I made a python text

● Text body (PDF format 299 pages: 3.12MB) Updated on 2020/05/14 (→ DL from mirror site) Main libraries mentioned: 　Kivy, argparse, socket, threading, concurrent, requests, 　BeautifulSoup, mpmath, subprocess, datetime, pickle, struct, 　base64, collections, enum, shutil, zipfile, wave, PyAudio, 　Tkinter → Sample program in the text __ [How to learn] __ Run the sample while reading Chapters 1 and 2. I think it is good to understand while doing so. (You can skip the parts that you find difficult) Read the other chapters as needed. Make your own variation of the execution example in the text You will deepen your understanding if you proceed while trying. For those who already know Python to some extent, grammar and examples I think it can also be used to find out. ● Library book (PDF format 185 pages: 3.41MB) Updated on 2020/06/03 (→ DL from mirror site) (Old name: Python3 module book) Library mentioned: 　OpenCV, Pillow, pygame, Eel, PyDub, NumPy, matplotlib, 　SciPy, SymPy, hashlib, passlib, Cython, Numba, ctypes, 　PyInstaller, JupyterLab, json, urllib, zenhan, jaconv → Sample program in library book Although NumPy and matplotlib are extremely sophisticated I'm worried about how much I should remember. So The amount of content that "If you remember it for the time being, it will be easier later" I'm looking for it. －－－－－－－－－－－－－－－－－－－－－ Introducing seminar activities using Python. → Introduction of activities applying Python －－－－－－－－－－－－－－－－－－－－－ I'm writing an article because I want people to think calmly about the strengths / weaknesses of Python in case some people blindly believe in Python. → Consideration of the advantages and disadvantages of Python －－－－－－－－－－－－－－－－－－－－－ [Useful link] ・ Compiled library for Windows It is a format to be installed by PIP. This is useful when the standard installation method does not work. (Since it is "Unofficial", please do so at your own risk.) －－－－－－－－－－－－－－－－－－－－－ [Data processing related] I am making a text about the basic knowledge for data processing in Python. It is still a prototype, and I would like to hear your opinions and advice. → Text of data processing by Python －－－－－－－－－－－－－－－－－－－－－ 【PySimpleGUI】 Probably the easiest GUI library for Python to use. I would like to hear your opinions as well. → Basic usage of PySimple GUI －－－－－－－－－－－－－－－－－－－－－ 　 (2017/05/16) I teach programming at school. I made an introductory text for Python 3 to teach beginners. It's a stance of an introductory book for those who have already mastered some language to quickly get used to Python. 　 It explains at once to the point where you can create an application using the GUI library "Kivy". (Introduction to Kivy) Also, an introductory explanation of requests and BeautifulSoup4 for web scraping is provided. (Basic explanation about Tkinter) 　 Although the degree of completion is still low, the text will be revised and updated if it is used in the field of education. We will publish it for free, so we would be grateful if you could give us your opinion. If you find any mistakes, please let us know. Contact information is on the back cover of the text.

Introduction page 　 Those who want to use this are welcome. I would like to improve the degree of perfection while receiving opinions. Especially, I hope it will be used by teachers who teach programming at school. We would appreciate it if you could give us any requests or suggestions from the field. (Reflect in the text as much as possible) If it is within the scope of this book, you can also send us your questions. We will do our best to accommodate you.

We also distribute Video Teaching Materials that summarizes the contents of the text.

Supplement (updates, information, etc.)

－－－－－－－－－－－－－－ [Supplement](2020/05 / 27-06 / 03) Added to the library book. I added various additions to the explanation about the handling of NumPy and SymPy matrices. I added an explanation of how to draw a pie chart and a horizontal bar graph with matplotlib. I added (how to specify the header) to the explanation part of the CSV output of the NumPy array. Other minor modifications 　 －－－－－－－－－－－－－－ [Supplement](2020/04 / 05-05 / 14) Added to the text body. I added a little to the part of split assignment. Added a commentary on float calculation error. Added a commentary on the zipfile module for handling ZIP archives. The most basic explanation about pprint is posted. Some additions to the regular expression. We have posted a sample to convert a number with a decimal point to a binary number / reverse conversion. Added a commentary on the chain of comparison operators. Some additions to the appendix "Management of memory usage". Other minor corrections (I find embarrassing mistakes every time I check ...) 　 Added to the library book. Added an explanation of how to draw a 3D bar graph with matplotlib. Also, some additions to the explanation of zero matrix creation (NumPy). The file I / O method was added to the explanation of the json module. Some additions to the min, max, argmin, and argmax parts of NumPy. I explained how to plot polar coordinates with matplotlib. In the sympy module section, we have included a description of the var function and a set of functions related to prime numbers. 　 (Apology) There was an error in the explanation about LaTeX output in the sympy section of the library book. Please replace it with the latest version as it has been corrected. 　 －－－－－－－－－－－－－－ [Supplement](2020/03 / 13-24) Added to the text body. Added explanation of how to output a file with the print function. Added a commentary on how to write a tuple of variables after the for statement and perform split assignment. Added explanation about collections.Counter. Added a commentary on issubclass to check the inheritance relationship of classes. Added regarding the output of WAV files. Other additions and corrections

Added to the library book. Explains how to aggregate NumPy arrays uniquely. Explains how to insert and delete elements in NumPy arrays. 　 －－－－－－－－－－－－－－ [Supplement](2019/12 / 01-20) Added to the text body. Added (re.sub, re.split) to the regular expression. I added a commentary on splitlines that splits a character string that spans multiple lines. The explanation about the assignment formula (Python3.8 ~) is included. Added a description of the argparse module for command argument parsing. A rudimentary explanation about the enum module is included. Other minor corrections and additions. 　 －－－－－－－－－－－－－－ [Supplement](2019/09 / 01-14) Some additions and corrections to the text body. We have posted a sample program that enumerates all Unicodes in which characters are defined.

－－－－－－－－－－－－－－ [Supplement](2019/08 / 01-31) Added to the text body. -Addition of basic explanation about assert and raise that raises an exception -Added to the explanation about dictionary objects -Addition of explanation about bit operation -Addition of explanation about shutil module ・ Other additions and corrections

You have pointed out (or scolded me) about the notation of the "" symbol. Since the text is written in TeX, it is difficult to put out the half-width "Japanese yen symbol", and there were many parts that were written using the full-width "¥". As you pointed out, this is a very bad thing, so I'll fix it. → (It has been fixed considerably)

Added to the library book. An example of the procedure for drawing a 3D scatter plot with matplotlib is posted. I also started writing about SciPy. Other additions and corrections. __Correction and apology __: There is an error in the sample program scatter3d01.py published in the 7/31 version of the library book. Please replace it with the latest version as it has been corrected. 　 －－－－－－－－－－－－－－ [Supplement](2019/06 / 08-07 / 26) Added to the text body. A sample program to investigate how much the calculation speed changes depending on whether or not NumPy is used is included in the appendix. Also, I added an explanation of how to suppress the display of warning messages and a content that introduces memory-profiler that checks the memory usage of the Python processing system. These are required when processing data with Jupyter Lab. 　 Some additions to the NumPy part of the library book. I explained how to apply the high speed of matrix operation and how to handle images as array data. We also added a description of the table function that draws a two-dimensional array as a table with matplotlib. __Correction and apology __: In the explanation of NumPy's FFT, "amplitude spectrum" was mistakenly described as "power spectrum". I'm sorry. I have corrected it, so please replace it.

－－－－－－－－－－－－－－ [Supplement](2019/05 / 21-06 / 06) The name "module book" may not be good. There are still errors in the handling of terms such as "module", "package", and "library" in the contents of the distributed text series. I started thinking about fixing it. Change the name to "Python3 Library Book".

According to the Ministry of Education, Culture, Sports, Science and Technology website, Python is used for programming in high school information departments. It is written. I feel that the content of the text to be distributed needs to be considered very carefully.

－－－－－－－－－－－－－－ [Supplement](2019/05 / 01-18) Added to the text body. I added a commentary on enumerate. The more you learn Python, the more you realize that it is a treasure trove of tricks for ease of use.

Added to the module book. I added the part of NumPy. The basic usage of the PyDub module is posted. In addition, some additions related to OpenCV and PyGame. It's almost time to check (overhaul) the module book as a whole (please wait)

－－－－－－－－－－－－－－ [Supplement](2019/04 / 06-30) Added to the text body. Since f-string is a very convenient function, I have included an explanation of its basic usage. Also, added a brief explanation about Anaconda's conda command. Added to the module book. I added an explanation of how to draw a heat map with matplotlib and how to convert an image into a numerical array of pixels. In addition, some explanations of NumPy have been added and modified. 　 －－－－－－－－－－－－－－ [Supplement](2019/02 / 22-03 / 28) Maintenance of the text body.

