7. Input and Output¶
There are several ways to present the output of a program; data can be printed in a human-readable form, or written to a file for future use. This chapter will discuss some of the possibilities.
7.1. Fancier Output Formatting¶
So far we’ve encountered two ways of writing values: expression statements and the print() function. (A third way is using the write() method of file objects; the standard output file can be referenced as sys.stdout . See the Library Reference for more information on this.)
Often you’ll want more control over the formatting of your output than simply printing space-separated values. There are several ways to format output.
To use formatted string literals , begin a string with f or F before the opening quotation mark or triple quotation mark. Inside this string, you can write a Python expression between < and >characters that can refer to variables or literal values.
The str.format() method of strings requires more manual effort. You’ll still use < and >to mark where a variable will be substituted and can provide detailed formatting directives, but you’ll also need to provide the information to be formatted.
Finally, you can do all the string handling yourself by using string slicing and concatenation operations to create any layout you can imagine. The string type has some methods that perform useful operations for padding strings to a given column width.
When you don’t need fancy output but just want a quick display of some variables for debugging purposes, you can convert any value to a string with the repr() or str() functions.
The str() function is meant to return representations of values which are fairly human-readable, while repr() is meant to generate representations which can be read by the interpreter (or will force a SyntaxError if there is no equivalent syntax). For objects which don’t have a particular representation for human consumption, str() will return the same value as repr() . Many values, such as numbers or structures like lists and dictionaries, have the same representation using either function. Strings, in particular, have two distinct representations.
The string module contains a Template class that offers yet another way to substitute values into strings, using placeholders like $x and replacing them with values from a dictionary, but offers much less control of the formatting.
7.1.1. Formatted String Literals¶
Formatted string literals (also called f-strings for short) let you include the value of Python expressions inside a string by prefixing the string with f or F and writing expressions as
An optional format specifier can follow the expression. This allows greater control over how the value is formatted. The following example rounds pi to three places after the decimal:
Passing an integer after the ‘:’ will cause that field to be a minimum number of characters wide. This is useful for making columns line up.
Other modifiers can be used to convert the value before it is formatted. ‘!a’ applies ascii() , ‘!s’ applies str() , and ‘!r’ applies repr() :
The = specifier can be used to expand an expression to the text of the expression, an equal sign, then the representation of the evaluated expression:
See self-documenting expressions for more information on the = specifier. For a reference on these format specifications, see the reference guide for the Format Specification Mini-Language .
7.1.2. The String format() Method¶
Basic usage of the str.format() method looks like this:
The brackets and characters within them (called format fields) are replaced with the objects passed into the str.format() method. A number in the brackets can be used to refer to the position of the object passed into the str.format() method.
If keyword arguments are used in the str.format() method, their values are referred to by using the name of the argument.
Positional and keyword arguments can be arbitrarily combined:
If you have a really long format string that you don’t want to split up, it would be nice if you could reference the variables to be formatted by name instead of by position. This can be done by simply passing the dict and using square brackets ‘[]’ to access the keys.
This could also be done by passing the table dictionary as keyword arguments with the ** notation.
This is particularly useful in combination with the built-in function vars() , which returns a dictionary containing all local variables.
As an example, the following lines produce a tidily aligned set of columns giving integers and their squares and cubes:
For a complete overview of string formatting with str.format() , see Format String Syntax .
7.1.3. Manual String Formatting¶
Here’s the same table of squares and cubes, formatted manually:
(Note that the one space between each column was added by the way print() works: it always adds spaces between its arguments.)
The str.rjust() method of string objects right-justifies a string in a field of a given width by padding it with spaces on the left. There are similar methods str.ljust() and str.center() . These methods do not write anything, they just return a new string. If the input string is too long, they don’t truncate it, but return it unchanged; this will mess up your column lay-out but that’s usually better than the alternative, which would be lying about a value. (If you really want truncation you can always add a slice operation, as in x.ljust(n)[:n] .)
