Makecode and CODAL: Intuitive and Efficient Embedded Systems Programming for Education

Total Page:16

File Type:pdf, Size:1020Kb

Makecode and CODAL: Intuitive and Efficient Embedded Systems Programming for Education MakeCode and CODAL: Intuitive and Efficient Embedded Systems Programming for Education James Devine Joe Finney Peli de Halleux Lancaster University, UK Lancaster University, UK Microsoft, USA [email protected] [email protected] [email protected] Michał Moskal Thomas Ball Steve Hodges Microsoft, USA Microsoft, USA Microsoft, UK [email protected] [email protected] [email protected] Abstract Across the globe, it is now commonplace for educators to engage in the making (design and development) of embed- ded systems in the classroom to motivate and excite their students. This new domain brings its own set of unique re- quirements. Historically, embedded systems development requires knowledge of low-level programming languages, lo- Figure 1. Example projects undertaken within education: cal installation of compilation toolchains, device drivers, and Rishworth School sent a micro:bit to space [19] (left); The applications. For students and educators, these requirements micro:bit placed in a custom-built rocket car for teleme- can introduce insurmountable barriers. try [20, 21] (right). We present the motivation, requirements, implementation, and evaluation of a new programming platform that enables novice users to create software for embedded systems. The 1 Introduction platform has two major components: 1) Microsoft MakeCode Recent years have witnessed expansive growth in the popu- (www.makecode.com), a web app that encapsulates an entire larity and ubiquity of embedded systems. This growth can beginner IDE for microcontrollers; and 2) CODAL, an effi- be primarily attributed to the emergence of new application cient component-oriented C++ runtime for microcontrollers. domains ranging from wearables, to home automation, indus- We show how MakeCode and CODAL provide an accessible, trial automation, and smart grids ś a phenomenon broadly cross-platform, installation-free programming experience referred to as the Internet of Things (IoT). As the IoT con- for the BBC micro:bit and other embedded devices. tinues to grow, it has become more pervasive ś far beyond the realm of domain experts and into the everyday lives of CCS Concepts · Software and its engineering → Em- the public. This has led to growth in non-expert developers bedded software; Runtime environments; Integrated and vi- actively creating software for embedded systems. Small to sual development environments; medium sized businesses now create new products through Keywords education, classroom, embedded systems rapid prototyping of embedded devices. Hobbyist makers cre- ACM Reference Format: ate novel technical projects to inspire themselves and society. James Devine, Joe Finney, Peli de Halleux, Michał Moskal, Thomas And now, more than ever before, educators are making exten- Ball, and Steve Hodges. 2018. MakeCode and CODAL: Intuitive sive use of physical computing devices as a direct means to and Efficient Embedded Systems Programming for Education. In teach and inspire a generation of students ś and to prepare Proceedings of 19th ACM SIGPLAN/SIGBED Conference on Languages, them for a society where IoT will be the norm. These new Compilers, and Tools for Embedded Systems (LCTES’18). ACM, New developers all share a common characteristic: they are not York, NY, USA, 12 pages. https://doi.org/10.1145/3211332.3211335 professional software developers [9, 10, 16]. To address this trend, in 2015 a consortium of industry Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are and academic partners came together to develop the BBC not made or distributed for profit or commercial advantage and that copies micro:bit ś an embedded device designed specifically for bear this notice and the full citation on the first page. Copyrights for third- education. One million of these devices were delivered to party components of this work must be honored. For all other uses, contact UK school children in 2016. The micro:bit is a highly capable the owner/author(s). IoT device containing a 32-bit ARM Cortex-M0 processor, in- LCTES’18, June 19ś20, 2018, Philadelphia, PA, USA tegrated light level, temperature, acceleration and magnetic © 2018 Copyright held by the owner/author(s). ACM ISBN 978-1-4503-5803-3/18/06. sensors, touch sensitive inputs, and USB and 2.4GHz radio https://doi.org/10.1145/3211332.3211335 communications. 19 LCTES’18, June 19ś20, 2018, Philadelphia, PA, USA J. Devine, J. Finney, P. Halleux, M. Moskal, T. Ball, S. Hodges Figure 1 highlights two example educational projects based Table 1. Example microcontroller devices in relationship on the BBC micro:bit. The first is a data gathering experiment, to a typical PC. Device abbreviations: Uno (Arduino Uno), where multiple sensor data was recorded to non-volatile micro:bit (BBC micro:bit), CPX (Adafruit Circuit Playground memory as the device was launched into near space (32.5km Express), PC (Personal Computer). altitude), along with an externally interfaced camera and Word CPU GPS unit. The second highlights a live data telemetry appli- Device RAM Flash Size Speed CPU cation, where acceleration data was streamed in real-time via Uno 2 kB 32 kB 8 16MHz AVR Bluetooth Low Energy to enable the profiling of chemical- micro:bit 16 kB 256 kB 32 16MHz ARMv6-M rocket powered model vehicles. These projects are highly CPX 32 kB 256 kB 32 48MHz ARMv6-M sophisticated and were undertaken by high school educators PC 16 GB 1 TB 64 3GHz x86-64 and their students. 