Что такое print в питоне
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Что такое print в питоне

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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.

5. Input and Output¶

In this section, we describe printing, which includes the use of the print function, the old-style % format specifiers and the new style <> format specifiers.

5.1. Printing to standard output (normally the screen)¶

The print function is the most commonly used command to print information to the “standard output device” which is normally the screen.

There are two modes to use print.

5.1.1. Simple print¶

The easiest way to use the print command is to list the variables to be printed, separated by comma. Here are a few examples:

Python adds a space between every object that is being printed.

Python prints a new line after every print call. To suppress that, use the end= parameter:

5.1.2. Formatted printing¶

The more sophisticated way of formatting output uses a syntax very similar to Matlab’s fprintf (and therefor also similar to C’s printf ).

The overall structure is that there is a string containing format specifiers, followed by a percentage sign and a tuple that contains the variables to be printed in place of the format specifiers.

A string can contain format identifiers (such as %f to format as a float, %d to format as an integer, and %s to format as a string):

The format specifier of type %W.Df means that a Float should be printed with a total Width of W characters and D digits behind the Decimal point. (This is identical to Matlab and C, for example.)

To print more than one object, provide multiple format specifiers and list several objects in the tuple:

Note that the conversion of a format specifier and a tuple of variables into string does not rely on the print command:

This means that we can convert objects into strings whereever we need, and we can decide to print the strings later – there is no need to couple the formatting closely to the code that does the printing.

Overview of commonly used format specifiers using the astronomical unit as an example:

Example output for AU

shorter of %e or %f

5.1.3. “str” and “__str__”¶

All objects in Python should provide a method __str__ which returns a nice string representation of the object. This method a.__str__() is called when we apply the str function to object a :

The str function is extremely convenient as it allows us to print more complicated objects, such as

The way Python prints this is that it uses the __str__ method of the list object. This will print the opening square bracket [ and then call the __str__ method of the first object, i.e. the integer 3. This will produce 3 . Then the list object’s __str__ method prints the comma , and moves on to call the __str__ method of the next element in the list (i.e. 4.2 ) to print itself. This way any composite object can be represented as a string by asking the objects it holds to convert themselves to strings.

The string method of object x is called implicitly, when we

use the “%s” format specifier to print x

pass the object x directly to the print command:

5.1.4. “repr” and “__repr__”¶

A second function, repr , should convert a given object into a string presentation so that this string can be used to re-created the object using the eval function. The repr function will generally provide a more detailed string than str . Applying repr to the object x will attempt to call x.__repr__() .

We can convert an object to its str() or repr presentation using the format specifiers %s and %r, respectively.

5.1.5. New-style string formatting¶

A new system of built-in formatting allows more flexibility for complex cases, at the cost of being a bit longer.

Basic ideas in examples:

This is a powerful and elegant way of string formatting, which is gradually being used more.

Further information

5.1.6. Changes from Python 2 to Python 3: print ¶

One (maybe the most obvious) change going from Python 2 to Python 3 is that the print command loses its special status. In Python 2, we could print “Hello World” using:

Effectively, we call the function print with the argument Hello World . All other functions in Python are called such that the argument is enclosed in parentheses, i.e.

This is the new convention required in Python 3 (and allowed for recent version of Python 2.x.)

Everything we have learned about formatting strings using the percentage operator still works the same way:

Ввод и вывод данных в Python

Для вывода данных в Python используется функция print(), а для получения пользовательского ввода — функция input().

Вывод в Python

В Python мы можем просто использовать функцию print() для вывода данных. Например:

Здесь функция print() выводит строку, заключенную в одинарные кавычки.

Синтаксис функции print():

Функция print() может иметь 5 параметров:

object — значение(я) для вывода;

sep (от «separator», необязательно) — позволяет разделить несколько объектов для вывода внутри функции print();

end (необязательно) — позволяет добавлять специальные значения, например, новая строка ‘\n’ или отступ ‘\t’ ;

file (необязательно) — позволяет указать место для вывода данных. По умолчанию используется значение sys.stdout (экран).

flush (необязательно) — логическое значение, указывающее, сбрасывается ли вывод или буферизуется. По умолчанию используется значение False .

Пример №1: Функция print() с одним параметром

Good Morning!
It is rainy today

Здесь функция print() имеет только 1 параметр — объект для вывода. Поскольку параметр end не указан, то используется значение по умолчанию ‘\n’ . Таким образом, мы получаем вывод в двух разных строках.

Пример №2: Функция print() с параметром end

Good Morning! It is rainy today

Обратите внимание, что мы добавили параметр end= ‘ ‘ в функцию print(). Следовательно, мы получаем вывод в одной строке, разделенной пробелом.

Пример №3: Функция print() с параметром sep

New Year. 2023. See you soon!

Здесь в функции print() используется сразу несколько элементов для вывода, разделенных запятой. Обратите внимание, что мы также добавили необязательный параметр sep= ‘. ‘ , который позволил вывести элементы через точку (а не через запятую).