• There is an error in the explanation of ProcessPoolExecutor regarding multi-process execution.
• There is an error in the explanation about the zip object We apologize to all the users. It has been corrected, so please replace it with the latest version. 　 Added a basic explanation about the struct module to the text body. It is required for the generation and expansion of binary data. Some additions to the explanation of the object-oriented and function definition parts. Added a basic explanation about "slice objects" that clearly treat "slices" attached to data structures as objects. I don't usually use it much, but I explained it because there are a few opportunities to handle it when processing data with Pandas. 　 Module book maintenance. Some additions and corrections in the explanation of NumPy and matplotlib. 　 －－－－－－－－－－－－－－ [Supplement](2019/01 / 01-02 / 21) Adjusted the appearance of the text body slightly. Also added a basic explanation about the base64 module and an explanation about inf and nan. 　 In the latest Python, the handling of object comparison by "is" has changed slightly, so changes accordingly. (Is it a bug fix in Python itself ...) 　 The user advised me, "Is the all, any function important?" It's a convenient function for data processing, so I added it immediately. (Thanks to those who gave me advice) 　 I posted a sample program about how to handle fonts in Kivy. 　 It's about the end of the year, so we'll be working on text maintenance. It seems that there will be more updates over the new year. 　 －－－－－－－－－－－－－－ [Supplement](2018/12 / 16-26) Added to the text body. Added a basic explanation of the with syntax. The with syntax is useful for neatly finishing programs that perform processing such as file access and communication. Added a description about the processing time when accessing the data structure. In Python, "list", "set", and "dictionary" are the basic data structures, but if they are not used properly, it may take a surprising amount of time to process. I hope it will be the basic knowledge for that judgment. The explanation of the basic usage of the fractions module is posted. You can calculate fractions. (Other minor additions and corrections) 　 －－－－－－－－－－－－－－ [Supplement](2018/12 / 06-10) Added to the text body. Added a basic explanation about the generator. Also, some additions (and other minor corrections) related to list alignment and inversion. 　 －－－－－－－－－－－－－－ [Supplement](2018/11 / 26-12 / 05) Added to the text body. Added a basic explanation about the pickle module. It is necessary to save the contents of the data structure handled by Python as binary data in a file. The binary data saved by the pickle module function is very convenient because it also includes the data type of the target data and class definition information (method definition, etc.). Also, some additions. 　 －－－－－－－－－－－－－－ [Supplement](2018/10 / 24-11 / 02) Added to the text body. Some additions have been made to the description of the pathlib module. We have also posted a sample program that applies this module to find files in directories (recursively). Also, I added a commentary on the type function that checks the data type. 　 Added to the module book. Added explanation about the basic usage of json module. 　 －－－－－－－－－－－－－－ [Supplement](2018/10 / 08-11) One of the consultations I have received from time to time is "Are there any Python exercises?" Creating something like a collection of questions is one idea, but I think it is a good idea to "create your own exercises" as an effective learning method. Specifically, I think it is better to create a variation (variant) of the execution example in the text by yourself. 　 It is difficult to get to the point of creating a collection of questions, but in the field of education, the current situation is that students (students) are asked to make small exercises on the spot while watching their movements. .. It is relatively effective, so it is recommended to "play with the text execution example". 　 Added to the text body. I have posted a rudimentary explanation of the zip function that combines multiple data strings into an iterator. Also, a description about the functools module. 　 Some additions to the module book. Contents related to the computer algebra module SymPy. I've included a brief explanation of the ʻis_'property that checks expressions and a description of how to pattern match. 　 －－－－－－－－－－－－－－ [Supplement](2018/09 / 22-25) Added to the text body. Added explanation of how to start an external program with the os.system function. 　 Added to the module book. I wrote how to use jaconv. 　 Other minor corrections and additions. 　 －－－－－－－－－－－－－－ Supplement Added to the text body. I briefly explained how to selectively extract parts from a data structure. In python 　　a,b = 2,3 You can write an assignment statement such as, but this should be seen as "a part of the variable sequence and the corresponding data structure was referenced" rather than seeing that the assignment worked in parallel. By applying this, it is easy to analyze fairly complicated data structures. It's not as much as "unification" in Prolog, but it's a "slightly nice feature". 　 －－－－－－－－－－－－－－ [Supplement](2018/09 / 12-14) Some additions to the text body. I wrote that the function defined by the def statement can be deleted by the del statement. (In addition, some corrections) 　 Python also has exec and eval, which means that it can be dynamically programmed during execution. In other words, "what Lisp can do can be done almost entirely in Python." This is "a great strength as an AI development environment." Python has a powerful set of packages for DNN, and you can link C / C ++ libraries at runtime. Furthermore, it is easy to link with Prolog, so it feels like the AI development environment is ready. 　 Also, added a description of the basic usage of passlib and PyInstaller to the module book. Added a brief explanation on how to set rasterization when reading EPS with Pillow module. (Other minor additions / corrections) 　 －－－－－－－－－－－－－－ [Supplement](2018/09 / 01-11) Added to the text body. I wrote the notes when loading the module. Just in case "From module name import *" There are people who do it, but it is the cause of "name collision accident". Be careful when doing this. Also, I added some explanation about how to write'\ _ \ _ init \ _ \ _. Py' when creating your own package. In addition, some additions regarding the comparison of objects by'is'. 　 Added to the module book. Explains how to encode / decode multibyte characters using urllib. This is a method to convert multi-byte characters included in Web URLs to character codes with'%' (and vice versa). I also posted a basic explanation about the module zenhan that converts full-width ⇔ half-width character strings. 　 －－－－－－－－－－－－－－ [Supplement](2018/08 / 22-29) Added to the text body. Added a brief explanation on how to start the Python interpreter by command operation under Anaconda environment. (Other, some additions and corrections) 　 The number of Anaconda users is starting to increase around me. It seems that there will be situations where the explanation of the PSF version of Python alone cannot handle it. 　 －－－－－－－－－－－－－－ [Supplement](2018/08 / 15-21) Additions and corrections to the text body. Added some additions and corrections to the explanation of the map function, and added explanation about Tkinter's messagebox. 　 The number of pages of text has increased considerably, but there are not many parts that beginners should read first. I wrote such a thing in the "Introduction" chapter. 　 Also, some additions to the explanation of SymPy in the module book. 　 －－－－－－－－－－－－－－ [Supplement](2018/07 / 25-08 / 11) When creating cross-platform apps and modules, it is necessary to acquire information about the computer environment. So I put the basic usage of the platform module in the text body. 　 There was an error in the explanation of the strftime format specification. I apologize to you. Please replace with the latest version. 　 Other minor corrections and updates. (Reference of environment variables, processing of character strings, etc.) 　 It was confirmed that the sample program of the text itself, including Kivy and sound, works with 3.7 for the time being. However, I will recommend 3.7 to others a little earlier. 　 －－－－－－－－－－－－－－ Supplement Recently, I've been getting a little more consultation about "Kivy has stopped working". Basically "Please uninstall all Kivy related packages and then reinstall." However, there were cases where it could not be resolved. In the case I dealt with, it was caused by "SDL2.dll version difference". As a workaround, I obtained the latest stable version of SDL2.dll from SDL official website, installed it, and then uninstalled and reinstalled Kivy. Worked. (This matter was also posted in the text itself) 　 For your reference. 　 (Further supplement) Be sure to obtain the dll from the "correct source", not just the SDL. At first glance, it may look like an "official site" or "authorized redistribution site", but in fact, it may come with malware, so please be careful. 　 －－－－－－－－－－－－－－ Supplement A brief introduction about Anaconda is posted in the main text. When starting Python, many people are wondering whether to use the genuine distribution of PSF or Anaconda. Anaconda is good for data processing. In particular, Anaconda is recommended for students because it comes with a large number of libraries (modules) in advance and it is easy to manage packages. I think that you will not have a hard time installing various modules. 　 One thing to note is ・ It is not so good to mix PSF version and Anaconda ・ Be careful about PIP in Anaconda environment There is. In the worst case, it will destroy the Python environment and you will have to reinstall it. Of course, in many cases it is "generally okay" to install the module with PIP under Anaconda environment, but always be careful. 　 As an aside, when using Python on Windows, you have the option of using the MSYS / MinGW environment instead of the PSF version or Anaconda. This realizes a UNIX-like development environment (POSIX environment) in a Windows environment, and is completely different from virtualizing a system using VirtualBox or the like. Even in this case, the pre-built packages for Python are starting to be available, so I think it's good to have more choices. However, using Python with MSYS / MinGW is not recommended for students. 　 －－－－－－－－－－－－－－ Supplement When you start using Python and modules actively, package management becomes troublesome. In the current text, I explain how to install with the plain Python installer (PSF version) and basic package management with PIP, but I feel that Anaconda can not be ignored soon. (Students who use Python at home seem to choose Anaconda) 　 Let's think about it for a moment. 　 －－－－－－－－－－－－－－ [Supplement](2018/07 / 07-15) Added to the text body. The basic explanation about namedtuple of collections module is posted. It's a pretty convenient data structure. Use namedtuple when you say "it's not enough to define a class ...". 　 It's been more than a year since the text was released, and I feel that the content has been completed in one step, so it's time to do the entire proofreading work (cleaning) once. I will continue to make minor corrections for a while. 　 Also, I'm starting to watch Python 3.7. So far, the samples introduced in the text itself are mostly working, but Kivy is still useless in my environment ... It is safer to refrain from putting 3.7 into action now. It seems that it will take a little longer for various modules to support 3.7. 　 You can install 3.6 and 3.7 at the same time and select the version at startup, so I think it's a good idea to install 3.7 and check the operation. A commentary is also posted in the main body of the text about how to start switching. (2.7 can also live together) 　 －－－－－－－－－－－－－－ [Supplement](2018/07 / 04-05) The basic usage of Eel is described in the module book. I am very grateful to be able to build a GUI within the framework of HTML5. Moreover, it is very easy to use. Eel can be expected to develop in the future. Since Python and JavaScript can be used at the same time for application development, the convenience is immeasurable. (Eel's GUI base is Google Chrome) 　 A point to note when using Eel is the exchange of values between Python and JavaScript. Since they are different processes, you can pass arguments to the function call, but you can't simply return the value with return (it's not impossible, but it's a bit of a hassle), so it's a bit unique. And simple) is required. 　 However, for those who are accustomed to HTML5, using Eel is the easiest way to build a GUI application. Moreover, since it is HTML5, both GUI functionality and design are outstanding. In addition, various JavaScript libraries can be used, so if you express it exaggeratedly, you will be happy with the feeling that you can create any app. 　 I also make JavaScript text. This has a strong "unfinished feeling", but please give us your opinion again. 　 －－－－－－－－－－－－－－ [Supplement](2018/07 / 01-04) A basic explanation of the exec function and eval function is included in the text body. It is a very convenient function that can execute data as a program. 　 Also, when displaying an image by combining Tkinter and Pillow, there is a surprising point in handling PhotoImage ... "The image is not displayed in Tkinter ..., I do not know the cause ..." There is a pitfall that seems to be such a thing. ， Please read. 　 －－－－－－－－－－－－－－ [Supplement](2018/06 / 18-07 / 01) The basic explanation of Tkinter is posted in the main body of the text. Also, I found some distorted terms (mistake of "function" and "method"), so I corrected it. I think that updates (corrections) will continue for a while. 　 Please continue to "impression", "point out errors", and "requests". We look forward to. 　 －－－－－－－－－－－－－－ Correction and apology There was a serious error in the text itself ... Corrected an error in the explanation of how to create a module. 　 We apologize to those who are using it. Please replace with the latest version. 　 Thank you to M.K. for pointing this out. It really helps. 　 I would appreciate it if you could point out in the future. 　 －－－－－－－－－－－－－－ Supplement There are a few messages saying "Would you like to explain Tkinter?" (From the beginning ...) I was wondering if Kivy alone would be fine, but Tkinter cannot be ignored in terms of ease of use. Consider. 　 －－－－－－－－－－－－－－ [Supplement](2018/05 / 26-29) Added to the text body. Added the explanation of the date / time format formatting method (format formatting by strftime) of datetime. Also, some additions to the sort method that sorts the elements of the list. 　 －－－－－－－－－－－－－－ [Supplement](2018/05 / 22-23) Added to the text body. Added an explanation about setting whether to handle multiple lines in Kivy's TextInput. I also added a rudimentary explanation about "iterator". I thought it would be necessary for the introductory book, but I felt that the students would be in trouble later if I didn't give an introduction. 　 Also, I added a description of how to get the file size, and found an error in the explanation about finditer for character string search, so I corrected it. 　 In addition, some mistakes in terms such as the mistake of the words "function" and "method" have been corrected. However, it seems that the term is still suspicious ... (Continued correction) 　 －－－－－－－－－－－－－－ Information We have released a text (prototype) about the basic usage of the data processing package. → Text of data processing by Python "Data processing" has a meaning only when it has an individual purpose, so it does not fall into the category of "explanation of language". Therefore, if you write only what you teach, the content will be quite narrow, so please give us your advice and suggestions again. 　 －－－－－－－－－－－－－－ Supplement Added to the text body. Added the method of setting the encoding (specifying the character code) when using the standard input / output by the sys module. 　 －－－－－－－－－－－－－－ Supplement Added to the text body. I made some additions about how to format and how to use the pathlib module. 　 －－－－－－－－－－－－－－ Supplement Added to the text body. Added a method to read the specified number of bytes of data from a binary file. 　 Nowadays I wonder, "Why didn't you give an explanation earlier?" It seems that there are still many things to go with this amount. 　 －－－－－－－－－－－－－－ Information We received opinions from those who obtained the text itself. You said, "It's too much," but at first you only need to use Chapters 1, 2, and 4. In short, the first thing you need is just over 60 pages. 　 Please postpone Kivy, sound, etc. and use it as needed. If you want to print the PDF on paper, we recommend "double-sided printing". 　 －－－－－－－－－－－－－－ Supplement Added to the text body. I didn't mention anything about "standard error output", so I added it this time. 　 －－－－－－－－－－－－－－ Information Several people have consulted that Jupyter related modules suddenly stopped working. 　 It also occurred in my environment, but it was solved by uninstalling the related package and installing it again. 　 －－－－－－－－－－－－－－ Supplement Added to the module book. I posted an example of using the input function on Jupyter Notebook. 　 －－－－－－－－－－－－－－ [Supplement](2018/04 / 11-16) Added to the text body. I found an error and corrected it. It is a range that is often used for repetition such as for, but you see this as a function that returns an object of the range class. (Complicated ...) It's easy to mistake whether it's a function or an object. 　 It feels like the materials for the new semester are ready. However, the update is unlikely to end for the time being. 　 －－－－－－－－－－－－－－ [Supplement](2018/04 / 01-6) Some additions to the module book regarding Jupyter Lab. Added a basic explanation of how to format and display mathematical expressions with MathJax when using the computer algebra module (SymPy) and how to play sounds. 　 －－－－－－－－－－－－－－ Supplement Added to the text body. You can use Japanese for variable names in Python3. It was a complete blind spot. I feel like I was asked by a student, "Can I use Japanese for variable names?" And said, "No! Start writing in half-width alphabets!" Very embarrassing ... 　 －－－－－－－－－－－－－－ Supplement Added to the module book. The explanation of the basic usage of Jupyter Lab is posted. When dealing with tables and graphs when using Python in interactive mode, it is important to have a certain level of visibility and usability. Especially when doing data analysis and modeling, I think Jupyter Lab is good. The style of executing Python scripts as an application is important, but I think that the style of interactively using it as a "workbench" will also be important in the future. I have a feeling that JupyterLab will become the standard interface for Python. I'm writing a textbook on statistical analysis and machine learning, but I'll rewrite all the parts that illustrate the work in Jupyter Lab ... 　 Jupyter Lab is likely to be updated frequently in the future. Keep an eye on it. 　 －－－－－－－－－－－－－－ Supplement Added to the text body. When managing packages with the pip command, the pip command cannot be executed directly if the pip command directory is not registered in the command search path. In that case, pip will be executed via the Python processing system. I added about the method. 　 －－－－－－－－－－－－－－ [Supplement](2018/02 / 19-20) Some additions to the text body. In Python, the distinction between global / local variables (variable scope) inside and outside the function definition gives a subtle impression. Before you get used to it, you may suffer from strange behavior. If you inadvertently create a bug that is difficult to find, I added this. 　 When converting a byte string to a string object, you may not understand the character code system, but we also added a basic explanation of the chardet package for identifying it. 　 As we enter spring break, we will have more work to update. 　 －－－－－－－－－－－－－－ [Supplement](2018/02 / 12-16) Added to the module book. Added a basic explanation on how to handle sprites in the pygame library. This is an essential function for game development. 　 The text itself has also started maintenance. We plan to update it several times for the new semester. It was pointed out that the operation verification of the sample program in the Mac environment is not good. Please wait for a while as we will verify everything once. 　 －－－－－－－－－－－－－－ Supplement Added to the condition judgment part of the text body. Explains the behavior when a special value is given to the conditional expression. 　 It seems that it is better not to use logical operations (and, or, not) of values other than truth values (True / False). I think that it is necessary to individually verify what the value will be as a result of logical operation. Otherwise, you will end up with bugs that are hard to find. 　 Also, the List of sample programs posted in the text has been released. You can download it. Please understand that this is a program made "quite redundantly" for students (beginners). It is "sloppy" by preparing extra variables and splitting lines. Actually, it can be written more concisely, so feel free to improve it. I think it will be a good training. 　 －－－－－－－－－－－－－－ [Supplement](2018/01 / 13-14) Added to the text body. A simple point came out, "How do you round off?", So I added it. Added to the module book. Added a method to skip heading lines when reading CSV data with NumPy. 　 You can use sprites in pygame. Making games will be fun. I will investigate how to use it and add it to the module book. (It's a spring break issue) 　 －－－－－－－－－－－－－－ Supplement Careless mistake found in the text body ... Corrected. I found a mistake just by looking at it. It seems that there are quite strange places scattered around this ... 　 I will overhaul this spring break to prepare for the new semester. (Of course, we will fix it as needed) 　 －－－－－－－－－－－－－－ Supplement Happy New Year. I look forward to working with you again this year. 　 Both the text body and the module book have been slightly revised. We would appreciate it if you could point out and give us your opinions this year as well. 　 －－－－－－－－－－－－－－ Supplement Added text body and module book. Graduation research has also become the last spurt, and while giving guidance, specific additional items are increasing one after another. There may be more updates throughout the next month. 　 －－－－－－－－－－－－－－ [Supplement](2017/12 / 22-23) Added to the text body. Added the character string replacement method and the character string search part by regular expression. (Other, some additions) 　 Current status report on the preparation of textbooks and teaching materials related to statistical analysis and machine learning. I feel that I have demonstrated and explained the most basic parts of statistics (probability distribution, estimation, hypothesis testing, etc.), but the parts related to modeling and machine learning are yet to come. 　 It is likely that it will be usable at school (workplace) within the next fiscal year. 　 －－－－－－－－－－－－－－ Supplement Added to the text body. Added a commentary on how to detect the end of audio playback and repeat playback in the section related to PyAudio and wave modules. 　 －－－－－－－－－－－－－－ Supplement Added index items to module book. I also fixed the appearance disorder. 　 I received an inquiry from a professor (friend) at another university and asked, "What is the permission to use the text?" The published text is "free software". We retain the copyright, but feel free to use it for commercial or non-commercial use. You can print and redistribute it, but please do not change the contents. 　 From such a thing, I am grateful for those who can request corrections and tsukkomi, so I am doing it freely. (We look forward to your suggestions) 　 －－－－－－－－－－－－－－ Supplement Corrected an error in the text itself. Thank you to Mr. Y.N for pointing this out as well. 　 －－－－－－－－－－－－－－ Supplement Added to the text body. It's Kivy related after a long time. Added the handling method at the start and end of the application. 　 Current status report on the preparation of textbooks and teaching materials related to statistical analysis and machine learning. The work is progressing, but the range of the contents to be handled is wider than I expected and I am sighing ... 　 Many of the requests we receive are to compactly summarize how to use various packages, but there are many packages and this field is completely meaningless for students without basic knowledge (statistics). As it becomes unclear, I'm starting to mention basic statistics ... 　 Therefore, it seems that it will take some time before we see the light of day. 　 －－－－－－－－－－－－－－ Supplement Added to the module book. 　 Added a method to "vectorize" user-defined functions with NumPy. I am preparing teaching materials for data science and machine learning, but since it is important to improve the efficiency of processing for a large amount of data, I wrote about how to speed up processing by vectorization. 　 Preparations for data science and machine learning, but it takes time to prepare sample data and think about easy-to-understand explanations of basic theory ... 　 Also, while using the students as a laboratory table ... (laughs) 　 －－－－－－－－－－－－－－ Supplement Added to the module book. 　 Added explanation about the graph drawing function of SymPy (computer algebra module). 　 －－－－－－－－－－－－－－ Supplement Added the text to deal with the troubles that occur when using Kivy. (Added to the chapter of the appendix) 　 You can select and set the graphic API used by Kivy. If this is not set properly, programs using Kivy may not work. 　 Thank you again for pointing out from Mr. Y.N. Since I am editing the text by myself, I am in a situation where I cannot test many cases in advance, so I would appreciate it if you could point out. 　 In another case, I added a module book about matplotlib. Added explanation of how to use Japanese fonts for graph headings and labels. 　 －－－－－－－－－－－－－－ Supplement Corrected typographical errors in the text body. 　 Thank you to Mr. Y.N for pointing this out. 　 We are currently preparing to explain how to use modules related to statistical analysis and machine learning. (It will take a long time this time ...) We would appreciate it if you could point out and request. (To: Everyone) 　 －－－－－－－－－－－－－－ Supplement Added to the module book. 　 I added an explanation about how to draw multiple graphs on one sheet with matplotlib (how to use subplots). 　 －－－－－－－－－－－－－－ Supplement Added text body for map, lambda, filter. 　 It is useful for writing a clean program like Python. There is an impression that "Python is like LISP". I personally like this feature. 　 －－－－－－－－－－－－－－ Supplement Some corrections and additions to both the text body and the module book. 　 -Storage order of left and right audio when WAV audio is read by Numpy ・ A little introduction of functions that can be used with Numpy 　 －－－－－－－－－－－－－－ Supplement Added a description of ctypes to the module book. 　 I added an explanation about how to pass data (handling arguments and return values) so that you can develop firmly in C language & Python. 　 －－－－－－－－－－－－－－ Supplement Added how to use ctypes (introductory level) to the module book. 　 Naturally, it's the fastest. (It is natural because it is C language) 　 In the future, I will try using Cython, Numba, and ctypes in seminar activities, and add the obtained tips. 　 －－－－－－－－－－－－－－ Supplement Added how to use Numba (introductory level) to the module book. 　 It feels like I've touched Cython and Numba, but I feel that I have to grasp the "points" of speed tuning. 　 After all, it may be certain that the speed measure is "write in C and call from Python". 　 We would love to hear your opinions on this as well. 　 The next speed measure is ctypes. 　 －－－－－－－－－－－－－－ Supplement As soon as I wrote the explanation of Cython, I received advice from teachers of other universities. "There is Numba" "Ctypes are good for connecting to C programs" ... I am very grateful. It looks very good, so I'll try to organize how to use it. 　 Cython feels like a "unique language", and it feels like it's a little different from Python. So, the opinion was that "Numba, which applies LLVM, is better." I would be grateful if it is highly compatible with the original Python. I will investigate. 　 －－－－－－－－－－－－－－ Supplement I started writing how to use Cython in the module book. I'm using Python in my seminar, but I'm starting to complain about the execution speed. For those who are not good at C language, this is an easy way to speed up Python programs. 　 The commentary on Cython is likely to continue to be revised. 　 －－－－－－－－－－－－－－ Supplement The notation of terms in the text body has been partially revised and added. 　 －－－－－－－－－－－－－－ Supplement Some additions to the text body regarding how to use mpmath. 　 －－－－－－－－－－－－－－ Supplement Added to the module book. I have included a brief explanation of how to create an animated GIF with Pillow. 　 －－－－－－－－－－－－－－ Supplement A professor from another university advised me, "Is the method of accessing the database important?" I'm sorry, I have only one body ... But I'll put it in my "to-do list". (Is it SQLite and MySQL?) 　 Given our current priorities, we are keeping in mind the direction towards machine learning. 　 －－－－－－－－－－－－－－ Supplement Today, the number of accesses has exceeded 15,000. Responsibility is getting heavier. I'm afraid that the text will break. 　 In both the text body and the module book, the terms are a little suspicious. 　 In the library to be imported and used, there are some parts of writing that are not clear whether it is a "class method" or a "library function". 　 Please be patient and keep in touch. 　 －－－－－－－－－－－－－－ Supplement Added how to install Kivy on Mac. I added it because there was a request from a Mac user. 　 －－－－－－－－－－－－－－ Supplement After all, it seems better to be prepared to teach how to use the pandas module to deal with the theme of data science. I'm thinking of starting here once the arrangement of Japanese processing methods is complete. 　 After all, this summer vacation seems to have spent time organizing the input / output of Japanese voice and the method of morphological analysis. 　 －－－－－－－－－－－－－－ Supplement-2 I was scolded by my acquaintance's Mac fan. I heard that the name of the Mac OS is incorrect, so I corrected it immediately. 　 －－－－－－－－－－－－－－ Supplement Added a method to install Python3 on Apple's Mac (OS X, mac OS) in the text body. I added it because there was a consultation from a Mac user. 　 There is a slight difference between Windows and Mac in how to start the Python interpreter and PIP commands. 　 －－－－－－－－－－－－－－ Supplement Added to the text body about how to delete files and folders (empty). Also, I added it because there was no explanation about how to write the conditional expression. 　 －－－－－－－－－－－－－－ Supplement Added to the text body. I have included a brief explanation of how to use the mpmath module to calculate large numbers of digits. 　 This is to accommodate students who have the theme of enlarging the image of the Mandelbrot set indefinitely, but in reality it will be written in C using GMP. It's a theme that allows you to understand the strengths and weaknesses of Python. 　 Also, I added about how to handle global variables inside the function definition. I forgot to explain the basics. 　 －－－－－－－－－－－－－－ Supplement I found an apologetic typographical error in the text itself. Fixed. I made a typo in Kivy's commentary "Setting to fix window size (prohibit resizing)" ... 　 －－－－－－－－－－－－－－ Supplement I received a question from a student. "What kind of syntax is with?" Is the question. 　 I think it's a Python-like part, so I'll add it, but I'll take some time to think about whether I can write an easy-to-understand explanation. 　 －－－－－－－－－－－－－－ Supplement Added the basic usage of the concurrent.futures module to the text body. I posted a sample program and demonstrated how to check the difference in execution time between multithreading and multiprocessing. 　 You can see its merits in a computer environment with a large number of CPUs and cores. 　 －－－－－－－－－－－－－－ Supplement Added text body for subprocess module. Added the explanation of the method (wait method) to synchronize with the end of the external process. 　 －－－－－－－－－－－－－－ Supplement Some additions to the text body. The explanation of how to get the command argument was missing. Also, pathlib seems to be useful, so I added an explanation of the basic usage. 　 A professor from another university pointed out about parallel processing. It is said that the threading module cannot utilize the performance of machines with many CPU cores. This was my ignorance. I heard that the concurrent.futures module is good, so I will try various things and then add to the text itself. 　 －－－－－－－－－－－－－－ Supplement Added text about Kivy. Added an explanation of how to delete a widget once registered. 　 Some students have begun to make trial and error about making apps. As I search for a way to build an elaborate GUI, I have a feeling that Kivy will continue to be added in the future. 　 －－－－－－－－－－－－－－ Supplement Added text about Kivy. (How to use Scroll View / Scroll View) I added it after receiving a consultation from a student who wanted to scroll and display a large widget. Certainly an important feature. 　 －－－－－－－－－－－－－－ Supplement Additions related to exception handling to the text body. 　 It may be my subjectivity, but I feel that learning Python will increase the number of students who are aware that they can create apps for themselves. 　 In the class, I use Java to teach programming, but I feel that doing Python in a seminar is more responsive. (Although it is still a long time before we can see realistic educational results ...) 　 －－－－－－－－－－－－－－ Supplement Added to the explanation of SymPy in the module book. Some additions to the explanation part of exception handling in the text body. Also, format correction and index addition. 　 －－－－－－－－－－－－－－ Supplement Additions on how to use subscripts. I can't stop adding basic items. 　 －－－－－－－－－－－－－－ Supplement In preparation for handling big data in the near future, I added a method for random access to files. However, it is only a method of seeking files. Text body 　 －－－－－－－－－－－－－－ Supplement Some students want to do Python on their home PC. It's very good. That's why I started to get advice on how to install it. However, the latest information about Kivy can only be seen on the original English site ... So, I added how to install Python, how to use PIP commands, and how to install Kivy in the text itself. Text body 　 http://www.lfd.uci.edu/~gohlke/pythonlibs/ has a compiled wheel package (for Windows) There is. This is useful when direct installation from the net fails with PIP. It says "unofficial", so at your own risk ... 　 It is said that "Japanese translation of Kivy document site" by @dario_okazaki has been completed. Kivy Document Site I am very grateful. I also recommend it to students. 　 －－－－－－－－－－－－－－ Supplement-2 Students who find an embarrassing mistake in the text will be delighted as if they had taken the head of a demon. 　 I haven't been bitten by the Kramer so far, but I've been dealing with cracks ... 　 Also, there is a request from a teacher at another university, not from a student, to "summarize how to use pandas." 　 After processing the grades, I think I'll try pandas when I enter the summer vacation. (I don't know when it will be written, so just in case) 　 －－－－－－－－－－－－－－ Supplement An introductory explanation of pygame has been added to the module book. Module Book 　 From the name of the module, it seems like a "game development library", but the reality is that SDL is wrapped a little to make it easier to use. It does not provide any functions that are particularly advantageous for game development. (There is no such thing as a platform dedicated to game development) 　 It is suitable for the case of "I just want a window drawing library that is easy to use and works lightly". I think it is also good for people who say "No need for a good GUI library!" 　 What is worrisome is what kind of relationship it will have with Pyglet and PySDL in the future. There is an atmosphere that Pyglet and PySDL2 will replace pygame, but I'm not sure if pygame will be less lively ... It may be different for each module, but we should pay attention to each module in the future. 　 The feature of pygame is that it is "easy and fast", but I think that you will still be dissatisfied with drawing lines (laughs). So far, I have no complaints about solid drawing. 　 I love Kivy and I'll be paying attention to it in the future, but I think pygame is overwhelmingly advantageous for quick experimental drawing in Python. Of course, I think it is also suitable for game development. (Just in case)