1 We introduce an open-source platform for embedded permitted by policy and/or access to the necessary technical devices such as the micro:bit that enables the development support is not present. An effective solution must therefore of embedded applications by non-expert programmers. This provide a fully transparent, platform agnostic, zero installation platform consists of two major components: 1) Microsoft experience to developing embedded software. MakeCode (www.makecode.com), a web app providing a beginner IDE for embedded systems; and 2) CODAL Optimization for Code Efficiency: The projects of Figure 1 (Component-Oriented Device Abstraction Layer), an efficient are enabled by small, highly resource-limited programmable C++ runtime with high-level programming abstractions. MCUs, which may have as little as a few kilobytes of RAM In the remainder of the introduction, we present the major and FLASH memory. Table 1 compares the core capabilities design challenges in bringing embedded systems into edu- of the class of MCU-based devices typically used in the edu- cation, briefly describe the architecture of our solution, and cation domain to a typical PC. Note that these devices have a give an overview of the paper and our results. proportionally large amount of processing power, relative to their storage. Consider the BBC micro:bit vs. a typical PC: the 1.1 Design Challenges micro:bit has about 100 times less CPU power, but 106 times Enabling novice programmers to successfully develop em- less RAM, and 106 times less storage. A language/runtime bedded applications is a non-trivial task. Throughout our should therefore not only seek to provide high code density and research we have identified a number of design challenges spatial efficiency, but actively trade off temporal for spatial that we address through MakeCode and CODAL. efficiency where possible. High Level Languages: Programming languages for micro- Asynchronous and Concurrent Programming: It is al- controller units (MCUs) have not kept pace with advances ready well understood that novice programmers benefit from in hardware. Despite active research in the field, the C/C++ event-based programming paradigms [17, 18, 26]. This is in- languages remain the standard for embedded systems: they creasingly relevant for embedded systems due to the typically provide a familiar imperative programming model, with com- asynchronous nature of their hardware. MCUs still follow pilers that produce highly efficient code, and enable low level Moore’s law, but this additional capacity is not typically in- access to hardware features when necessary. The Arduino vested in speeding up processors. Instead, more independent project (www.arduino.cc), started in 2003, and ARM’s Mbed peripherals (such as Bluetooth/WiFi radio modules, audio platform (www.mbed.org) both rely heavily on a C/C++ pro- inputs/output processors, etc.) are integrated onto the same gramming model [6, 24]. However, the limitations of using package as the CPU as a system-on-chip. Such peripherals C/C++ as an application programming language for inexpe- often operate independently of the main CPU. An effective rienced developers are well understood [8]. To address this, language/runtime should directly support an asynchronous higher level languages such as JavaScript, Python, and even interaction model designed to cooperate with the independent visual programming languages are required. nature of peripherals while remaining highly intuitive to the programmer. Zero Installation Architecture: The development environ- ment for existing embedded systems typically requires the Intuitive and Extensible APIs: Intuitive APIs and program- installation of code editors, custom device drivers, com- ming models are required to support novice users, yet it is piler toolchains, and even additional programming hardware equally important that these APIs remain complete enough (such as a JLink programmer). For many, particularly in the to realise the ambitious projects that may be undertaken as field of education, this presents a high adoption barrier asin students advance: simplification via the reduction of func- many schools, custom hardware and software is simply not tionality is not a valid approach. An effective solution must provide APIs that are consistent, easy to understand/use, and 1 MakeCode is open-source at https://github.com/microsoft/pxt; CODAL is progressive, to address the growing capabilities of the program- open-source at https://github.com/lancaster-university/codal. mer. 20 MakeCode and CODAL: Intuitive and Efficient Embedded... LCTES’18, June 19ś20, 2018, Philadelphia, PA,USA Figure 3.