Пример №4: Вывод переменных и литералов в Python

Функция print() также может использоваться для вывода переменных. Например:

Built-in Functions¶

The Python interpreter has a number of functions and types built into it that are always available. They are listed here in alphabetical order.

Return the absolute value of a number. The argument may be an integer, a floating point number, or an object implementing __abs__() . If the argument is a complex number, its magnitude is returned.

Return an asynchronous iterator for an asynchronous iterable . Equivalent to calling x.__aiter__() .

Note: Unlike iter() , aiter() has no 2-argument variant.

New in version 3.10.

Return True if all elements of the iterable are true (or if the iterable is empty). Equivalent to:

When awaited, return the next item from the given asynchronous iterator , or default if given and the iterator is exhausted.

This is the async variant of the next() builtin, and behaves similarly.

This calls the __anext__() method of async_iterator, returning an awaitable . Awaiting this returns the next value of the iterator. If default is given, it is returned if the iterator is exhausted, otherwise StopAsyncIteration is raised.

New in version 3.10.

Return True if any element of the iterable is true. If the iterable is empty, return False . Equivalent to:

As repr() , return a string containing a printable representation of an object, but escape the non-ASCII characters in the string returned by repr() using \x , \u , or \U escapes. This generates a string similar to that returned by repr() in Python 2.

Convert an integer number to a binary string prefixed with “0b”. The result is a valid Python expression. If x is not a Python int object, it has to define an __index__() method that returns an integer. Some examples:

If the prefix “0b” is desired or not, you can use either of the following ways.

See also format() for more information.

Return a Boolean value, i.e. one of True or False . x is converted using the standard truth testing procedure . If x is false or omitted, this returns False ; otherwise, it returns True . The bool class is a subclass of int (see Numeric Types — int, float, complex ). It cannot be subclassed further. Its only instances are False and True (see Boolean Values ).

Changed in version 3.7: x is now a positional-only parameter.

This function drops you into the debugger at the call site. Specifically, it calls sys.breakpointhook() , passing args and kws straight through. By default, sys.breakpointhook() calls pdb.set_trace() expecting no arguments. In this case, it is purely a convenience function so you don’t have to explicitly import pdb or type as much code to enter the debugger. However, sys.breakpointhook() can be set to some other function and breakpoint() will automatically call that, allowing you to drop into the debugger of choice. If sys.breakpointhook() is not accessible, this function will raise RuntimeError .

Raises an auditing event builtins.breakpoint with argument breakpointhook .

New in version 3.7.

Return a new array of bytes. The bytearray class is a mutable sequence of integers in the range 0 <= x < 256. It has most of the usual methods of mutable sequences, described in Mutable Sequence Types , as well as most methods that the bytes type has, see Bytes and Bytearray Operations .

The optional source parameter can be used to initialize the array in a few different ways:

If it is a string, you must also give the encoding (and optionally, errors) parameters; bytearray() then converts the string to bytes using str.encode() .

If it is an integer, the array will have that size and will be initialized with null bytes.

If it is an object conforming to the buffer interface , a read-only buffer of the object will be used to initialize the bytes array.

If it is an iterable, it must be an iterable of integers in the range 0 <= x < 256 , which are used as the initial contents of the array.

Without an argument, an array of size 0 is created.

class bytes ( source = b» ) class bytes ( source , encoding ) class bytes ( source , encoding , errors )

Return a new “bytes” object which is an immutable sequence of integers in the range 0 <= x < 256 . bytes is an immutable version of bytearray – it has the same non-mutating methods and the same indexing and slicing behavior.

Accordingly, constructor arguments are interpreted as for bytearray() .

Bytes objects can also be created with literals, see String and Bytes literals .

Return True if the object argument appears callable, False if not. If this returns True , it is still possible that a call fails, but if it is False , calling object will never succeed. Note that classes are callable (calling a class returns a new instance); instances are callable if their class has a __call__() method.

New in version 3.2: This function was first removed in Python 3.0 and then brought back in Python 3.2.

Return the string representing a character whose Unicode code point is the integer i. For example, chr(97) returns the string ‘a’ , while chr(8364) returns the string ‘€’ . This is the inverse of ord() .

The valid range for the argument is from 0 through 1,114,111 (0x10FFFF in base 16). ValueError will be raised if i is outside that range.

Transform a method into a class method.

A class method receives the class as an implicit first argument, just like an instance method receives the instance. To declare a class method, use this idiom:

The @classmethod form is a function decorator – see Function definitions for details.

A class method can be called either on the class (such as C.f() ) or on an instance (such as C().f() ). The instance is ignored except for its class. If a class method is called for a derived class, the derived class object is passed as the implied first argument.

Class methods are different than C++ or Java static methods. If you want those, see staticmethod() in this section. For more information on class methods, see The standard type hierarchy .

Changed in version 3.9: Class methods can now wrap other descriptors such as property() .

Changed in version 3.10: Class methods now inherit the method attributes ( __module__ , __name__ , __qualname__ , __doc__ and __annotations__ ) and have a new __wrapped__ attribute.

