The Python Bookの The Python Book 4th Edition の目次

With the Python interpreter, you aren’t just limited to what is already available; you can extend the available functionality by defining your own Python objects, with their own methods and data, within your C code. These newly-created objects can then be called from within the Python interpreter. They are defined as static objects, with code like: The new PyObject contains the executable code for the methods to be used for your new object. You also need to create a method definition to be able to register the details with the Python interpreter. You do this by creating a PyMethodDef array: Once you have finished these two parts, you are almost ready to start using your new module code. You need to initialise it with the function: Now, you can import…

With the content and the bulk of the computing hosted on a server, a web application can better guarantee a consistent experience for the end user. The popular Django framework provides a very complete environment of plugins and works on the DRY principle (Don’t Repeat Yourself). Because of this, you should be able to build your web application very quickly. Since Django is built on Python, you should be able to install it with “sudo pip install Django”. Most distributions should have a package for Django, too. Depending on what you want to do with your app, you may need to install a database like MySQL or postgresql to store your application data. There are Django utilities available to automatically generate a starting point for your new project’s code: This…

What if you need to actually have truly parallel code, that has the ability to run on multiple cores? Because Python has the GIL, you need to move away from using threads and go to using separate processes to handle the different tasks. Luckily, Python includes a multiprocessing module that provides the process equivalent to the threading module. As with the threading module, you create a new process object and hand in a target function to be run. You then need to call the start() method to get it running. With threads, sharing data is trivial because memory is global and everybody can see everything. However, different processes are in different memory scopes. In order to share data, we need to explicitly set up some form of communications. You can…

01 Install Flask Create a new directory inside of which your project will live. Open a Terminal window and navigate to be inside your new directory. Create a new virtual environment for this project, placed inside a new directory called ‘venv’, and activate it. Once inside the new virtual shell, proceed to installing Flask using the ‘pip install Flask’ command. 02 Create Index Create a new file in the root of the project location called ‘index.py’. The sample API will use a SQLite database, so we need to import that module for use in the application. We’ll also import some core components from the Flask module to handle request management and response formatting as well as some other functions. The minimum import for a Flask application is Flask itself. 03…

Heroku heroku.com This app is perhaps one of the most wellknown cloud hosting providers. Their stack server environments support a number of core web app languages including Python as standard. Their unique Toolbelt command-line features and integration with Git repositories, as well as being incredibly quick and easy to scale and improve performance, makes them an obvious choice. A free account will let you run a Python web app on one dyno instance without any cost. Python Anywhere www.pythonanywhere.com Another hosted option, and one created specifically for Python applications in general is Python Anywhere. The free basic option plan has enough weight and power behind it to get you up and running with a Python web app without having to scale, but as soon as your project gains traction, you…

As people have worked with writing parallel Python code over time, the painful parts have been identified and people have written packages to try and make these a bit more comfortable to work with. One of these packages that has been gaining in popularity is dask. The real power of dask is its flexibility. It can use many different parallelisation backends, and it also gives methods and objects that build on those used for scientific computations. For example, these new objects can mimic numpy arrays, or pandas data frames. Because of all of this additional functionality, you can select what you want support for when you install dask. For example, if you want everything, you can install it with this command: The back end parallelisation method used by dask is…

In a previous piece, we looked at how you could use your Raspberry Pi and some Python code to look at a scene and figure out whether there was any motion there. Now we will take it one step further and see if we can get our Raspberry Pis to actually recognise faces. We’ll assume here that you are either using the camera module for the Raspberry Pi, or a USB web cam. In either case, you have a stream of images being handed to your code, ready to be processed. Again, as in previous articles, we will be using the OpenCV Python module to handle all of the heavy image processing involved. The first step is to be sure you have Python and the OpenCV module installed with: To…

Python has a massive environment of extra modules that can provide functionality in hundreds of different disciplines. However, every programming language has a core set of functionality that everyone should know in order to get useful work done. Python is no different in this regard. Here, we will look at 50 commands that we consider to be essential to programming in Python. Others may pick a slightly different set, but this list contains the best of the best. We will cover all of the basic commands, from importing extra modules at the beginning of a program to returning values to the calling environment at the end. We will also be looking at some commands that are useful in learning about the current session within Python, like the current list of…