There is another method, str.zfill() , which pads a numeric string on the left with zeros. It understands about plus and minus signs:
7.1.4. Old string formatting¶
The % operator (modulo) can also be used for string formatting. Given ‘string’ % values , instances of % in string are replaced with zero or more elements of values . This operation is commonly known as string interpolation. For example:
More information can be found in the printf-style String Formatting section.
7.2. Reading and Writing Files¶
open() returns a file object , and is most commonly used with two positional arguments and one keyword argument: open(filename, mode, encoding=None)
The first argument is a string containing the filename. The second argument is another string containing a few characters describing the way in which the file will be used. mode can be ‘r’ when the file will only be read, ‘w’ for only writing (an existing file with the same name will be erased), and ‘a’ opens the file for appending; any data written to the file is automatically added to the end. ‘r+’ opens the file for both reading and writing. The mode argument is optional; ‘r’ will be assumed if it’s omitted.
Normally, files are opened in text mode, that means, you read and write strings from and to the file, which are encoded in a specific encoding. If encoding is not specified, the default is platform dependent (see open() ). Because UTF-8 is the modern de-facto standard, encoding="utf-8" is recommended unless you know that you need to use a different encoding. Appending a ‘b’ to the mode opens the file in binary mode. Binary mode data is read and written as bytes objects. You can not specify encoding when opening file in binary mode.
In text mode, the default when reading is to convert platform-specific line endings ( \n on Unix, \r\n on Windows) to just \n . When writing in text mode, the default is to convert occurrences of \n back to platform-specific line endings. This behind-the-scenes modification to file data is fine for text files, but will corrupt binary data like that in JPEG or EXE files. Be very careful to use binary mode when reading and writing such files.
It is good practice to use the with keyword when dealing with file objects. The advantage is that the file is properly closed after its suite finishes, even if an exception is raised at some point. Using with is also much shorter than writing equivalent try — finally blocks:
If you’re not using the with keyword, then you should call f.close() to close the file and immediately free up any system resources used by it.
Calling f.write() without using the with keyword or calling f.close() might result in the arguments of f.write() not being completely written to the disk, even if the program exits successfully.
After a file object is closed, either by a with statement or by calling f.close() , attempts to use the file object will automatically fail.
7.2.1. Methods of File Objects¶
The rest of the examples in this section will assume that a file object called f has already been created.
To read a file’s contents, call f.read(size) , which reads some quantity of data and returns it as a string (in text mode) or bytes object (in binary mode). size is an optional numeric argument. When size is omitted or negative, the entire contents of the file will be read and returned; it’s your problem if the file is twice as large as your machine’s memory. Otherwise, at most size characters (in text mode) or size bytes (in binary mode) are read and returned. If the end of the file has been reached, f.read() will return an empty string ( » ).
f.readline() reads a single line from the file; a newline character ( \n ) is left at the end of the string, and is only omitted on the last line of the file if the file doesn’t end in a newline. This makes the return value unambiguous; if f.readline() returns an empty string, the end of the file has been reached, while a blank line is represented by ‘\n’ , a string containing only a single newline.
For reading lines from a file, you can loop over the file object. This is memory efficient, fast, and leads to simple code:
If you want to read all the lines of a file in a list you can also use list(f) or f.readlines() .
f.write(string) writes the contents of string to the file, returning the number of characters written.
Other types of objects need to be converted – either to a string (in text mode) or a bytes object (in binary mode) – before writing them:
f.tell() returns an integer giving the file object’s current position in the file represented as number of bytes from the beginning of the file when in binary mode and an opaque number when in text mode.
To change the file object’s position, use f.seek(offset, whence) . The position is computed from adding offset to a reference point; the reference point is selected by the whence argument. A whence value of 0 measures from the beginning of the file, 1 uses the current file position, and 2 uses the end of the file as the reference point. whence can be omitted and defaults to 0, using the beginning of the file as the reference point.