Changed in version 3.11: Class methods can no longer wrap other descriptors such as property() .

Compile the source into a code or AST object. Code objects can be executed by exec() or eval() . source can either be a normal string, a byte string, or an AST object. Refer to the ast module documentation for information on how to work with AST objects.

The filename argument should give the file from which the code was read; pass some recognizable value if it wasn’t read from a file ( ‘<string>’ is commonly used).

The mode argument specifies what kind of code must be compiled; it can be ‘exec’ if source consists of a sequence of statements, ‘eval’ if it consists of a single expression, or ‘single’ if it consists of a single interactive statement (in the latter case, expression statements that evaluate to something other than None will be printed).

The optional arguments flags and dont_inherit control which compiler options should be activated and which future features should be allowed. If neither is present (or both are zero) the code is compiled with the same flags that affect the code that is calling compile() . If the flags argument is given and dont_inherit is not (or is zero) then the compiler options and the future statements specified by the flags argument are used in addition to those that would be used anyway. If dont_inherit is a non-zero integer then the flags argument is it – the flags (future features and compiler options) in the surrounding code are ignored.

Compiler options and future statements are specified by bits which can be bitwise ORed together to specify multiple options. The bitfield required to specify a given future feature can be found as the compiler_flag attribute on the _Feature instance in the __future__ module. Compiler flags can be found in ast module, with PyCF_ prefix.

The argument optimize specifies the optimization level of the compiler; the default value of -1 selects the optimization level of the interpreter as given by -O options. Explicit levels are 0 (no optimization; __debug__ is true), 1 (asserts are removed, __debug__ is false) or 2 (docstrings are removed too).

This function raises SyntaxError if the compiled source is invalid, and ValueError if the source contains null bytes.

If you want to parse Python code into its AST representation, see ast.parse() .

Raises an auditing event compile with arguments source and filename . This event may also be raised by implicit compilation.

When compiling a string with multi-line code in ‘single’ or ‘eval’ mode, input must be terminated by at least one newline character. This is to facilitate detection of incomplete and complete statements in the code module.

It is possible to crash the Python interpreter with a sufficiently large/complex string when compiling to an AST object due to stack depth limitations in Python’s AST compiler.

Changed in version 3.2: Allowed use of Windows and Mac newlines. Also, input in ‘exec’ mode does not have to end in a newline anymore. Added the optimize parameter.

Changed in version 3.5: Previously, TypeError was raised when null bytes were encountered in source.

New in version 3.8: ast.PyCF_ALLOW_TOP_LEVEL_AWAIT can now be passed in flags to enable support for top-level await , async for , and async with .

Return a complex number with the value real + imag*1j or convert a string or number to a complex number. If the first parameter is a string, it will be interpreted as a complex number and the function must be called without a second parameter. The second parameter can never be a string. Each argument may be any numeric type (including complex). If imag is omitted, it defaults to zero and the constructor serves as a numeric conversion like int and float . If both arguments are omitted, returns 0j .

For a general Python object x , complex(x) delegates to x.__complex__() . If __complex__() is not defined then it falls back to __float__() . If __float__() is not defined then it falls back to __index__() .

When converting from a string, the string must not contain whitespace around the central + or — operator. For example, complex(‘1+2j’) is fine, but complex(‘1 + 2j’) raises ValueError .

Changed in version 3.6: Grouping digits with underscores as in code literals is allowed.

Changed in version 3.8: Falls back to __index__() if __complex__() and __float__() are not defined.

This is a relative of setattr() . The arguments are an object and a string. The string must be the name of one of the object’s attributes. The function deletes the named attribute, provided the object allows it. For example, delattr(x, ‘foobar’) is equivalent to del x.foobar . name need not be a Python identifier (see setattr() ).

class dict ( ** kwarg ) class dict ( mapping , ** kwarg ) class dict ( iterable , ** kwarg )

Create a new dictionary. The dict object is the dictionary class. See dict and Mapping Types — dict for documentation about this class.

For other containers see the built-in list , set , and tuple classes, as well as the collections module.

dir ( ) ¶ dir ( object )

Without arguments, return the list of names in the current local scope. With an argument, attempt to return a list of valid attributes for that object.

If the object has a method named __dir__() , this method will be called and must return the list of attributes. This allows objects that implement a custom __getattr__() or __getattribute__() function to customize the way dir() reports their attributes.

If the object does not provide __dir__() , the function tries its best to gather information from the object’s __dict__ attribute, if defined, and from its type object. The resulting list is not necessarily complete and may be inaccurate when the object has a custom __getattr__() .

The default dir() mechanism behaves differently with different types of objects, as it attempts to produce the most relevant, rather than complete, information:

If the object is a module object, the list contains the names of the module’s attributes.

If the object is a type or class object, the list contains the names of its attributes, and recursively of the attributes of its bases.

Otherwise, the list contains the object’s attributes’ names, the names of its class’s attributes, and recursively of the attributes of its class’s base classes.