Resources Python 2: www.python.org/download IDLE: www.python.org/idle One of the best ways to get to know Python is by building lots of simple projects so you can understand a bit more about the programming language. This time round, we’re looking at Hangman, a multi-round game relying on if and while loops and dealing with strings of text in multiple ways. We’ll be using some of the techniques we implemented last time as well, so we can build upon them. Hangman still doesn’t require the Pygame set of modules, but it’s a little more advanced than rock-paper-scissors. We’re playing around with a lot more variables this time. However, we’re still looking at comparisons, random selections and human input, along with splitting up a string, editing a list and even displaying rudimentary graphics.…

System administration tasks are some of the most annoying things that you need to deal with when you have to maintain your own system. Because of this, system administrators have constantly been trying to find ways to automate these types of tasks to maximise their time. They started with basic shell scripts, and then moved on to various scripting languages. For a long time, Perl had been the language of choice for developing these types of maintenance tools. However, Python is now growing in popularity as the language to use. It has reached the point where most Linux distributions have a Python interpreter included in order to run system scripts, so you shouldn’t have any excuse for not writing your own scripts. Because you will be doing a lot system…

While Django is one of the most popular frameworks around for doing web development, it is by no means the only one around. There are several others available that may prove to be a better fit for particular problem domains. For example, if you are looking for a really self-contained framework, you could look at web2py. Everything you need to be able to have a complete system, from databases to web servers to a ticketing system, are included as part of the framework. It is so self-contained that it can even run from a USB drive If you need even less of a framework, there are several mini-frameworks that are available. For example, CherryPy is a purely Pythonic multi-threaded web server that you can embed within your own application. This…

Resources Python-devel Python development libraries, required for compiling third-party Python module setuptools setuptools allows you to download, build, install, upgrade, and uninstall Python packages with ease System administration is an important part of our computing environment. It does not matter whether you are managing systems at your work our home. Linux, being a UNIX-based operating system, already has everything a system administrator needs, such as the world-class shells (not just one but many, including Bash, csh, zsh etc), handy tools, and many other features which make the Linux system an administrator’s dream. So why do we need Python when Linux already has everything built-in? Being a dynamic scripting language, Python is very easy to read and learn. That’s just not us saying that, but many Linux distributions actually use Python…

With such a small physical footprint and a low power requirement, the Raspberry Pi is a perfect platform that you can use to build your own scientific equipment. We will look at how you might be able to use your Pi to monitor and analyse sounds in your environment. This is useful if you are listening for particular sounds. You need a Raspberry Pi, some kind of USB microphone, and some kind of USB wireless connection if you want to check on the monitoring process remotely. The specifics of the hardware are up to you, but you should be able to use almost anything that is available to you. This article will focus on the Python code that you will need in order to record this audio and do some…

Disqus, the popular social interaction comment service provider, has been implementing their production applications in Python for a very long time. Python’s benefit for the development team was its ability to scale effectively and cater for a large number of consumers whilst also providing an effective underlying API for internal and external use. The company are now starting to run some production apps in Go, but the majority of code still runs on Python. World-renowned image sharing service Instagram and social pin board Pinterest have also implemented Python as part of their web stack, opting for Django to assist with the functionality and ability to cater for the many thousands of content views and requests made to their services. Mozilla, Atlassian’s Bitbucket repository service, and popular satire site The Onion…

Resources Python base: http://www.python.org/download/ Django source: www.djangoproject.com/download/djangoproject.com/download/ We’ve been building our Django blog to create and display posts, allow people to make comments, and filter posts by month like a classic blog sidebar. We still have a bit of a way to go until it looks and behaves more like a classic blog, though. In this tutorial, we’re going to add in summaries, excerpts, categories and finally an RSS feed. This allows us to look at a few things – firstly we’ll get a better understanding of crossmodel referencing and how that works in the admin site. We will also go through how to make changes to the database, and how Django helps when creating an SQL query. Finally, the RSS feed is part of a standard feed library in…