In text files (those opened without a b in the mode string), only seeks relative to the beginning of the file are allowed (the exception being seeking to the very file end with seek(0, 2) ) and the only valid offset values are those returned from the f.tell() , or zero. Any other offset value produces undefined behaviour.
File objects have some additional methods, such as isatty() and truncate() which are less frequently used; consult the Library Reference for a complete guide to file objects.
7.2.2. Saving structured data with json ¶
Strings can easily be written to and read from a file. Numbers take a bit more effort, since the read() method only returns strings, which will have to be passed to a function like int() , which takes a string like ‘123’ and returns its numeric value 123. When you want to save more complex data types like nested lists and dictionaries, parsing and serializing by hand becomes complicated.
Rather than having users constantly writing and debugging code to save complicated data types to files, Python allows you to use the popular data interchange format called JSON (JavaScript Object Notation). The standard module called json can take Python data hierarchies, and convert them to string representations; this process is called serializing. Reconstructing the data from the string representation is called deserializing. Between serializing and deserializing, the string representing the object may have been stored in a file or data, or sent over a network connection to some distant machine.
The JSON format is commonly used by modern applications to allow for data exchange. Many programmers are already familiar with it, which makes it a good choice for interoperability.
If you have an object x , you can view its JSON string representation with a simple line of code:
Another variant of the dumps() function, called dump() , simply serializes the object to a text file . So if f is a text file object opened for writing, we can do this:
To decode the object again, if f is a binary file or text file object which has been opened for reading:
JSON files must be encoded in UTF-8. Use encoding="utf-8" when opening JSON file as a text file for both of reading and writing.
This simple serialization technique can handle lists and dictionaries, but serializing arbitrary class instances in JSON requires a bit of extra effort. The reference for the json module contains an explanation of this.
pickle — the pickle module
Contrary to JSON , pickle is a protocol which allows the serialization of arbitrarily complex Python objects. As such, it is specific to Python and cannot be used to communicate with applications written in other languages. It is also insecure by default: deserializing pickle data coming from an untrusted source can execute arbitrary code, if the data was crafted by a skilled attacker.
Русские Блоги
Разница и использование read (), readline (), readlines () в Python
0. Подготовка
гипотеза a.txt Содержание выглядит следующим образом:
1. Метод чтения ([размер])
read([size]) Метод читает байты размера из текущей позиции файла, если нет параметра size , Означает чтение до конца файла, его область видимости — строковый объект
2.readline () метод
Из буквального значения видно, что этот метод считывает одну строку за раз, поэтому при чтении он занимает мало памяти, что больше подходит для больших файлов. Этот метод возвращает строковый объект.
3. Метод readlines () считывает все строки всего файла и сохраняет их в переменной списка. Каждая строка служит элементом, но чтение большого файла занимает больше памяти.
Выходной результат:
<type ‘list’>
Hello
Welcome
What is the fuck.
Модуль 4.linecache
Конечно, вы также можете использовать модуль linecache для особых нужд, например, если вы хотите вывести n-ую строку файла:
Для больших файлов эффективность в порядке.
Когда я учился читать файл, я нашел статью с простым и ясным объяснением, поэтому я скопировал ее напрямую и сохранил для дальнейшего использования. Эта статья взята из:https://www.jianshu.com/p/a672f39287c4
Интеллектуальная рекомендация
Использование Mybatis paging assistant и General Mapper
Трансфер изhttps://blog.csdn.net/zbw18297786698/article/details/53945729/ 1. Представление Mybatis paging assistant 2. Использование Mybatis paging assistant 3. В программе Java установите параметры п.
64-битная целочисленная проблема
Название Описание Введите положительное целое число n, посчитайте количество его положительных множителей, n <= 10 ^ (12), например, когда n = 30, на выходе должно быть 8. Исходный код Анатомия Лог.
Кратко поговорим о шаблонах проектирования-мост
1. Что такое режим моста Режим моста (Bridge) отделяет абстрактную часть от части реализации, так что все они могут быть изменены независимо. Схема структуры UML выглядит следующим образом: Среди них .