The resulting list is sorted alphabetically. For example:

Because dir() is supplied primarily as a convenience for use at an interactive prompt, it tries to supply an interesting set of names more than it tries to supply a rigorously or consistently defined set of names, and its detailed behavior may change across releases. For example, metaclass attributes are not in the result list when the argument is a class.

Take two (non-complex) numbers as arguments and return a pair of numbers consisting of their quotient and remainder when using integer division. With mixed operand types, the rules for binary arithmetic operators apply. For integers, the result is the same as (a // b, a % b) . For floating point numbers the result is (q, a % b) , where q is usually math.floor(a / b) but may be 1 less than that. In any case q * b + a % b is very close to a, if a % b is non-zero it has the same sign as b, and 0 <= abs(a % b) < abs(b) .

enumerate ( iterable , start = 0 ) ¶

Return an enumerate object. iterable must be a sequence, an iterator , or some other object which supports iteration. The __next__() method of the iterator returned by enumerate() returns a tuple containing a count (from start which defaults to 0) and the values obtained from iterating over iterable.

The arguments are a string and optional globals and locals. If provided, globals must be a dictionary. If provided, locals can be any mapping object.

The expression argument is parsed and evaluated as a Python expression (technically speaking, a condition list) using the globals and locals dictionaries as global and local namespace. If the globals dictionary is present and does not contain a value for the key __builtins__ , a reference to the dictionary of the built-in module builtins is inserted under that key before expression is parsed. That way you can control what builtins are available to the executed code by inserting your own __builtins__ dictionary into globals before passing it to eval() . If the locals dictionary is omitted it defaults to the globals dictionary. If both dictionaries are omitted, the expression is executed with the globals and locals in the environment where eval() is called. Note, eval() does not have access to the nested scopes (non-locals) in the enclosing environment.

The return value is the result of the evaluated expression. Syntax errors are reported as exceptions. Example:

This function can also be used to execute arbitrary code objects (such as those created by compile() ). In this case, pass a code object instead of a string. If the code object has been compiled with ‘exec’ as the mode argument, eval() ‘s return value will be None .

Hints: dynamic execution of statements is supported by the exec() function. The globals() and locals() functions return the current global and local dictionary, respectively, which may be useful to pass around for use by eval() or exec() .

If the given source is a string, then leading and trailing spaces and tabs are stripped.

See ast.literal_eval() for a function that can safely evaluate strings with expressions containing only literals.

Raises an auditing event exec with the code object as the argument. Code compilation events may also be raised.

exec ( object , globals = None , locals = None , / , * , closure = None ) ¶

This function supports dynamic execution of Python code. object must be either a string or a code object. If it is a string, the string is parsed as a suite of Python statements which is then executed (unless a syntax error occurs). 1 If it is a code object, it is simply executed. In all cases, the code that’s executed is expected to be valid as file input (see the section File input in the Reference Manual). Be aware that the nonlocal , yield , and return statements may not be used outside of function definitions even within the context of code passed to the exec() function. The return value is None .

In all cases, if the optional parts are omitted, the code is executed in the current scope. If only globals is provided, it must be a dictionary (and not a subclass of dictionary), which will be used for both the global and the local variables. If globals and locals are given, they are used for the global and local variables, respectively. If provided, locals can be any mapping object. Remember that at the module level, globals and locals are the same dictionary. If exec gets two separate objects as globals and locals, the code will be executed as if it were embedded in a class definition.

If the globals dictionary does not contain a value for the key __builtins__ , a reference to the dictionary of the built-in module builtins is inserted under that key. That way you can control what builtins are available to the executed code by inserting your own __builtins__ dictionary into globals before passing it to exec() .

The closure argument specifies a closure–a tuple of cellvars. It’s only valid when the object is a code object containing free variables. The length of the tuple must exactly match the number of free variables referenced by the code object.

Raises an auditing event exec with the code object as the argument. Code compilation events may also be raised.

The built-in functions globals() and locals() return the current global and local dictionary, respectively, which may be useful to pass around for use as the second and third argument to exec() .

The default locals act as described for function locals() below: modifications to the default locals dictionary should not be attempted. Pass an explicit locals dictionary if you need to see effects of the code on locals after function exec() returns.

Changed in version 3.11: Added the closure parameter.

Construct an iterator from those elements of iterable for which function is true. iterable may be either a sequence, a container which supports iteration, or an iterator. If function is None , the identity function is assumed, that is, all elements of iterable that are false are removed.

Note that filter(function, iterable) is equivalent to the generator expression (item for item in iterable if function(item)) if function is not None and (item for item in iterable if item) if function is None .

See itertools.filterfalse() for the complementary function that returns elements of iterable for which function is false.

Return a floating point number constructed from a number or string x.

If the argument is a string, it should contain a decimal number, optionally preceded by a sign, and optionally embedded in whitespace. The optional sign may be ‘+’ or ‘-‘ ; a ‘+’ sign has no effect on the value produced. The argument may also be a string representing a NaN (not-a-number), or positive or negative infinity. More precisely, the input must conform to the floatvalue production rule in the following grammar, after leading and trailing whitespace characters are removed:

Here digit is a Unicode decimal digit (character in the Unicode general category Nd ). Case is not significant, so, for example, “inf”, “Inf”, “INFINITY”, and “iNfINity” are all acceptable spellings for positive infinity.

