the price while the LSTM did not present reliable results.

abstract: Photosynthesis is the primary source of energy for most living organisms. Light harvesting complexes (LHC) play a vital role in harvesting sunlight and passing it on to the protein complexes of the electron transfer chain which create the electrochemical potential across the membrane which drives ATP synthesis. phycobilisomes (PBS) are the most important LHCs in cyanobacteria. PBS is a complex of three light harvesting proteins: phycoerythrin (PE), phycocyanin (PC) and allophycocyanin (APC). This work has been done on a newly discovered cyanobacterium called Leptolyngbya Heron Island (L.HI). This study has three important goals: 1) Sequencing, assembly and annotation of the L.HI genome - Since this is a newly discovered cyanobacterium, its genome was not previously elucidated. Illumina sequencing, a type of next generation sequencing (NGS) technology was employed to sequence the genome. Unfortunately, the natural isolate contained other contaminating and potentially symbiotic bacterial populations. A novel bioinformatics strategy for separating DNA from contaminating bacterial populations from that of L.HI was devised which involves a combination of tetranucleotide frequency, %(G+C), BLAST analysis and gene annotation. 2) Structural elucidation of phycoerythrin - Phycoerythrin is the most important protein in the PBS assembly because it is one of the few light harvesting proteins which absorbs green light. The protein was crystallized and its structure solved to a resolution of 2Å. This protein contains two chemically distinct types of chromophores: phycourobilin and phycoerythrobilin. Energy transfer calculations indicate that there is unidirectional flow of energy from phycourobilin to phycoerythrobilin. Energy transfer time constants using Forster energy transfer theory have been found to be consistent with experimental data available in literature. 3) Effect of chromatic acclimation on photosystems - Chromatic acclimation is a phenomenon in which an organism modulates the ratio of PE/PC with change in light conditions. Our investigation in case of L.HI has revealed that the PE is expressed more in green light than PC in red light. This leads to unequal harvesting of light in these two states. Therefore, photosystem II expression is increased in red-light acclimatized cells coupled with an increase in number of PBS.<br>Dissertation/Thesis<br>Ph.D. Chemistry 2014

Осіпова Ю. В. Програмна реалізація автоматизації здійснення торгових операцій на біржі цінних паперів : кваліфікаційна робота магістра спеціальності 122 "Комп'ютерні науки" / наук. керівник К. С. Решевська. Запоріжжя : ЗНУ, 2020. 58 с.<br>UA : Робота викладена на 58 сторінках друкованого тексту, містить 1 таблицю, 3 рисунки, 17 джерел. Об’єкт дослідження – процеси біржової торгівлі на ринку фінансів і цінних паперів. Мета роботи: дослідження методів розробки та реалізація програмного продукту (торгового радника) засобами Python. Методи дослідження – аналітичний, порівняльний. Торгівля на біржі фінансів і цінних паперів в Україні набрала величезної популярності за останні роки. Це пов'язане зі зростанням можливостей обробки і розповсюдження фінансової інформації, завдяки чому фінансова торгівля стала більш досяжною для фізичних і юридичних осіб. В умовах зростання обсягів операцій, збільшення кількості гравців, скорочення часу розповсюдження інформації і здійснення угод, надзвичайно зростає попит на автоматизовані технології технічного аналізу стану ринку, які дозволяють проводити поглиблений аналіз ринкових показників, контролювати і мінімізувати торговельні ризики, забезпечуючи зменшення фінансових втрат. В роботі викладені: а) основні поняття фондового ринку. Розглянуті форми, стилі і методи біржової торгівлі; б) аналіз існуючих торгових платформ та біржових торгівельних роботів; в) програмна реалізація торгового робота засобами Рython.<br>EN : The work is presented on 58 pages of printed text, 1 table, 3 figures, 17 references. The object of study is the processes of stock exchange trading in the financial and securities markets. The aim of the study is study methods of development and implementation of software (trading advisor) by Python tools. The methods of research are analytical, comparative. Trading on the stock exchange of finance and securities in Ukraine has gained enormous popularity in recent years. This is due to the increased ability to process and disseminate financial information, making financial trading more accessible to individuals and businesses. As operations grow, the number of players increases, the dissemination of information and the execution of transactions, the demand for automated market analysis technologies that allow for an in-depth analysis of market indicators, control and minimize trade risks while reducing financial losses is growing. The work outlines: a) basic concepts of the stock market. Forms, styles and methods of exchange trading are considered; b) analysis of existing trading platforms and stock trading robots; c) Python software implementation of trading robot.