Kivy is recommended for making "decent apps". 　 －－－－－－－－－－－－－－ Supplement Since it became necessary to execute window drawing and keyboard & mouse handling at high speed, I started to summarize how to use Pygame. 　 I will add it to the module book soon. 　 －－－－－－－－－－－－－－ Supplement Added to the text body. Added the method to check whether the key exists in the dictionary in the explanation part of the dictionary type object. Also added about data type conversion. I realized that the explanation of the surprisingly rudimentary matters was missing. After all, when you actually start using the text, you will find cracks one after another. Text body 　 －－－－－－－－－－－－－－ Supplement The introduction explanation of hashlib is included in the module book. Module Book (Cryptographic hash generation module) It is necessary for concealing password character strings and creating digital signatures for documents. 　 －－－－－－－－－－－－－－ Supplement I added the "Generate list using for" part of the text body, and also added the conversion between characters and character codes. Text body 　 When students start using it, the parts to be added will appear one after another. 　 －－－－－－－－－－－－－－ Supplement "Disclaimer" was added to each text. 　 －－－－－－－－－－－－－－ Supplement I added a little bit to the text itself. (Part of subprocess) Also, I added a commentary on how to concatenate character strings. (I missed the explanation though it is an important method) Text body 　 －－－－－－－－－－－－－－ Supplement The index of the text itself was poor, so I added a little bit. Text body 　 －－－－－－－－－－－－－－ Supplement I received a question (request?) "Would you like to explain the pandas module?" 　 please wait for a while. I also have only one body ... However, I was worried about it, so I may start it around the summer vacation. I will actually need it for my seminar activities ... (I have no promise when it will be) 　 It seems that pandas is useful for statistical analysis. 　 －－－－－－－－－－－－－－ Supplement I started to write numpy and matplotlib in the module book. Module Book 　 From now on, it seems that the number of additions to the module book will increase with the activities of the seminar. 　 －－－－－－－－－－－－－－ Supplement Added a method to start an external program using the subprocess module. Text body It also explains how to start multiple external programs and pipe I / O asynchronously with them. 　 Regarding the asyncio module, it seems that it goes beyond the scope of "beginner" and "introduction", so I am thinking of making it a commentary content in a form different from this text. (Slight policy change) 　 After that, if you put an introductory explanation of the numpy and matplotlib modules in the module book, it seems that you can use it as a teaching material for seminars for a while. 　 Also, I added a method for generating random numbers. (Indispensable for creating games) 　 －－－－－－－－－－－－－－ Supplement Numpy is a standard for high-speed numerical operations in Python. However, numpy is not universal in every aspect of the research subject, and in order to obtain a numerical solution of an arbitrarily set differential equation, it is necessary to write a simulation program individually. 　 Regarding numpy, I will write an introductory explanation in the module book, but I have to deal with the theme of my seminar as soon as possible, so I will write the simulation code in C language for a while. 　 So, we will call the program (executable file) written in C from Python and throw only the part that requires speed to C. It seems that many modules call external programs like that. 　 So, I'm going to put together the usage of the subprocess and asyncio modules as soon as possible and incorporate them into the text body. 　 －－－－－－－－－－－－－－ Supplement Kivy's KV language, I have to organize information for beginners. I thought about how to learn and how to consult with students. 　 It's the next theme. After a while, I will correct and add the text again ... 　 －－－－－－－－－－－－－－ Supplement-2 Students made a "disappointing voice" when Kivy's text input did not support the Japanese input method of Windows / Mac. But it's still in the future. 　 The display during input may be corrupted, but for the time being, I can input Japanese somehow ... Kivy is just developing. He persuaded the students that "the UI has the highest potential and will be the focus of attention in the future!" I have personal expectations, but I will be dating Kivy for a while.