Otherwise, if the argument is an integer or a floating point number, a floating point number with the same value (within Python’s floating point precision) is returned. If the argument is outside the range of a Python float, an OverflowError will be raised.

For a general Python object x , float(x) delegates to x.__float__() . If __float__() is not defined then it falls back to __index__() .

If no argument is given, 0.0 is returned.

Changed in version 3.6: Grouping digits with underscores as in code literals is allowed.

Changed in version 3.7: x is now a positional-only parameter.

Changed in version 3.8: Falls back to __index__() if __float__() is not defined.

Convert a value to a “formatted” representation, as controlled by format_spec. The interpretation of format_spec will depend on the type of the value argument; however, there is a standard formatting syntax that is used by most built-in types: Format Specification Mini-Language .

The default format_spec is an empty string which usually gives the same effect as calling str(value) .

A call to format(value, format_spec) is translated to type(value).__format__(value, format_spec) which bypasses the instance dictionary when searching for the value’s __format__() method. A TypeError exception is raised if the method search reaches object and the format_spec is non-empty, or if either the format_spec or the return value are not strings.

Changed in version 3.4: object().__format__(format_spec) raises TypeError if format_spec is not an empty string.

Return a new frozenset object, optionally with elements taken from iterable. frozenset is a built-in class. See frozenset and Set Types — set, frozenset for documentation about this class.

For other containers see the built-in set , list , tuple , and dict classes, as well as the collections module.

getattr ( object , name ) ¶ getattr ( object , name , default )


Return the value of the named attribute of object. name must be a string. If the string is the name of one of the object’s attributes, the result is the value of that attribute. For example, getattr(x, ‘foobar’) is equivalent to x.foobar . If the named attribute does not exist, default is returned if provided, otherwise AttributeError is raised. name need not be a Python identifier (see setattr() ).

Since private name mangling happens at compilation time, one must manually mangle a private attribute’s (attributes with two leading underscores) name in order to retrieve it with getattr() .

Return the dictionary implementing the current module namespace. For code within functions, this is set when the function is defined and remains the same regardless of where the function is called.

The arguments are an object and a string. The result is True if the string is the name of one of the object’s attributes, False if not. (This is implemented by calling getattr(object, name) and seeing whether it raises an AttributeError or not.)

Return the hash value of the object (if it has one). Hash values are integers. They are used to quickly compare dictionary keys during a dictionary lookup. Numeric values that compare equal have the same hash value (even if they are of different types, as is the case for 1 and 1.0).

For objects with custom __hash__() methods, note that hash() truncates the return value based on the bit width of the host machine. See __hash__() for details.

Invoke the built-in help system. (This function is intended for interactive use.) If no argument is given, the interactive help system starts on the interpreter console. If the argument is a string, then the string is looked up as the name of a module, function, class, method, keyword, or documentation topic, and a help page is printed on the console. If the argument is any other kind of object, a help page on the object is generated.

Note that if a slash(/) appears in the parameter list of a function when invoking help() , it means that the parameters prior to the slash are positional-only. For more info, see the FAQ entry on positional-only parameters .

This function is added to the built-in namespace by the site module.

Changed in version 3.4: Changes to pydoc and inspect mean that the reported signatures for callables are now more comprehensive and consistent.

Convert an integer number to a lowercase hexadecimal string prefixed with “0x”. If x is not a Python int object, it has to define an __index__() method that returns an integer. Some examples:

If you want to convert an integer number to an uppercase or lower hexadecimal string with prefix or not, you can use either of the following ways:

See also format() for more information.

See also int() for converting a hexadecimal string to an integer using a base of 16.

To obtain a hexadecimal string representation for a float, use the float.hex() method.

Return the “identity” of an object. This is an integer which is guaranteed to be unique and constant for this object during its lifetime. Two objects with non-overlapping lifetimes may have the same id() value.

CPython implementation detail: This is the address of the object in memory.

Raises an auditing event builtins.id with argument id .

input ( ) ¶ input ( prompt )

If the prompt argument is present, it is written to standard output without a trailing newline. The function then reads a line from input, converts it to a string (stripping a trailing newline), and returns that. When EOF is read, EOFError is raised. Example:

If the readline module was loaded, then input() will use it to provide elaborate line editing and history features.

Raises an auditing event builtins.input with argument prompt before reading input

Raises an auditing event builtins.input/result with the result after successfully reading input.

Return an integer object constructed from a number or string x, or return 0 if no arguments are given. If x defines __int__() , int(x) returns x.__int__() . If x defines __index__() , it returns x.__index__() . If x defines __trunc__() , it returns x.__trunc__() . For floating point numbers, this truncates towards zero.

If x is not a number or if base is given, then x must be a string, bytes , or bytearray instance representing an integer in radix base. Optionally, the string can be preceded by + or — (with no space in between), have leading zeros, be surrounded by whitespace, and have single underscores interspersed between digits.