Простое приложение Android Android (1)
Простое приложение Android Android (1) Во-первых, кратко Помните, — я не узнал простое приложение Android. (Операция дизайна учебной программы) Пример Пакет: Ссылка: https: //pan.baidu.com/s/1leq1owku.
Формат вывода строк Python
# В основном используют способ форматирования строки для вывода, в общем, строка в формате вывода.
Difference in read(), readline() and readlines() in Python
I was looking on a web of Python the commands mentioned in title and their difference; however, I have not satisfied with a complete basic understanding of these commands.
Suppose my file has only the following content.
This is the first time I am posing a question on this site, I will appreciate if someone clarifies my doubts for learning the Python. I thank the StackOverflow for this platform.
In the commands read() , readline() and readlines() , one difference is of course reading whole file, or a single line, or specified line.
But I didn’t understand the use/necessity of bracket () in these commands. For example, what is the difference in readline() and readline(7) ? If the argument 7 exceeds the number of lines in the file, what will be output?
On the web mentioned above, it is explained what the argument in read() does; but it is not mentioned what the argument in readline() or readlines() does?
2 Answers 2
Reads and returns a string of n characters, or the entire file as a single string if n is not provided.
Returns the next line of the file with all text up to and including the newline character. If n is provided as a parameter than only n characters will be returned if the line is longer than n.
Returns a list of strings, each representing a single line of the file. If n is not provided then all lines of the file are returned. If n is provided then n characters are read but n is rounded up so that an entire line is returned.
For details, you should consult the library documentation, not the tutorial.
readline(size=-1)
Read and return one line from the stream. If size is specified, at most size bytes will be read.
The line terminator is always b’\n’ for binary files; for text files, the newline argument to open() can be used to select the line terminator(s) recognized.
readlines(hint=-1)
Read and return a list of lines from the stream. hint can be specified to control the number of lines read: no more lines will be read if the total size (in bytes/characters) of all lines so far exceeds hint .
Note that it’s already possible to iterate on file objects using for line in file: . without calling file.readlines() .
So, readline() reads an entire line. readline(7) reads at most 7 bytes of a line. readlines() reads all the lines as a list. readlines(7) returns at least 1 complete line and more lines as well( until it exceeds 7 bytes)
4 Ways to Read a Text File Line by Line in Python
Reading files is a necessary task in any programming language. Whether it’s a database file, image, or chat log, having the ability to read and write files greatly enhances what we can with Python.
Before we can create an automated audiobook reader or website, we’ll need to master the basics. After all, no one ever ran before they crawled.
To complicate matters, Python offers several solutions for reading files. We’re going to cover the most common procedures for reading files line by line in Python. Once you’ve tackled the basics of reading files in Python, you’ll be better prepared for the challenges that lie ahead.
You’ll be happy to learn that Python provides several functions for reading, writing, and creating files. These functions simplify file management by handling some of the work for us, behind the scenes.
We can use many of these Python functions to read a file line by line.
Read a File Line by Line with the readlines() Method
Our first approach to reading a file in Python will be the path of least resistance: the readlines() method. This method will open a file and split its contents into separate lines.
This method also returns a list of all the lines in the file. We can use readlines() to quickly read an entire file.
For example, let’s say we have a file containing basic information about employees at our company. We need to read this file and do something with the data.
employees.txt
Name: Marcus Gaye
Age: 25
Occupation: Web Developer
Name: Sally Rain
age: 31
Occupation: Senior Programmer
Example 1: Using readlines() to read a file
Output
readline() vs readlines()
Unlike its counterpart, the readline() method only returns a single line from a file. The realine() method will also add a trailing newline character to the end of the string.
With the readline() method, we also have the option of specifying a length for the returned line. If a size is not provided, the entire line will be read.
Consider the following text file:
wise_owl.txt
A wise old owl lived in an oak.
The more he saw the less he spoke.
The less he spoke the more he heard.
Why can’t we all be like that wise old bird?
We can use readline() to get the first line of the text document. Unlike readlines(), only a single line will be printed when we use the readline() method to read the file.