Among them, I think there is no doubt that the update will greatly improve it. 　 －－－－－－－－－－－－－－ Supplement It seems that the Japanese translation of the Kivy document site is in progress. Kivy Document Site 　 Thank you. This is useful when you need a detailed reference. 　 －－－－－－－－－－－－－－ Supplement The introduction explanation of SymPy is included in the module book. Module Book (Computer algebra module) You can do things like Mathematica and Maxima. 　 You may be wondering "Why SymPy?", But the theme of our seminar was "Proposal of a user interface for an easy-to-use computer algebra system", and that's the situation. 　 SymPy is a great package, and it's a level that competes with commercial systems except for graphical features (probably). The manual also has more than 1,700 pages in PDF ... 　 I think Maxima, which is free to use as a formula calculator, or Mathematica, if you have money, is good. You can easily make 3D plots. (I personally don't recommend forcing SymPy to be a mathematical calculator as it is. I think it's a hassle ...) 　 I think SymPy will be very useful when developing apps that incorporate computer algebra functions (educational software, thinking support apps, etc.). 　 －－－－－－－－－－－－－－ Supplement About Kivy: Added explanation of basic usage of ActionBar (Kivy style menu), ScreenManager, Carousel, TabbedPanel. (Responded to requests from students) 　 Also, I added a basic explanation about the Clock module required to handle time events (timers) in Kivy. There was a student who tried to use for and while to repeat the process of starting at the timing in the GUI application. Instead, set a timer. 　 With this, I wonder if I can give guidance on making apps ... 　 I'm worried about cracking, but I'll crush it over time. Text body If you have any problems, please contact us. We will correct and upload it immediately. －－－－－－－－－－－－－－ Supplement-2 When making an app with Kivy, using the KV language makes debugging a little difficult for beginners ... 　 If you make a mistake in a Python program, the error message is easy to understand, but it is difficult to detect the mistake made in KV ... In short, the message "There is a XX error in what line of the KV language" does not appear. 　 For experts, the KV language is appreciated in terms of development efficiency, but for beginners, the KV language is likely to reduce the efficiency of studying ... 　 Until you get used to Kivy, I think it's better to write APIs in Python normally, but what do you think ... 　 －－－－－－－－－－－－－－ Supplement We asked you about the handling of Kivy's frame buffer (FBO), so we added a commentary. It seems that it is difficult to extract the pixel value with ordinary Canvas drawing. That's why we use FBO. Text body 　 －－－－－－－－－－－－－－ Supplement The introduction explanation of Pillow is included in the module book. Module Book (Image processing module) You can do things like Photoshop. 　 －－－－－－－－－－－－－－ Supplement The release date is July, but I immediately received a voice saying "I want you to teach me how to use the sound", so I added the content. (Wave, PyAudio) In addition, we have made some additions and corrections in response to consultations from students. 　 I started to make a "module book". I wrote only the part like the introduction of OpenCV module. (Image recognition module) Module Book 　 As for modules, there are too many types published, so I think I will mainly write about the ones that I found out how to use in my seminar.