A base-n integer string contains digits, each representing a value from 0 to n-1. The values 0–9 can be represented by any Unicode decimal digit. The values 10–35 can be represented by a to z (or A to Z ). The default base is 10. The allowed bases are 0 and 2–36. Base-2, -8, and -16 strings can be optionally prefixed with 0b / 0B , 0o / 0O , or 0x / 0X , as with integer literals in code. For base 0, the string is interpreted in a similar way to an integer literal in code , in that the actual base is 2, 8, 10, or 16 as determined by the prefix. Base 0 also disallows leading zeros: int(‘010’, 0) is not legal, while int(‘010’) and int(‘010’, 8) are.

Changed in version 3.4: If base is not an instance of int and the base object has a base.__index__ method, that method is called to obtain an integer for the base. Previous versions used base.__int__ instead of base.__index__ .

Changed in version 3.6: Grouping digits with underscores as in code literals is allowed.

Changed in version 3.7: x is now a positional-only parameter.

Changed in version 3.8: Falls back to __index__() if __int__() is not defined.

Changed in version 3.11: The delegation to __trunc__() is deprecated.

Changed in version 3.11: int string inputs and string representations can be limited to help avoid denial of service attacks. A ValueError is raised when the limit is exceeded while converting a string x to an int or when converting an int into a string would exceed the limit. See the integer string conversion length limitation documentation.

Return True if the object argument is an instance of the classinfo argument, or of a (direct, indirect, or virtual ) subclass thereof. If object is not an object of the given type, the function always returns False . If classinfo is a tuple of type objects (or recursively, other such tuples) or a Union Type of multiple types, return True if object is an instance of any of the types. If classinfo is not a type or tuple of types and such tuples, a TypeError exception is raised. TypeError may not be raised for an invalid type if an earlier check succeeds.

Changed in version 3.10: classinfo can be a Union Type .

Return True if class is a subclass (direct, indirect, or virtual ) of classinfo. A class is considered a subclass of itself. classinfo may be a tuple of class objects (or recursively, other such tuples) or a Union Type , in which case return True if class is a subclass of any entry in classinfo. In any other case, a TypeError exception is raised.

Changed in version 3.10: classinfo can be a Union Type .

Return an iterator object. The first argument is interpreted very differently depending on the presence of the second argument. Without a second argument, object must be a collection object which supports the iterable protocol (the __iter__() method), or it must support the sequence protocol (the __getitem__() method with integer arguments starting at 0 ). If it does not support either of those protocols, TypeError is raised. If the second argument, sentinel, is given, then object must be a callable object. The iterator created in this case will call object with no arguments for each call to its __next__() method; if the value returned is equal to sentinel, StopIteration will be raised, otherwise the value will be returned.

One useful application of the second form of iter() is to build a block-reader. For example, reading fixed-width blocks from a binary database file until the end of file is reached:

Return the length (the number of items) of an object. The argument may be a sequence (such as a string, bytes, tuple, list, or range) or a collection (such as a dictionary, set, or frozen set).

CPython implementation detail: len raises OverflowError on lengths larger than sys.maxsize , such as range(2 ** 100) .

Rather than being a function, list is actually a mutable sequence type, as documented in Lists and Sequence Types — list, tuple, range .

Update and return a dictionary representing the current local symbol table. Free variables are returned by locals() when it is called in function blocks, but not in class blocks. Note that at the module level, locals() and globals() are the same dictionary.

The contents of this dictionary should not be modified; changes may not affect the values of local and free variables used by the interpreter.

Return an iterator that applies function to every item of iterable, yielding the results. If additional iterables arguments are passed, function must take that many arguments and is applied to the items from all iterables in parallel. With multiple iterables, the iterator stops when the shortest iterable is exhausted. For cases where the function inputs are already arranged into argument tuples, see itertools.starmap() .

max ( iterable , * , key = None ) ¶ max ( iterable , * , default , key = None ) max ( arg1 , arg2 , * args , key = None )

Return the largest item in an iterable or the largest of two or more arguments.

If one positional argument is provided, it should be an iterable . The largest item in the iterable is returned. If two or more positional arguments are provided, the largest of the positional arguments is returned.

There are two optional keyword-only arguments. The key argument specifies a one-argument ordering function like that used for list.sort() . The default argument specifies an object to return if the provided iterable is empty. If the iterable is empty and default is not provided, a ValueError is raised.

If multiple items are maximal, the function returns the first one encountered. This is consistent with other sort-stability preserving tools such as sorted(iterable, key=keyfunc, reverse=True)[0] and heapq.nlargest(1, iterable, key=keyfunc) .

New in version 3.4: The default keyword-only argument.

Changed in version 3.8: The key can be None .

Return a “memory view” object created from the given argument. See Memory Views for more information.

min ( iterable , * , key = None ) ¶ min ( iterable , * , default , key = None ) min ( arg1 , arg2 , * args , key = None )

Return the smallest item in an iterable or the smallest of two or more arguments.