Recommended publications
  • Micropython for Satlink 3 Documentation Release 1.8.4
    MicroPython for Satlink 3 Documentation Release 1.8.4 Damien P. George, contributors, and Sutron Corporation Jul 28, 2017 CONTENTS 1 Python first time setup & configuration1 1.1 1. Download & Install LinkComm....................................1 1.2 2. Download & Install Python......................................1 1.3 3. Download & Install Pyinstaller....................................3 1.4 4. Download & Install PyCharm.....................................3 1.5 5. Testing out .py to .exe converter....................................5 1.6 6. Python PyQt5 GUI..........................................6 1.7 7. Connect PyCharm into external programs like linkcomm or micropython..............6 1.8 8. Configure PyCharm for program development using LinkComm..................9 1.9 9. Configure PyCharm with SL3 API for auto completion....................... 11 1.10 10. Setting docstring stub in PyCharm.................................. 13 2 MicroPython libraries 15 2.1 Python standard libraries and micro-libraries.............................. 15 2.2 MicroPython-specific libraries...................................... 16 2.3 Libraries specific to the Satlink 3.................................... 19 3 The MicroPython language 39 3.1 Overview of MicroPython Differences from Standard Python..................... 39 3.2 Code examples of how MicroPython differs from Standard Python with work-arounds........ 41 3.3 The MicroPython Interactive Interpreter Mode (aka REPL)....................... 56 3.4 Maximising Python Speed.......................................
    [Show full text]
  • Setting up Your Environment
    APPENDIX A Setting Up Your Environment Choosing the correct tools to work with asyncio is a non-trivial choice, since it can significantly impact the availability and performance of asyncio. In this appendix, we discuss the interpreter and the packaging options that influence your asyncio experience. The Interpreter Depending on the API version of the interpreter, the syntax of declaring coroutines change and the suggestions considering API usage change. (Passing the loop parameter is considered deprecated for APIs newer than 3.6, instantiating your own loop should happen only in rare circumstances in Python 3.7, etc.) Availability Python interpreters adhere to the standard in varying degrees. This is because they are implementations/manifestations of the Python language specification, which is managed by the PSF. At the time of this writing, three relevant interpreters support at least parts of asyncio out of the box: CPython, MicroPython, and PyPy. © Mohamed Mustapha Tahrioui 2019 293 M. M. Tahrioui, asyncio Recipes, https://doi.org/10.1007/978-1-4842-4401-2 APPENDIX A SeTTinG Up YouR EnViROnMenT Since we are ideally interested in a complete or semi-complete implementation of asyncio, our choice is limited to CPython and PyPy. Both of these products have a great community. Since we are ideally using a lot powerful stdlib features, it is inevitable to pose the question of implementation completeness of a given interpreter with respect to the Python specification. The CPython interpreter is the reference implementation of the language specification and hence it adheres to the largest set of features in the language specification. At the point of this writing, CPython was targeting API version 3.7.