Planning for transportation within northern Canadian communities presents unique challenges, but new research tools offer opportunities for testing potentially innovative solutions that might help improve mobility within these communities. In particular, problem solving has been enriched in recent years by using the spatial modeling methods offered by Geographical Information Systems (GIS). This thesis first reviews various GIS methods before applying one method – the ‘Route Utility Theory’ – to a newly-developed set of metrics for determining the cost of alternate modes of intracommunity transportation. This set of metrics is applied to a data set that represents the trips or journeys made by non-car users in Iqaluit, the capital city of Nunavut Territory. GIS data on roads, walking trails, land contours, and public and residential neighbourhoods are analyzed. The results facilitate comparisons between road options and trail options for improving the movement of people within Iqaluit. Five bus routes were then custom designed and compared using the study’s metrics. The study found that increasing bus and trail options within Iqaluit would provide more efficient options for non-car users. It is argued that the study’s metrics can be adapted for application in other northern communities, and possibly in other isolated and rural communities in different world situations.<br>Graduate

Face recognition applications are widely used today for a variety of tasks, whether personal or professional. When looking for a service that provides face detection and classification, it is easy to find several solutions. In this project another way is described so that it is possible to perform this task according to the desired needs without the need to use proprietary software. With the emergence of the Django Rest Frame Work, web application development has become easier. This work describes development of stable foundation and features that offer an administration panel, relational database management, and support for a Restful Application Programming Interface (API). This takes advantage of the exclusive use of Open Source technologies thus the application code can be modified and distributed free of charge. For the development of an API that could perform detection and facial recognition, applying an Open Source philosophy, in addition to Django Rest Framework technologies such as Python, C++, MySql and JSON were used. The prototype is initially capable of recognizing the number of faces per image, assessing eyes, smile, age and gender. Flexibility is designed to increase application capabilities with new algorithms implemented in various programing languages.<br>Atualmente, as aplicações de reconhecimento de facial são amplamente utilizadas para uma variedade de tarefas, pessoais ou profissionais. Ao procurarmos um serviço que forneça deteção e classificação de rosto, é fácil encontrar várias soluções. Neste projeto, é descrita outra maneira para que seja possível executar esta tarefa de acordo com as necessidades desejadas, sem a necessidade de usar software proprietário. Com o surgimento do Django Rest Framework, o desenvolvimento de aplicações web ficou mais fácil. Este trabalho descreve o desenvolvimento de bases e recursos estáveis que oferecem um painel de administração, gestão de uma base de dados relacional e o suporte para uma API (Application Programming Interface) Restful. Ao tirar proveito do uso exclusivo de tecnologias Open Source, é permitido que o código possa ser modificado e distribuído gratuitamente. Para o desenvolvimento de uma API que pudesse realizar a deteção e o reconhecimento facial, aplicando uma filosofia Open Source, para além da tecnologia Django Rest Framework foram utilizadas tecnologias como Python, C ++, MySql e JSON. O protótipo é inicialmente capaz de reconhecer o número de rostos por imagem, e avaliar olhos, sorriso, idade e sexo. Mas para além disso, foi projetada flexibilidade para aumentar os recursos através da implementação de novos algoritmos em várias linguagens de programação.

The thesis researches the ability of use of Python programming language in the field of high school education and uses qualitative and quantitative methods of research and finds Python suitable. The thesis also brings theoretical analysis of the Python language, including practical exams in the form of sample programs. It researchs even other programming languages used in education and their suitability for this purpose and compares them with Python programming language. It also finds two most common used programming languages at high schools, which are Pascal / Object Pascal and Java.