If one positional argument is provided, it should be an iterable . The smallest item in the iterable is returned. If two or more positional arguments are provided, the smallest of the positional arguments is returned.

There are two optional keyword-only arguments. The key argument specifies a one-argument ordering function like that used for list.sort() . The default argument specifies an object to return if the provided iterable is empty. If the iterable is empty and default is not provided, a ValueError is raised.

If multiple items are minimal, the function returns the first one encountered. This is consistent with other sort-stability preserving tools such as sorted(iterable, key=keyfunc)[0] and heapq.nsmallest(1, iterable, key=keyfunc) .

New in version 3.4: The default keyword-only argument.

Changed in version 3.8: The key can be None .

Retrieve the next item from the iterator by calling its __next__() method. If default is given, it is returned if the iterator is exhausted, otherwise StopIteration is raised.

Return a new featureless object. object is a base for all classes. It has methods that are common to all instances of Python classes. This function does not accept any arguments.

object does not have a __dict__ , so you can’t assign arbitrary attributes to an instance of the object class.

Convert an integer number to an octal string prefixed with “0o”. The result is a valid Python expression. If x is not a Python int object, it has to define an __index__() method that returns an integer. For example:

If you want to convert an integer number to an octal string either with the prefix “0o” or not, you can use either of the following ways.

See also format() for more information.

Open file and return a corresponding file object . If the file cannot be opened, an OSError is raised. See Reading and Writing Files for more examples of how to use this function.

file is a path-like object giving the pathname (absolute or relative to the current working directory) of the file to be opened or an integer file descriptor of the file to be wrapped. (If a file descriptor is given, it is closed when the returned I/O object is closed unless closefd is set to False .)

mode is an optional string that specifies the mode in which the file is opened. It defaults to ‘r’ which means open for reading in text mode. Other common values are ‘w’ for writing (truncating the file if it already exists), ‘x’ for exclusive creation, and ‘a’ for appending (which on some Unix systems, means that all writes append to the end of the file regardless of the current seek position). In text mode, if encoding is not specified the encoding used is platform-dependent: locale.getencoding() is called to get the current locale encoding. (For reading and writing raw bytes use binary mode and leave encoding unspecified.) The available modes are:

open for reading (default)

open for writing, truncating the file first

open for exclusive creation, failing if the file already exists

open for writing, appending to the end of file if it exists

text mode (default)

open for updating (reading and writing)

The default mode is ‘r’ (open for reading text, a synonym of ‘rt’ ). Modes ‘w+’ and ‘w+b’ open and truncate the file. Modes ‘r+’ and ‘r+b’ open the file with no truncation.

As mentioned in the Overview , Python distinguishes between binary and text I/O. Files opened in binary mode (including ‘b’ in the mode argument) return contents as bytes objects without any decoding. In text mode (the default, or when ‘t’ is included in the mode argument), the contents of the file are returned as str , the bytes having been first decoded using a platform-dependent encoding or using the specified encoding if given.

Python doesn’t depend on the underlying operating system’s notion of text files; all the processing is done by Python itself, and is therefore platform-independent.

buffering is an optional integer used to set the buffering policy. Pass 0 to switch buffering off (only allowed in binary mode), 1 to select line buffering (only usable in text mode), and an integer > 1 to indicate the size in bytes of a fixed-size chunk buffer. Note that specifying a buffer size this way applies for binary buffered I/O, but TextIOWrapper (i.e., files opened with mode=’r+’ ) would have another buffering. To disable buffering in TextIOWrapper , consider using the write_through flag for io.TextIOWrapper.reconfigure() . When no buffering argument is given, the default buffering policy works as follows:

Binary files are buffered in fixed-size chunks; the size of the buffer is chosen using a heuristic trying to determine the underlying device’s “block size” and falling back on io.DEFAULT_BUFFER_SIZE . On many systems, the buffer will typically be 4096 or 8192 bytes long.

“Interactive” text files (files for which isatty() returns True ) use line buffering. Other text files use the policy described above for binary files.

encoding is the name of the encoding used to decode or encode the file. This should only be used in text mode. The default encoding is platform dependent (whatever locale.getencoding() returns), but any text encoding supported by Python can be used. See the codecs module for the list of supported encodings.

errors is an optional string that specifies how encoding and decoding errors are to be handled—this cannot be used in binary mode. A variety of standard error handlers are available (listed under Error Handlers ), though any error handling name that has been registered with codecs.register_error() is also valid. The standard names include:

‘strict’ to raise a ValueError exception if there is an encoding error. The default value of None has the same effect.

‘ignore’ ignores errors. Note that ignoring encoding errors can lead to data loss.

‘replace’ causes a replacement marker (such as ‘?’ ) to be inserted where there is malformed data.

‘surrogateescape’ will represent any incorrect bytes as low surrogate code units ranging from U+DC80 to U+DCFF. These surrogate code units will then be turned back into the same bytes when the surrogateescape error handler is used when writing data. This is useful for processing files in an unknown encoding.