Udemy related

It is quite difficult for those who have graduated (or are enrolled) in the Faculty of Humanities (Humanities) to learn programming by themselves. The Python texts that are released for free assume that those who are already familiar with other languages will learn Python in a short time. 　 If you are learning programming for the first time, you will need a detailed guide on what to do specifically. Those who are actually educated about the Python language at school and those who have a certain number of friends who are familiar with Python can naturally understand the detailed points in learning, but it is not in such an environment. I think that there are some disadvantages in learning. 　 I actually teach programming, and I strongly feel about this. Those who have mastered C ++, Java, and JavaScript to some extent can learn by themselves only with Python texts, but those who do not can get stuck early with texts alone. For such a person, I have to give a detailed explanation at the operation level in front of the PC. 　 　 Nowadays, many excellent teaching materials (books, internet sites, etc.) related to Python are sold and released, including paid and free ones, and I think that it is becoming less difficult to obtain information sources. .. However, I think that it is difficult to obtain the "detailed points of operation" mentioned above from the text medium, and for the time being, I am thinking of dealing with this with video teaching materials. 　 So far, we are delivering one video course on Udemy, and I would like to introduce it here. It is a more compact summary of the free text "Introduction to Python 3". 　 Please understand that this is a video course that is completely unnecessary for those who can learn Python only with the free text "Introduction to Python 3", other books, and information on Internet sites. 　 This video material from Udemy was created for those who have been frustrated by self-study in Python or who are learning programming for the first time in Python. (11 hours in total) 　 >>> Link to Course 　 ・ Facebook ・ Twitter

table of contents

[Table of contents of the text body]