“But, what about 3D?” we hear you ask. Luckily, we can reuse much of what we have already covered here to move into three dimensions. The first change is that vertices now are defined with three values rather than two, giving you a set of x, y and z coordinates. The second change is in the category of functions that you need to use. You can see that the drawing functions used are explicitly two-dimensional in their names. For example, you should have noticed the ‘2’ in names like ‘glVertex2f()’. To draw three-dimensionally, this changes to names like ‘glVertex3fv()’. The third change is more conceptual. Once we move to three dimensions, we need to worry about where we are in relation to the object that is being drawn, and what…

We have seen that the key part of object detection within an image is the cascade file. When you open one up, you will notice that it doesn’t seem to be very complicated. The complicated bit is in the encoded data that defines that features within the cascade algorithm that are used to identify the object. This data needs to be discovered through a training step where the relevant OpenCV functions look at images that both have the object in question and images that do not have the object. You need a much larger set of negative images compared to positive images. For example, the author of the blog entry at http:// coding-robin.de/2013/07/22/train-your-own-opencvhaar-classifier.html needed to use a set of 40 positive images and 600 negative images in order to identify…

Resources An old/new toy Resistors Small disc motor LED A radio Small webcam Female-to-female jumper jerky wire Tactile button In part one of this ‘hack a toy’ tutorial you created four hacks that were originally used to augment a £3 R2D2 sweet dispenser making it light up, vibrate, play music and stream a live web feed to a mobile device. You may have been working on your own features to use and customise your toy. Part two of this tutorial begins by showing two different ways to set up and use a button to trigger your hacks. One method is to add and code your own button, the second method is to utilise the toy’s own builtin button. The next part walks you through how to wire up, code and…

Basics 01 Running Python scripts On most of the UNIX systems, you can Python scripts from the command line. 02 Running Python programs from Python interpreter The Python interactive interpreter makes it easy to try your first steps in programming and using all Python commands. You just issue each command at the command prompt (>>>), one by one, and the answer is immediate. Python interpreter can be started by issuing the command: In this article, all the code starting at the symbol is meant to be given at the Python prompt. It is also important to remember that Python takes tabs very seriously – so if you are receiving any error that mentions tabs, correct the tab spacing. 03 Dynamic typing In Java, C++, and other statically typed languages, you must…

Back in issue 155, we looked at how to call C functions from within a Python program to get more speed. But, there are times, within a C program, when you may want to execute some piece of Python code. Maybe you want to be able to run user code within your program, for example. This means you can enable users to use plug-ins to extend your program’s functionality. The way we can do this is by embedding Python within the C program. We will look at how to embed, how to run your Python code, and how to interact with the Python interpreter you’ve set up. This is functionality built into Python itself, so you don’t need to install anything extra on your Raspberry Pi, aside from the development…

The underlying philosophy of Unix is to build small, specialised programs that do one job extremely well. You then chain these together to build more complex behaviours. There is no reason why you shouldn’t use the same philosophy within your Python scripts. There are several utility programs available to use with very little work on your part. The older way of handling this was through using functions like “popen()” and “spawnl()” from the os module, but a better way of running other programs is by using the subprocess module instead. You can then launch a program, like ls, by using: This provides you with a long file listing for the current directory. The function “run()” was introduced in Python 3.5 and is the suggested way of handling this. If you…

Python has become one of the key languages used in science. There is a huge number of packages available to handle almost any task that you may have and, importantly, Python knows what it isn’t good at. To deal with this, Python has been designed to easily incorporate code from C or FORTRAN. This way, you can offl oad any heavy computations to more efficient code. The core package of most of the scientific code available is numpy. One of the problems in Python is that the object oriented nature of the language is the source of its inefficiencies. With no strict types, Python always needs to check parameters on every operation. Numpy provides a new datatype, the array, which helps solve some of these issues. Arrays can only hold…