    [Show full text]
  • Python Crypto Misuses in the Wild
    Python Crypto Misuses in the Wild Anna-Katharina Wickert Lars Baumgärtner [email protected] [email protected] Technische Universität Darmstadt Technische Universität Darmstadt Darmstadt, Germany Darmstadt, Germany Florian Breitfelder Mira Mezini [email protected] [email protected] Technische Universität Darmstadt Technische Universität Darmstadt Darmstadt, Germany Darmstadt, Germany ABSTRACT 1 INTRODUCTION Background: Previous studies have shown that up to 99.59 % of the Cryptography, hereafter crypto, is widely used nowadays to protect Java apps using crypto APIs misuse the API at least once. However, our data and ensure confidentiality. For example, without crypto, these studies have been conducted on Java and C, while empirical we would not be able to securely use online banking or do online studies for other languages are missing. For example, a controlled shopping. Unfortunately, previous research results show that crypto user study with crypto tasks in Python has shown that 68.5 % of the is often used in an insecure way [3, 4, 7, 9, 11]. One such problem is professional developers write a secure solution for a crypto task. the choice of an insecure parameter, like an insecure block mode, for Aims: To understand if this observation holds for real-world code, crypto primitives like encryption. Many static analysis tools exist we conducted a study of crypto misuses in Python. Method: We to identify these misuses such as CryptoREX [13], CryptoLint [4], developed a static analysis tool that covers common misuses of5 CogniCryptSAST [8], and Cryptoguard [12]. different Python crypto APIs. With this analysis, we analyzed 895 While these tools and the respective in-the-wild studies concen- popular Python projects from GitHub and 51 MicroPython projects trate on Java and C, user studies suggest that the existing Python for embedded devices.
    [Show full text]
  • How Python Is Winning New Friends
    How Python is Winning New Friends Steve Holden CTO, Global Stress Index Limited [email protected] IntroducFons • Programmer since 1967 • Computaonal scienFst by training • Engineer at heart • Python user since Python 1.4 (c. 1995) • Enjoy helping people to learn I’ve WriSen about Python Any Python users out there? Developments in CompuFng SOME HISTORY 1948 Programming Was Hard • No operang system • No libraries • No compilers • No assemblers • The painful process of abstracFon layering began 1977 Easier to Program • Assemblers/compilers available • UNIX starFng to emerge as a common base – Microprogramming handled hardware complexity • Storage flexibly handled by the OS • Networking heading to ubiquity 1984 2015 2016 2017 2020 ? Whatever it is, it will be complex! And so to Python “BUT IT’S [JUST] A SCRIPTING LANGUAGE …” What’s a “ScripFng Language”? • “First they ignore you; then they abuse you; then they crack down on you and then you win.” – not Mahatma Ghandi What’s a “ScripFng Language”? • “First they ignore you; then they abuse you; then they crack down on you and then you win.” – not Mahatma Ghandi • “Ridicule is like repression. Both give place to respect when they fail to produce the intended effect.” – Mahatma Ghandi Note to Purists • Learners do not have complex needs – Simplicity and consistency are important – ExecuFon speed mostly isn’t • Direct hands-on experience enables • Large resources not required – Wide availability and ease of access are criFcal The Programming Audience • Professional soiware engineers • ScienFsts • Lab
    [Show full text]
  • Pdf for a Detailed Explanation, Along with Various Techniques for Debouncing
    MicroPython Documentation Release 1.11 Damien P. George, Paul Sokolovsky, and contributors May 29, 2019 CONTENTS i ii CHAPTER ONE MICROPYTHON LIBRARIES Warning: Important summary of this section • MicroPython implements a subset of Python functionality for each module. • To ease extensibility, MicroPython versions of standard Python modules usually have u (“micro”) prefix. • Any particular MicroPython variant or port may miss any feature/function described in this general docu- mentation (due to resource constraints or other limitations). This chapter describes modules (function and class libraries) which are built into MicroPython. There are a few categories of such modules: • Modules which implement a subset of standard Python functionality and are not intended to be extended by the user. • Modules which implement a subset of Python functionality, with a provision for extension by the user (via Python code). • Modules which implement MicroPython extensions to the Python standard libraries. • Modules specific to a particular MicroPython port and thus not portable. Note about the availability of the modules and their contents: This documentation in general aspires to describe all modules and functions/classes which are implemented in MicroPython project. However, MicroPython is highly configurable, and each port to a particular board/embedded system makes available only a subset of MicroPython libraries. For officially supported ports, there is an effort to either filter out non-applicable items, or mark individual descriptions with “Availability:” clauses describing which ports provide a given feature. With that in mind, please still be warned that some functions/classes in a module (or even the entire module) described in this documentation may be unavailable in a particular build of MicroPython on a particular system.