Example 2: Read a single line with the readline() method
Output
The readline() method only retrieves a single line of text. Use readline() if you need to read all the lines at once.
Output
[‘A wise old owl lived in an oak.\n’, ‘The more he saw the less he spoke.\n’, ‘The less he spoke the more he heard.\n’, “Why can’t we all be like that wise old bird?\n”]
Using a While Loop to Read a File
It’s possible to read a file using loops as well. Using the same wise_owl.txt file that we made in the previous section, we can read every line in the file using a while loop.
Example 3: Reading files with a while loop and readline()
Output
A wise old owl lived in an oak.
The more he saw the less he spoke.
The less he spoke the more he heard.
Why can’t we all be like that wise old bird?
Beware of infinite loops
A word of warning when working with while loops is in order. Be careful to add a termination case for the loop, otherwise you’ll end up looping forever. Consider the following example:
Executing this code will cause Python to fall into an infinite loop, printing “Groundhog Day” until the end of time. When writing code like this, always provide a way to exit the loop.
If you find that you’ve accidentally executed an infinite loop, you can escape it in the terminal by tapping Control+C on your keyboard.
Reading a file object in Python
It’s also possible to read a file in Python using a for loop. For example, our client has given us a list of addresses of previous customers. We need to read the data using Python.
Here’s the list of clients:
address_list.txt
Bobby Dylan
111 Longbranch Ave.
Houston, TX 77016
Sam Garfield
9805 Border Rd.
New Brunswick, NJ 08901
Penny Lane
408 2nd Lane
Lindenhurst, NY 11757
Marcus Gaye
622 Shub Farm St.
Rockledge, FL 32955
Prudence Brown
66 Ashley Ave.
Chaska, MN 55318
Whenever we open a file object, we can use a for loop to read its contents using the in keyword. With the in keyword, we can loop through the lines of the file.
Example 4: Using a for loop to read the lines in a file
Unfortunately, this solution will not work for our client. It’s very important that the data is in the form of a Python list. We’ll need to break the file into separate addresses and store them in a list before we can continue.
Example 5: Reading a file and splitting the content into a list
Reading a file with the Context Manager
File management is a delicate procedure in any programming language. Files must be handled with care to prevent their corruption. When a file is opened, care must be taken to ensure the resource is later closed.
And there is a limit to how many files can be opened at once in Python. In order to avoid these problems, Python provides us with the Context Manager.
Introducing the with block
Whenever we open a file in Python, it’s important that we remember to close it. A method like readlines() will work okay for small files, but what if we have a more complex document? Using Python with statements will ensure that files are handled safely.
- The with statement is used for safely accessing resource files.
- Python creates a new context when it encounters the with block.
- Once the block executes, Python automatically closes the file resource.
- The context has the same scope as the with statement.
Let’s practice using the with statement by reading an email we have saved as a text file.
email.txt
Dear Valued Customer,
Thank you for reaching out to us about the issue with the product that you purchased. We are eager to address any concerns you may have about our products.
We want to make sure that you are completely satisfied with your purchase. To that end, we offer a 30-day, money-back guarantee on our entire inventory. Simply return the product and we’ll happily refund the price of your purchase.
Thank you,
The ABC Company
This time a for loop is used to read the lines of the file. When we’re using the Context Manager, the file is automatically closed when it’s handler goes out of scope. When the function is finished with the file, with statement ensures the resource is handled responsibly.
Summary
We’ve covered several ways of reading files line by line in Python. We’ve learned there is a big difference between the readline() and readlines() methods, and that we can use a for loop to read the contents of a file object.
We also learned how to use the with statement to open and read files. We saw how the context manager was created to make handling files safer and easier in Python.
Several examples were provided to illustrated the various forms of file handling available in Python. Take time to explore the examples and don’t be afraid to experiment with the code if you don’t understand something.
If you’d like to learn about programming with Python, follow the links below to view more great lessons from Python for Beginners.