While you could simply write some code that runs on a standard computer and a standard Linux distribution, this is usually not optimal when trying to handle all of the data processing that a robot needs when dealing with events in realtime. When you reach this point, you may need to look at a dedicated operating system – the Robot Operating System (ROS). ROS is designed to provide the same type of interface between running code the computer hardware it is running on, with the lowest possible overhead. One of the really powerful features of ROS is that it is designed to facilitate communication between different processes running on the computer, or potentially over multiple computers connected over some type of network. Instead of each process being a silo that…

The majority of programmers will learn single-threaded programming as their first computational model. The basic idea is that instructions for the computer are processed sequentially, one after the other. This works well enough in most situations, but you will reach a point where you need to start multitasking. The classical situation for writing multi-threaded applications is to have them run on a multi-processor machine of some persuasion. In these cases, you would have some heavy, compute-bound process running on each processor. Since your Raspberry Pi is not a huge 16-core desktop machine, you might be under the assumption that you can’t take advantage of using multiple threads of execution. This isn’t true, though. There are lots of problems that map naturally to the multiple thread model. You may also have…

Kivy is a highly cross-platform graphical framework for Python, designed for the creation of innovative user interfaces like multitouch apps. Its applications can run not only on the traditional desktop platforms of Linux, OS X and Windows, but also Android and iOS, plus devices like the Raspberry Pi. That means you can develop cross-platform apps using Python libraries such as Requests, SQLAlchemy or even NumPy. You can even access native mobile APIs straight from Python using some of Kivy’s sister projects. Another great feature is the Cython-optimised OpenGL graphics pipeline, allowing advanced GPU effects even though the basic Python API is very simple. Kivy is a set of Python/Cython modules that can easily be installed via pip, but you’ll need a few dependencies. It uses Pygame as a rendering backend…

Installing Django The installation of Django is relatively easy once you have python installed. See for yourself as we build a simple app here 01 Create Virtual Environment Create a new directory for your project and navigate inside it using a new Terminal window. Create a new virtual environment for this project, opting to use the latest Python 3. Your Python 3 location may vary, so be sure to set the correct path for the binary package. 02 Activate and Install Using your Terminal window, activate the virtual environment to start the project-specific shell. VirtualEnv has a local version of the Python package manager pip installed, so it’s fairly straight forward to run the command to install Django. 03 Create Core Project The Django install contains some incredibly useful command-line…

In a previous article, we looked at how to combine multiple Raspberry Pis together to make a cluster of machines. But how can you make use of this small monster that you have created? Luckily, IPython is a great way to put all of these machines to work, getting some serious work done. IPython started out as an enhanced interface for Python, replacing the usual interactive interface that is available. The initial design involved creating a client/server system for IPython, which quickly allowed for some very interesting functionality. One of these extra capabilities is the ability to run multiple IPython servers that a single IPython client can connect to. You can then connect to these IPython servers and run processes in parallel. This first step is to install IPython on…

Many of the examples we have looked at in this column have been programs that run on the console. Here we will be taking a look at how you can include 3D graphics within your Python code. The hardware on the board includes a GPU, so you should be able to take advantage of everything this computer is capable of. Since we are going to be playing with graphics, this means that you will probably want to have an actual monitor connected to your Raspberry Pi. If you don’t have one, you can connect to your Raspberry Pi over SSH with X11 forwarding turned on. As long as you have an X11 server on your desktop, you can see the display on your local machine. To get access to OpenGL…

Resources Raspberry Pi Twilio account Text messaging, or SMS (Short Message Service), has become a staple of everyday communication. What began life as a 40 pence message service is now offered by most tariff providers as an unlimited service. Twilio, a cloud communications company, enables you to send SMS messages for free from your Raspberry Pi to a mobile phone using just six lines of code. 01 Set up your Twilio account The first step of this project is to register for a Twilio account and Twilio number. This is free and will enable you to send an SMS to a registered, verified phone. Once signed up, you will receive a verification code via SMS to the registered phone. When prompted, enter this onto the Twilio site to authenticate your…

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