    [Show full text]
  • Bringing Python to Godot
    Bringing Python to Godot 01/02/2020 Emmanuel Leblond - https://github.com/touilleMan/godot-python Godot ? Open source (MIT) Full featured Linux support ❤❤❤ Demo time ! Godot: dynamic from the ground class Node2D : public Node { godot/node2d.hpp GDCLASS(Node2D, Node); void set_rot(float p_angle); float get_rot() const; ... void _bind_methods() { ClassDB::bind_method(D_METHOD("get_rot"), &Node2D::get_rot); ClassDB::bind_method(D_METHOD("set_rot", "degrees"), &Node2D::set_rot); ... } } Godot: dynamic from the ground class Node2D : public Node { godot/node2d.hpp GDCLASS(Node2D, Node); void set_rot(float p_angle); float get_rot() const; ... void _bind_methods() { ClassDB::bind_method(D_METHOD("get_rot"), &Node2D::get_rot); ClassDB::bind_method(D_METHOD("set_rot", "degrees"), &Node2D::set_rot); ... } } Godot: dynamic from the ground class Node2D : public Node { godot/node2d.hpp GDCLASS(Node2D, Node); void set_rot(float p_angle); float get_rot() const; ... void _bind_methods() { ClassDB::bind_method(D_METHOD("get_rot"), &Node2D::get_rot); ClassDB::bind_method(D_METHOD("set_rot", "degrees"), &Node2D::set_rot); ... } } # C++ static traditional way Node2D *obj = new Node2D(); obj->set_ret(4.2); Godot: dynamic from the ground class Node2D : public Node { godot/node2d.hpp GDCLASS(Node2D, Node); void set_rot(float p_angle); float get_rot() const; ... void _bind_methods() { ClassDB::bind_method(D_METHOD("get_rot"), &Node2D::get_rot); ClassDB::bind_method(D_METHOD("set_rot", "degrees"), &Node2D::set_rot); ... } } # C++ static traditional way # C++ Dynamic
    [Show full text]
  • Micropython Documentation Release 1.10 Damien P. George, Paul
    MicroPython Documentation Release 1.10 Damien P. George, Paul Sokolovsky, and contributors Jan 25, 2019 CONTENTS 1 MicroPython libraries 1 1.1 Python standard libraries and micro-libraries..............................2 1.1.1 Builtin functions and exceptions................................2 1.1.2 array – arrays of numeric data................................5 1.1.3 cmath – mathematical functions for complex numbers....................5 1.1.4 gc – control the garbage collector...............................6 1.1.5 math – mathematical functions................................7 1.1.6 sys – system specific functions................................9 1.1.7 ubinascii – binary/ASCII conversions........................... 11 1.1.8 ucollections – collection and container types...................... 11 1.1.9 uerrno – system error codes................................. 12 1.1.10 uhashlib – hashing algorithms............................... 13 1.1.11 uheapq – heap queue algorithm................................ 14 1.1.12 uio – input/output streams................................... 14 1.1.13 ujson – JSON encoding and decoding............................ 16 1.1.14 uos – basic “operating system” services............................ 16 1.1.15 ure – simple regular expressions............................... 20 1.1.16 uselect – wait for events on a set of streams........................ 22 1.1.17 usocket – socket module................................... 23 1.1.18 ussl – SSL/TLS module................................... 28 1.1.19 ustruct – pack and unpack
    [Show full text]
  • Sistema Basado En Tecnología 5G De Monitorización Psicoacústica Del Paisaje Sonoro En Smart Cities Con Offloading Computacional Dinámico En El Edge