1 Introduction --- 1 1.1 What you can do with Python --- 1 1.2 Contents of this manual --- 1 1.2.1 How to read this book --- 2 1.3 How to install and start the processing system --- 2 1.3.1 Python processing distribution (distribution form) --- 2 1.3.2 Starting Python processing system --- 2 1.3.3 Interactive mode --- 3 1.4 GUI library to be used --- 3 1.5 Detailed information about Python --- 3 2 Basics of Python --- 4 2.1 Script execution --- 4 2.1.1 Comments to be written in the program --- 5 2.1.2 Program indent --- 5 2.2 Variables and data types --- 6 2.2.1 Variable release (discard) --- 7 2.2.2 Numerical value --- 7 2.2.2.1 Maximum value, minimum value --- 10 2.2.2.2 Rounding of floating point numbers --- 11 2.2.2.3 Mathematical functions --- 11 2.2.2.4 Special values: inf, nan --- 12 2.2.2.5 Handling of floating point numbers with multiple precision --- 14 2.2.2.6 Handling of fractions --- 15 2.2.2.7 Random number generation --- 17 2.2.3 Character string --- 18 2.2.3.1 Escape sequence --- 18 2.2.3.2 raw character string (raw string) --- 19 2.2.3.3 Character string over multiple lines --- 19 2.2.3.4 Decomposition and composition of character strings --- 20 2.2.3.5 Character string replacement --- 21 2.2.3.6 Character replacement --- 22 2.2.3.7 Judgment of letters and numbers --- 22 2.2.3.8 Uppercase / lowercase conversion and judgment --- 23 2.2.3.9 Character string content inspection --- 23 2.2.3.10 Character code / character type --- 24 2.2.4 Truth value (bool type) --- 26 2.2.5 Null object: None --- 26 2.2.6 Type conversion --- 26 2.2.7 Type inspection --- 26 2.2.8 Cardinal conversion --- 27 2.2.8.1 N-ary number → decimal number --- 27 2.2.8.2 Decimal number → n-ary number --- 27 2.2.9 Bit operation --- 28 2.3 Data structure --- 30 2.3.1 List --- 30 2.3.1.1 Access to list elements --- 30 2.3.1.2 Editing the list --- 30 2.3.1.3 Realization of stack and queue by list: pop method --- 32 2.3.1.4 Inspection of list --- 33 2.3.1.5 Exception handling --- 34 2.3.1.6 Counting the number of elements --- 35 2.3.1.7 Alignment of elements (1): sort method --- 36 2.3.1.8 Sorting of elements (2): sorted function --- 37 2.3.1.9 Reversing the order of elements --- 37 2.3.1.10 Duplicate list --- 37 2.3.2 Tuple --- 38 2.3.2.1 Special tuple --- 39 2.3.3 set --- 39 2.3.3.1 Operation of set theory --- 40 　　　2.3.3.2　frozenset　---　41　 2.3.4 Dictionary type --- 41 2.3.4.1 Access to the dictionary by get method --- 41 2.3.4.2 How to retrieve the key and value columns --- 42 2.3.4.3 How to check the number of elements in a dictionary type object --- 42 2.3.4.4 How to generate a dictionary from a list or tuple --- 43 2.3.4.5 How to retrieve all elements of a dictionary as columns --- 43 2.3.5 Advanced application of subscripts (slices) --- 43 2.3.5.1 Slice object (reference) --- 44 2.3.6 Data structure conversion --- 45 2.3.7 Value allocation according to the data structure (split assignment) --- 46 2.3.7.1 Selective partial extraction of data structure --- 47 2.3.8 Data structure shuffle --- 47 2.3.9 About the speed of access to the data structure --- 47 2.4 Control structure --- 48 2.4.1 Repeat (1): for --- 48 2.4.1.1 range object --- 49 2.4.1.2 else in the for statement --- 50 2.4.1.3 Data structure generation using for (element inclusion notation) --- 50 2.4.1.4 Iterator --- 51 2.4.1.5 For statement using split assignment --- 52 2.4.1.6 zip function and zip object --- 52 2.4.1.7 Addition of index information by enumerate --- 53 2.4.2 Repeat (2): while --- 54 2.4.3 Repeated interruption and skip --- 55 2.4.4 Conditional branch --- 55 2.4.4.1 Conditional expression --- 56 2.4.4.2 Conditional judgment regarding various "empty" values --- 56 2.4.4.3 Comparison by ʻis' --- 58 2.5 Input / output --- 59 2.5.1 Standard output --- 59 2.5.1.1 Formatting of output data --- 59 2.5.1.2 Handling of standard output by sys module --- 61 2.5.2 Standard input --- 62 2.5.2.1 Handling of standard input by sys module --- 63 2.5.3 Input from file --- 64 2.5.3.1 Handling of byte strings --- 67 2.5.3.2 How to check the code system of byte string --- 68 2.5.3.3 How to read the specified number of bytes --- 68 2.5.3.4 How to read the contents of the file at once --- 68 2.5.3.5 How to read a file as an iterator --- 68 2.5.4 Output to file --- 69 2.5.5 Standard error output --- 69 2.5.6 Handling of paths (files, directories) --- 71 2.5.6.1 Operations related to the current directory --- 71 2.5.6.2 List of directory contents --- 72 2.5.6.3 Get file size --- 72 2.5.6.4 File and directory inspection --- 72 2.5.6.5 Delete files and directories --- 72 2.5.6.6 Information about running scripts --- 73 2.5.6.7 Concatenation of path expressions --- 73 2.5.6.8 Yet another way to handle paths: pathlib --- 73 2.5.7 Acquisition of command arguments --- 75 2.5.8 Be careful when processing input / output --- 76 2.6 Function definition --- 77 2.6.1 Formal parameters --- 77 2.6.1.1 Function with an indefinite number of arguments --- 77 2.6.1.2 How to write `*'in the argument when calling a function --- 78 2.6.1.3 Keyword argument --- 78 2.6.2 Variable scope (handling of variables inside and outside the function definition) --- 79 2.6.3 Deletion of defined function --- 80 2.7 Object-oriented programming --- 81 2.7.1 Class definition --- 81 2.7.1.1 Constructor --- 81 2.7.1.2 Method definition --- 81 2.7.1.3 Class variables --- 82 2.7.1.4 Attribute investigation (property investigation) --- 84 2.7.2 Investigation of class inheritance relationship --- 84 2.8 Programming according to the data structure --- 85 2.8.1 map function --- 86 2.8.1.1 Map of a function that takes multiple arguments --- 87 2.8.1.2 How to give a zip object to the map function --- 87 2.8.2 lambda and function definition --- 88 　　2.8.3　filter　---　90　 2.8.4 if ~ else as a ternary operator ... --- 90 2.8.5 Batch judgment by all, any --- 90 2.8.6 Higher-order function module: functools --- 92 　　　2.8.6.1　reduce　---　92　 2.9 Substitution formula --- 93 3 Building a GUI application with Kivy --- 94 3.1 Kivy Basics --- 94 3.1.1 Implementation of application program --- 94 3.1.2 Concept of GUI construction --- 94 3.1.2.1 Widget --- 95 3.1.2.2 Layout --- 96 3.1.2.3 Screen --- 96 3.1.3 Handling of windows --- 97 3.1.4 Disable multi-touch --- 97 3.2 Basic GUI application construction method --- 98 3.2.1 Event processing (introduction) --- 98 3.2.1.1 Event handling --- 98 3.2.2 Example of application construction --- 99 3.2.3 Event processing (method by registering callback) --- 102 3.2.4 Registering and deleting widgets --- 103 3.2.5 Handling of application start and end --- 104 3.3 How to use various widgets --- 105 3.3.1 Label: Label --- 105 3.3.1.1 Registering fonts in resources --- 107 3.3.2 Button: Button --- 108 3.3.3 Text input: TextInput --- 108 3.3.4 Checkbox: CheckBox --- 109 3.3.5 Progress Bar: ProgressBar --- 109 3.3.6 Slider: Slider --- 109 3.3.7 Switch: Switch --- 109 3.3.8 Toggle Button: ToggleButton --- 109 3.3.9 Image: Image --- 110 3.3.9.1 Sample program --- 110 3.4 Canvas Graphics --- 111 3.4.1 Graphics class --- 112 　　　3.4.1.1　Color　---　112　 　　　3.4.1.2　Line　---　112　 　　　3.4.1.3　Rectangle　---　112　 　　　3.4.1.4　Ellipse　---　113　 3.4.2 Sample program --- 113 3.4.2.1 Sine function plot --- 113 3.4.2.2 Display of various figures and images --- 113 3.4.3 Drawing to the frame buffer --- 115 3.4.3.1 Pixel value retrieval --- 116 3.4.3.2 Coordinate position obtained from the event --- 117 3.5 ScrollView --- 117 3.5.1 Widget size setting --- 118 3.6 Setting to fix the window size (prohibit resizing) --- 118 3.7 Construction of UI in Kivy language --- 119 3.7.1 Basics of Kivy language --- 119 3.7.1.1 Explanation using a sample program --- 119 3.7.1.2 Correspondence between Python programs and Kv files --- 121 3.8 Event by time --- 122 3.8.1 Time event schedule --- 122 3.9 GUI construction format --- 122 3.9.1 Screen handling: Screen and Screen Manager --- 123 　　　3.9.1.1　ScreenManager　---　123　 　　　3.9.1.2　Screen　---　123　 3.9.2 Action Bar: ActionBar --- 125 3.9.3 Tab panel: TabbedPanel --- 126 3.9.4 Swipe: Carousel --- 127 4 Matters necessary for practical application development --- 129 4.1 Date and time processing --- 129 4.1.1 Basic functions --- 129 4.1.1.1 Date and time formatting --- 130 4.1.1.2 datetime property --- 130 4.1.2 Use of time module --- 131 4.1.2.1 Time measurement --- 131 4.1.2.2 Waiting for program execution --- 132 4.2 Character string search and regular expression --- 132 4.2.1 Pattern search --- 132 4.2.1.1 Search using regular expressions --- 134 4.2.1.2 Union of search patterns --- 136 4.2.1.3 Pattern matching using regular expressions --- 137 4.2.1.4 Pattern matching at the beginning and end of the line --- 137 4.2.2 Replacement process: re.sub --- 138 4.2.2.1 Replacement process over multiple lines --- 138 4.2.2.2 Replacement process with reference to pattern matching group --- 139 4.2.3 Application to character string decomposition: re.split --- 139 4.3 Multi-thread and multi-process --- 140 4.3.1 Multi-thread --- 140 4.3.2 Multi-process --- 141 　　　4.3.2.1　ProcessPoolExecutor　---　141　 4.3.3 Comparison of execution time between multithread and multiprocess --- 142 4.4 Generator --- 143 4.4.1 Generator function --- 143 4.4.2 Generator type --- 144 4.5 Split programming by creating modules and packages --- 145 4.5.1 Module --- 145 4.5.1.1 Module as a single source file --- 145 4.5.2 Package (library configured as a directory) --- 146 4.5.2.1 Module execution --- 147 4.5.3 Investigation of the directory where the module is located --- 148 4.5.4 About \ _ \ _ init \ _ \ _. Py --- 148 4.6 Random access in the file --- 150 4.6.1 Specifying the access location of the file (seek of the file) --- 150 4.6.2 Sample program --- 150 4.7 Saving and loading data objects: pickle module --- 152 4.8 Binary data creation and deployment: struct module --- 154 4.8.1 Creation of binary data --- 154 4.8.2 Expansion of binary data --- 154 4.8.3 Byte order --- 156 4.9 How to convert binary data to text: base64 module --- 157 4.10 exec and eval --- 159 4.10.1 Namespace designation --- 159 4.10.2 eval function --- 159 4.11 collections module --- 160 4.11.1 Queue: deque --- 160 4.11.1.1 Adding and extracting elements: append, pop --- 160 4.11.1.2 Rotation of element order: rotate --- 161 4.11.2 Aggregation of elements: Counter --- 161 4.11.2.1 Extract the aggregated results in order of appearance frequency --- 162 　　4.11.3　namedtuple　---　162　 4.12 Enumeration type: enum module --- 163 4.12.1 Enum type --- 163 4.12.2 Example of how to handle constants --- 164 　　4.12.3　IntEnum　---　165　 4.12.4 Assigning a value to the Enum element by the auto function --- 165 4.13 Exception (error) handling --- 167 4.13.1 How to raise an exception --- 167 4.14 Investigation of symbols used --- 169 4.15 with syntax --- 170 4.16 Formatted display of data structure: pprint module --- 175 4.17 Acquisition of information on processing environment --- 176 4.17.1 Acquisition of Python version information --- 176 4.17.2 Use of platform module --- 176 4.17.3 Reference of environment variables --- 177 4.18 Operations on files and directories: shutil module --- 179 4.18.1 Duplicate files and directories --- 179 4.18.2 Handling of archive files (archive) and compression processing --- 180 4.19 Handling of ZIP archive: zipfile module --- 181 4.19.1 Open the ZIP archive file --- 181 4.19.2 Addition of members to the archive --- 181 4.19.3 Confirmation of the contents of the library --- 181 4.19.4 Reading archive members --- 182 4.19.5 Development of library --- 182 4.19.5.1 Access to password-protected ZIP archive --- 183 4.20 Handling of command arguments: argparse module --- 184 4.20.1 Command argument format --- 184 4.20.2 How to use --- 184 4.20.2.1 Setting optional arguments --- 185 4.20.2.2 Position argument setting --- 185 4.20.2.3 Command line analysis processing --- 185 4.20.3 Explanation according to the sample program --- 185 4.20.3.1 Help function --- 186 4.20.3.2 Specifying the command argument type --- 187 4.20.4 Subcommand implementation method --- 187 4.21 End of script (end of program) --- 189 5 TCP / IP communication --- 190 5.1 socket module --- 190 5.1.1 Preparation of socket --- 190 5.1.2 Server-side program processing --- 191 5.1.3 Client-side program processing --- 191 5.1.4 Send and receive --- 191 5.1.5 Sample program --- 191 5.2 WWW content analysis --- 193 5.2.1 requests library --- 193 5.2.1.1 Method related to request transmission --- 193 5.2.1.2 Method related to acquired content --- 194 5.2.1.3 Assess based on Session object --- 195 5.2.2 Beautiful Soup Library --- 195 5.2.2.1 Handling of HTML content in BS --- 196 6 Cooperation with external programs --- 198 6.1 How to start an external program --- 198 6.1.1 Standard input / output connection --- 198 6.1.1.1 Closing standard input of external program --- 201 6.1.2 Asynchronous input / output --- 201 6.1.3 Synchronization with external process (waiting for termination) --- 203 6.1.4 An easier way to start an external program --- 203 7 Sound input / output --- 205 7.1 Basic knowledge --- 205 7.2 WAV format file input / output: wave module --- 205 7.2.1 Opening and closing WAV format files --- 205 7.2.1.1 Various attributes of WAV format data --- 206 7.2.2 Reading from WAV format file --- 206 7.2.3 Sample program --- 206 7.2.4 Relationship between the number of quantization bits and the sampling value --- 207 7.2.5 Handling of read frame data --- 207 7.2.6 Example of outputting WAV format data (1): From list to WAV file --- 209 7.2.7 Example of outputting WAV format data (2): From NumPy array to WAV file --- 210 7.2.8 Notes on sound data size --- 211 7.3 Sound input and playback: PyAudio library --- 212 7.3.1 Sound input / output via stream --- 212 7.3.2 Playing WAV format sound files --- 213 7.3.2.1 Detection of end of sound playback --- 215 7.3.3 Input from a voice input device --- 215 A Information about Python --- 219 A.1 Python internet site --- 219 A.2 Example of Python installation work --- 219 A.2.1 PSF version installation package method --- 219 A.2.2 Method by Anaconda --- 220 A.3 Mechanism of starting Python --- 220 A.3.1 Starting PSF version Python --- 220 A.3.2 Starting Anaconda Navigator --- 221 A.3.3 Starting Anaconda Prompt --- 222 A.3.3.1 Management of Python environment by conda command --- 223 A.4 Library management by PIP --- 223 A.4.1 Solution when PIP command cannot be executed --- 224 B Information about Kivy --- 225 B.1 Example of Kivy installation work --- 225 B.2 Information for avoiding troubles when using Kivy --- 225 B.2.1 Setting of drawing API used by Kivy --- 225 B.2.2 About SDL --- 226 B.3 GUI design tool --- 226 C Tkinter: Basic GUI toolkit --- 227 C.1 Basic handling --- 227 C.1.1 Usage example --- 228 C.1.1.1 Setting whether to change the window size --- 229 C.1.2 Widget placement --- 229 C.2 Various widgets --- 231 C.2.1 Check button and radio button --- 231 C.2.1.1 Variable class --- 232 C.2.2 Entry (text box) and combo box --- 233 C.2.2.1 End of program --- 235 C.2.3 List box --- 235 C.2.4 Text (character editing area) and scroll bar --- 236 C.2.5 scale (slider) and progress barber --- 238 C.2.5.1 Callback function setting of Vaviable class --- 239 C.3 Menu construction --- 239 C.4 Canvas drawing --- 241 C.4.1 Drawing method (partial) --- 241 C.4.2 Figure management --- 244 C.5 Event handling --- 246 C.5.1 Execution of a function with a specified time --- 248 C.6 Display of multiple windows --- 249 C.7 Acquisition of information about displays and windows --- 250 C.8 Messagebox --- 251 C.8.1 Handling of application termination --- 253 D Library handling --- 254 D.1 Thing about reading of library --- 254 D.1.1 Granting an alias when reading the library --- 254 D.1.2 Reading the library to omit the prefix --- 254 D.1.2.1 Precautions when omitting the prefix (name conflict) --- 255 D.2 Introduction of various libraries --- 256 E Ingenuity to make the interactive mode easier to use --- 257 E.1 Suppression and display of warning messages --- 257 E.2 Memory usage status management --- 258 F sample program --- 259 F.1 Comparison of list / set / dictionary access speed --- 259 F.1.1 Access in the form of giving an integer index to the slice --- 259 F.1.2 Time required for membership inspection --- 260 F.2 Comparison of calculation speed with and without library use --- 263 F.3 pathlib application example --- 266 F.4 Conversion between floating point number and binary number --- 267 F.5 List of all Unicode characters --- 268