    SISTEMA BASADO EN TECNOLOGÍA 5G DE MONITORIZACIÓN PSICOACÚSTICA DEL PAISAJE SONORO EN SMART CITIES CON OFFLOADING COMPUTACIONAL DINÁMICO EN EL EDGE Jaume Segura-Garcia1, Santiago Felici-Castell1, Jose M. Alcaraz Calero2, Qi Wang2, Jesús López-Ballester1, Rafael Fayos-Jordán1, Juan J. Pérez-Solano1, Miguel Arana-Burgui3 1 Dpt Informàtica, ETSE – Universitat de València {e-mail: [email protected], [email protected], [email protected], [email protected], [email protected]} 2 School of Computing, Engineering and Physical Sciences – University of the West of Scotland 3 INAMAT – Universidad Pública de Navarra, Spain Resumen En las tecnologías de próxima generación, el control de las molestias por ruido ambiental en una Smart City debería ser lo más eficiente posible. Los sistemas IoT sobre tecnologías 5G ofrecen una gran oportunidad para hacer offloading del cómputo en los nodos sensores, ya que proporciona una serie de nuevos conceptos para el cómputo dinámico que las tecnologías anteriores no ofrecían. En este artículo, se ha implementado un sistema IoT completo basado en tecnología 5G para la monitorización psicoacústica utilizando diferentes opciones para descargar el cómputo a diferentes partes del sistema. Esta descarga se ha realizado mediante el desarrollo de diferentes splittings funcionales de los algoritmos de cálculo de las métricas psicoacústicas. Por último, se muestra una comparación del rendimiento entre los diferentes splittings funcionales y su aplicación con un análisis detallado. Palabras clave: 5G LTE-M1, psicoacústica, monitorización del soundscape, splitting funcional, Smart City. Abstract In the next generation technologies, the environmental noise nuisance monitoring in a Smart City should be as much efficient as possible. 5G IoT systems offer a big opportunity to offload the computation from the sensor nodes, since it provides a series of new concepts for dynamic computing that the previous technologies did not offer.
    [Show full text]
  • Release 1.9.2 Damien P. George, Paul Sokolovsky, and Contributors
    MicroPython Documentation Release 1.9.2 Damien P. George, Paul Sokolovsky, and contributors August 23, 2017 CONTENTS 1 Quick reference for the WiPy1 1.1 General board control (including sleep modes).............................1 1.2 Pins and GPIO..............................................1 1.3 Timers..................................................1 1.4 PWM (pulse width modulation).....................................2 1.5 ADC (analog to digital conversion)...................................2 1.6 UART (serial bus)............................................2 1.7 SPI bus..................................................2 1.8 I2C bus..................................................3 1.9 Watchdog timer (WDT).........................................3 1.10 Real time clock (RTC)..........................................3 1.11 SD card..................................................4 1.12 WLAN (WiFi)..............................................4 1.13 Telnet and FTP server..........................................4 1.14 Heart beat LED..............................................4 2 General information about the WiPy7 2.1 No floating point support.........................................7 2.2 Before applying power..........................................7 2.3 WLAN default behaviour........................................7 2.4 Telnet REPL...............................................7 2.5 Local file system and FTP access....................................7 2.6 FileZilla settings.............................................8 2.7 Upgrading
    [Show full text]
  • Building Micropython with KEIL and Programming with Python on I.MX RT1050/1060 Rev
    AN13242 Building Micropython with KEIL and Programming with Python on i.MX RT1050/1060 Rev. 0 — 27 April, 2021 Application Note Contents 1 Introduction 1 Introduction......................................1 This application note introduces the porting of MicroPython, the packaging of 2 Hardware platform...........................1 2.1 i.MX RT1050/60 crossover peripheral functions, and the adaptation of circuit boards, using the example process........................................ 1 of our work on the i.MX RT1050/1060EVK development board. The code are 2.2 i.MX RT1050/60 EVK board........ 1 mainly written in C language, but are presented to the users as Python modules 3 Micropython.....................................2 and types. You can either evaluate and use MicroPython on this development 3.1 Brief introduction to Python board, or use it to port and adapt your new board design. MicroPython’s native Language.....................................2 project management and build environment is based on GCC and Make under 3.2 Brief introduction to Micropython Linux. To facilitate the development habits of most MCU embedded engineers, .....................................................3 the development environment is also ported to Keil MDK5. 4 Building and running Micropython on i.MX RT1050/1060 EVK.................. 3 The readers are expected to have basic experience of development with KEIL 4.1 Downloading source code........... 3 MDK, knowing what is CMSIS-Pack, the concept of target in KEIL and how to 4.2 Opening project with KEIL
    [Show full text]
  • Or How to Avoid Recoding Your (Entire) Application in Another Language Before You Start
    Speeding up Python Or how to avoid recoding your (entire) application in another language Before you Start ● Most Python projects are “fast enough”. This presentation is not for them. ● Profle your code, to identify the slow parts AKA “hot spots”. ● The results can be surprising at times. ● Don’t bother speeding up the rest of your code. Improving your Python ● Look into using a better algorithm or datastructure next. ● EG: Sorting inside a loop is rarely a good idea, and might be better handled with a tree or SortedDict. Add Caching ● Memorize expensive-to-compute (and recompute) values. ● Can be done relatively easily using functools.lru_cache in 3.2+. Parallelise ● Multicore CPU’s have become common. ● Probably use threading or multiprocessing. Threading ● CPython does not thread CPU-bound tasks well. ● CPython can thread I/O-bound tasks well. ● CPython cannot thread a mix of CPU-bound and I/ O-bound well. ● Jython, IronPython and MicroPython can thread arbitrary workloads well. ● Data lives in the same threaded process. This is good for speed, bad for reliability. Multiprocessing ● Works with most Python implementations. ● Is a bit slower than threading when threading is working well. ● Gives looser coupling than threading, so is easier to “get right”. ● Can pass data from one process to another using shared memory. Numba ● If you’re able to isolate your performance issue to a small number of functions or methods (callables), consider using Numba. ● It’s just a decorator – simple. ● It has “object mode” (which doesn’t help much), and “nopython mode” (which can help a lot, but is more restrictive).
    [Show full text]
  • Python Auf Dem Microcontroller
    Python auf dem Microcontroller Python auf dem Microcontroller Alexander Böhm [email protected] Chemnitzer Linux-Tage, 16. März 2019 Alexander Böhm [email protected] Chemnitzer Linux-Tage, 16. März 2019 1 / 26 Microcontroller-Entwicklung im IoT mehr Leistung mehr eingebaute Geräte energieeffizienter ! mehr Möglichkeiten Verschmelzung von Desktop- und Microcontroller-Welt Python auf dem Microcontroller Einführung Motivation Python ist schnell und einfach Alexander Böhm [email protected] Chemnitzer Linux-Tage, 16. März 2019 2 / 26 mehr eingebaute Geräte energieeffizienter ! mehr Möglichkeiten Verschmelzung von Desktop- und Microcontroller-Welt Python auf dem Microcontroller Einführung Motivation Python ist schnell und einfach Microcontroller-Entwicklung im IoT mehr Leistung Alexander Böhm [email protected] Chemnitzer Linux-Tage, 16. März 2019 2 / 26 energieeffizienter ! mehr Möglichkeiten Verschmelzung von Desktop- und Microcontroller-Welt Python auf dem Microcontroller Einführung Motivation Python ist schnell und einfach Microcontroller-Entwicklung im IoT mehr Leistung mehr eingebaute Geräte Alexander Böhm [email protected] Chemnitzer Linux-Tage, 16. März 2019 2 / 26 ! mehr Möglichkeiten Verschmelzung von Desktop- und Microcontroller-Welt Python auf dem Microcontroller Einführung Motivation Python ist schnell und einfach Microcontroller-Entwicklung im IoT mehr Leistung mehr eingebaute Geräte energieeffizienter Alexander Böhm [email protected] Chemnitzer Linux-Tage, 16. März
    [Show full text]