[Table of contents of library book]

1 Image input / output and processing --- 1 　　1.1　OpenCV　---　1　 1.1.1 Video input --- 2 1.1.2 User interface --- 2 1.1.2.1 Input from video file --- 3 1.1.3 Saving the frame to a file --- 3 1.1.4 Reading still images --- 4 1.1.5 Color separation and composition --- 5 1.1.6 Inspection of image similarity --- 6 1.1.6.1 Calculation of AKAZE features --- 6 1.1.6.2 Collation of feature data --- 6 1.1.6.3 Sample program --- 7 　　1.2　Pillow　---　9　 1.2.1 Loading and saving image files --- 9 1.2.1.1 Resolution when reading EPS --- 10 1.2.2 Creating a new Image object --- 10 1.2.3 Viewing images --- 11 1.2.4 Editing images --- 11 1.2.4.1 Image enlargement / reduction --- 11 1.2.4.2 Extraction of the image part --- 12 1.2.4.3 Image duplication --- 12 1.2.4.4 Paste image --- 12 1.2.4.5 Image rotation --- 12 1.2.5 Image processing --- 13 1.2.5.1 Color separation and composition --- 13 1.2.6 Drawing --- 13 1.2.7 Creating an animated GIF --- 15 1.2.8 Conversion from Image object to numerical array of pixels --- 15 2 GUI and multimedia --- 16 　　2.1　pygame　---　16　 2.1.1 Basic matters --- 16 2.1.1.1 Surface object --- 16 2.1.1.2 Application execution loop --- 16 2.1.2 Drawing function --- 18 2.1.2.1 Drawing sample program --- 21 2.1.2.2 Rotation, scaling sample program --- 22 2.1.3 Keyboard and mouse handling --- 24 2.1.4 Audio playback --- 25 2.1.4.1 Method using Sound object --- 26 2.1.4.2 Conversion from Sound object to NumPy array --- 27 2.1.5 Use of sprites --- 29 　　2.2　Eel　---　34　 2.2.1 Basic matters --- 34 2.2.2 Calling a function written in Python / JavaScript --- 36 2.2.2.1 About the return value of the function --- 37 2.3 Media data conversion: PyDub --- 38 2.3.1 Reading audio files --- 38 2.3.2 Conversion from voice data to NumPy array --- 38 2.3.3 Conversion from NumPy array to voice data --- 39 2.3.4 Saving audio files --- 39 2.3.4.1 Save as MP3 format file --- 39 2.3.4.2 Save as WAV format file --- 39 3 Science and technology --- 40 3.1 Library for numerical calculation and visualization: NumPy / matplotlib --- 40 3.1.1 Generation of array object --- 40 3.1.1.1 About the element type of the array --- 41 3.1.1.2 Array of truth values --- 41 3.1.1.3 Special values: infinity and non-number --- 41 3.1.1.4 Data string generation (sequence generation) --- 42 3.1.1.5 Generation of multidimensional array --- 43 3.1.1.6 Investigation of the shape of the array --- 43 3.1.1.7 Access to array elements --- 44 3.1.1.8 Operation when a data string is given to a slice --- 45 3.1.1.9 Access to specified rows and columns --- 45 3.1.1.10 Deformation of array shape --- 45 3.1.1.11 Row and column transposition --- 47 3.1.1.12 Row, column inversion and rotation --- 47 3.1.1.13 Type conversion --- 48 3.1.2 Array concatenation and repetition --- 48 3.1.2.1 Concatenation by append and concatenate --- 48 3.1.2.2 Connection by hstack and vstack --- 49 3.1.2.3 Repeating array by tile --- 50 3.1.3 Expansion of array dimensions --- 50 3.1.3.1 Newaxis object method --- 50 3.1.3.2 Method by expand \ _dims --- 51 3.1.4 Data extraction --- 51 3.1.4.1 Masking by truth value sequence --- 51 3.1.4.2 Extraction of elements by conditional expression --- 52 3.1.4.3 Combined conditional expressions by logical operators --- 52 3.1.4.4 Extraction and replacement of elements by where --- 52 3.1.4.5 Search for maximum value, minimum value, and its position --- 53 3.1.5 Data sorting (sorting) --- 53 3.1.5.1 Two-dimensional array alignment --- 54 3.1.5.2 How to get the index of the alignment result --- 54 3.1.6 Various processing for arrays --- 55 3.1.6.1 Elimination of duplicate elements --- 55 3.1.6.2 Aggregation of integer elements --- 55 3.1.7 Calculation for data string: 1D to 1D --- 56 3.1.8 Data visualization (basic) --- 56 3.1.8.1 Basic procedure of drawing process --- 57 3.1.8.2 Two-dimensional plot: Line graph --- 57 3.1.8.3 Creating multiple graphs --- 59 3.1.8.4 Matplotlib graph structure --- 62 3.1.8.5 Display of Japanese headings / labels --- 66 3.1.8.6 How to save the graph as an image file --- 67 3.1.9 Random number generation --- 68 3.1.9.1 Generation of uniform random numbers --- 68 3.1.9.2 Generation of integer random numbers --- 68 3.1.9.3 Generation of normal random numbers --- 68 3.1.9.4 Random number seed --- 68 3.1.9.5 RandomState object --- 69 3.1.10 Statistical processing --- 70 3.1.10.1 Total --- 70 3.1.10.2 Maximum value, minimum value --- 70 3.1.10.3 mean, variance, standard deviation --- 70 3.1.10.4 Percentage points --- 71 3.1.10.5 Section and tabulation (class and frequency survey) --- 71 3.1.10.6 Data shuffle --- 72 3.1.11 Data visualization (2) --- 73 3.1.11.1 Histogram --- 73 3.1.11.2 Scatter plot --- 73 3.1.11.3 Bar graph --- 74 3.1.11.4 Box plot --- 74 3.1.12 Calculation on data string: \ (n ) dimension to 1 dimension --- 75 3.1.13 Data visualization: 3D plot --- 76 3.1.13.1 Wireframe --- 76 3.1.13.2 Surface plot --- 77 3.1.13.3 3D scatter plot --- 78 3.1.14 Data visualization: Other --- 79 3.1.14.1 Heat map --- 79 3.1.14.2 Creating a table --- 81 3.1.15 Fast Fourier Transform (FFT) --- 83 3.1.15.1 Conversion from time domain to frequency domain: Fourier transform --- 83 3.1.15.2 Conversion from frequency domain to time domain: Fourier transform / inverse transform --- 83 3.1.15.3 Specifying the aspect ratio of the plot --- 86 3.1.15.4 Precautions when using Fourier transform --- 87 3.1.16 Complex number calculation --- 87 3.1.16.1 Square root of complex number --- 87 3.1.16.2 Complex number norm --- 87 3.1.16.3 Conjugate complex number --- 87 3.1.16.4 Complex number argument (phase) --- 88 3.1.17 Matrix calculation --- 89 3.1.17.1 Matrix sum and product --- 89 3.1.17.2 Identity matrix, zero matrix, etc. --- 89 3.1.17.3 Make all matrix elements the same value --- 89 3.1.17.4 Diagonal component, diagonal matrix --- 90 3.1.17.5 Transpose of matrix --- 91 3.1.17.6 Determinant and inverse matrix --- 91 3.1.17.7 Eigenvalues and eigenvectors --- 91 3.1.17.8 Matrix rank --- 92 3.1.17.9 Complex conjugate matrix --- 92 3.1.17.10 Hermitian conjugate matrix --- 92 3.1.17.11 Vector norm --- 93 3.1.18 I / O: Array object file I / O --- 94 3.1.18.1 Saving to a text file --- 94 3.1.18.2 Reading from a text file --- 94 3.1.18.3 I / O to binary files --- 95 3.1.18.4 Compressed storage and loading of data --- 95 3.1.19 Matrix comparison --- 96 3.1.20 Implementation of user-defined functions that process arrays --- 96 3.1.21 Example of improvement of calculation speed by applying matrix calculation --- 98 3.1.22 Handling of image data --- 99 3.1.22.1 Conversion from pixel array to image data (linkage with PIL library) --- 100 3.1.22.2 Conversion from image data to pixel array (linkage with PIL library) --- 101 3.1.22.3 Sample program: Three-color separation of images --- 101 3.1.23 Other functions --- 103 3.1.23.1 Extraction of data above / below the standard --- 103 3.1.23.2 Extraction of data in the specified range --- 104 3.2 Library for scientific calculation: SciPy --- 107 3.2.1 Signal processing tool: scipy.signal --- 107 3.2.1.1 Generation of basic waveform --- 107 3.3 Computer algebra library: SymPy --- 111 3.3.1 Precautions regarding loading of modules --- 111 3.3.2 Basic matters --- 111 3.3.2.1 Object for computer algebra --- 112 3.3.2.2 Simplification of mathematical formulas (evaluation) --- 112 3.3.2.3 Structure of expression {\ tt f (x, y, ...) (extracting head and argument sequence) --- 113 3.3.2.4 Constant --- 113 3.3.3 Basic computer algebra function --- 114 3.3.3.1 Expansion of formula --- 114 3.3.3.2 Factorization --- 114 3.3.3.3 Arrangement by specified symbols --- 114 3.3.3.4 Approximate minutes: Simplification of fractions (1) --- 115 3.3.3.5 Partial fractions --- 115 3.3.3.6 Simplification of fractions (2) --- 116 3.3.3.7 Substitution (replacement of symbols) --- 116 3.3.3.8 Various mathematical functions --- 116 3.3.3.9 Formula type --- 116 3.3.4 Analytical processing --- 117 3.3.4.1 Extreme --- 117 3.3.4.2 Derivative function --- 117 3.3.4.3 Delayed execution of differential operation --- 118 3.3.4.4 Primitive function --- 118 3.3.4.5 Delayed execution of integrate --- 118 3.3.4.6 Definite integral --- 119 3.3.4.7 Series expansion --- 119 3.3.5 Solving various equations --- 119 3.3.5.1 Solving algebraic equations --- 119 3.3.5.2 Solving differential equations --- 120 3.3.5.3 Solving the difference equation (difference equation, recurrence formula) --- 121 3.3.6 Linear algebra --- 121 3.3.6.1 Determinant --- 121 3.3.6.2 Inverse matrix --- 121 3.3.6.3 Eigenvalues, eigenvectors --- 122 3.3.7 Summation --- 122 3.3.8 Pattern matching --- 123 3.3.9 Numerical calculation --- 124 3.3.9.1 Prime factorization --- 124 3.3.9.2 Approximate value --- 124 3.3.10 Format conversion output --- 124 　　　　　　3.3.10.1　LaTeX 　---　124　 3.3.11 Graph plot --- 124 3.3.11.1 How to save the graph to an image file --- 126 4 Security-related --- 127 　　4.1　hashlib　---　127　 4.1.1 Basic usage --- 127 　　4.2　passlib　---　127　 4.2.1 Algorithms that can be used --- 127 5 Acceleration of programs / application construction --- 129 　　5.1　Cython　---　129　 5.1.1 Usage example --- 129 5.1.2 Adjustment for speeding up --- 131 　　5.2　Numba　---　132　 5.2.1 Basic usage --- 132 5.2.2 Speeding up by specifying the type --- 133 　　5.3　ctypes　---　133　 5.3.1 Example of creating a shared library in C language --- 134 5.3.2 Example of calling a function in a shared library --- 134 5.3.3 Handling of arguments and return values --- 135 5.3.3.1 Transfer of array data --- 137 　　5.4　PyInstaller　---　140　 5.4.1 Simple usage example --- 140 5.4.1.1 How to build as a single executable file --- 141 6 Dialogue work environment (JupyterLab) --- 142 6.1 Basic matters --- 142 6.1.1 Start and end --- 143 6.1.2 Display area configuration and operation method --- 143 6.1.2.1 Notebook usage example --- 144 6.1.2.2 About the kernel --- 146 6.1.3 Execution of input function in Notebook --- 146 6.2 Comment display by Markdown --- 147 6.3 Usage example --- 148 6.3.1 Formatted display of SymPy formulas by MathJax --- 148 6.3.2 Sound playback with IPython.display module --- 149 7 Others --- 151 7.1 json: Use of data exchange format JSON --- 151 7.1.1 JSON notation --- 151 7.1.2 Usage example --- 151 7.2 urllib: URL processing --- 152 7.2.1 Handling of other byte characters (`%'encoding) --- 152 7.2.1.1 Character code system specification --- 152 7.3 zenhan: Full-width ⇔ half-width conversion --- 153 7.4 jaconv: Various conversions related to Japanese characters --- 153

written by Katsunori Nakamura