‘xmlcharrefreplace’ is only supported when writing to a file. Characters not supported by the encoding are replaced with the appropriate XML character reference &#nnn; .

‘backslashreplace’ replaces malformed data by Python’s backslashed escape sequences.

‘namereplace’ (also only supported when writing) replaces unsupported characters with \N <. >escape sequences.

newline determines how to parse newline characters from the stream. It can be None , » , ‘\n’ , ‘\r’ , and ‘\r\n’ . It works as follows:

When reading input from the stream, if newline is None , universal newlines mode is enabled. Lines in the input can end in ‘\n’ , ‘\r’ , or ‘\r\n’ , and these are translated into ‘\n’ before being returned to the caller. If it is » , universal newlines mode is enabled, but line endings are returned to the caller untranslated. If it has any of the other legal values, input lines are only terminated by the given string, and the line ending is returned to the caller untranslated.

When writing output to the stream, if newline is None , any ‘\n’ characters written are translated to the system default line separator, os.linesep . If newline is » or ‘\n’ , no translation takes place. If newline is any of the other legal values, any ‘\n’ characters written are translated to the given string.

If closefd is False and a file descriptor rather than a filename was given, the underlying file descriptor will be kept open when the file is closed. If a filename is given closefd must be True (the default); otherwise, an error will be raised.

A custom opener can be used by passing a callable as opener. The underlying file descriptor for the file object is then obtained by calling opener with (file, flags). opener must return an open file descriptor (passing os.open as opener results in functionality similar to passing None ).

The newly created file is non-inheritable .

The following example uses the dir_fd parameter of the os.open() function to open a file relative to a given directory:

The type of file object returned by the open() function depends on the mode. When open() is used to open a file in a text mode ( ‘w’ , ‘r’ , ‘wt’ , ‘rt’ , etc.), it returns a subclass of io.TextIOBase (specifically io.TextIOWrapper ). When used to open a file in a binary mode with buffering, the returned class is a subclass of io.BufferedIOBase . The exact class varies: in read binary mode, it returns an io.BufferedReader ; in write binary and append binary modes, it returns an io.BufferedWriter , and in read/write mode, it returns an io.BufferedRandom . When buffering is disabled, the raw stream, a subclass of io.RawIOBase , io.FileIO , is returned.

See also the file handling modules, such as fileinput , io (where open() is declared), os , os.path , tempfile , and shutil .

Raises an auditing event open with arguments file , mode , flags .

The mode and flags arguments may have been modified or inferred from the original call.

Changed in version 3.3:

The opener parameter was added.

The ‘x’ mode was added.

IOError used to be raised, it is now an alias of OSError .

FileExistsError is now raised if the file opened in exclusive creation mode ( ‘x’ ) already exists.

Changed in version 3.4:

The file is now non-inheritable.

Changed in version 3.5:

If the system call is interrupted and the signal handler does not raise an exception, the function now retries the system call instead of raising an InterruptedError exception (see PEP 475 for the rationale).

The ‘namereplace’ error handler was added.

Changed in version 3.6:

Support added to accept objects implementing os.PathLike .

On Windows, opening a console buffer may return a subclass of io.RawIOBase other than io.FileIO .

Changed in version 3.11: The ‘U’ mode has been removed.

Given a string representing one Unicode character, return an integer representing the Unicode code point of that character. For example, ord(‘a’) returns the integer 97 and ord(‘€’) (Euro sign) returns 8364 . This is the inverse of chr() .

Return base to the power exp; if mod is present, return base to the power exp, modulo mod (computed more efficiently than pow(base, exp) % mod ). The two-argument form pow(base, exp) is equivalent to using the power operator: base**exp .

The arguments must have numeric types. With mixed operand types, the coercion rules for binary arithmetic operators apply. For int operands, the result has the same type as the operands (after coercion) unless the second argument is negative; in that case, all arguments are converted to float and a float result is delivered. For example, pow(10, 2) returns 100 , but pow(10, -2) returns 0.01 . For a negative base of type int or float and a non-integral exponent, a complex result is delivered. For example, pow(-9, 0.5) returns a value close to 3j .

For int operands base and exp, if mod is present, mod must also be of integer type and mod must be nonzero. If mod is present and exp is negative, base must be relatively prime to mod. In that case, pow(inv_base, -exp, mod) is returned, where inv_base is an inverse to base modulo mod.

Here’s an example of computing an inverse for 38 modulo 97 :

Changed in version 3.8: For int operands, the three-argument form of pow now allows the second argument to be negative, permitting computation of modular inverses.

Changed in version 3.8: Allow keyword arguments. Formerly, only positional arguments were supported.

Print objects to the text stream file, separated by sep and followed by end. sep, end, file, and flush, if present, must be given as keyword arguments.

All non-keyword arguments are converted to strings like str() does and written to the stream, separated by sep and followed by end. Both sep and end must be strings; they can also be None , which means to use the default values. If no objects are given, print() will just write end.

The file argument must be an object with a write(string) method; if it is not present or None , sys.stdout will be used. Since printed arguments are converted to text strings, print() cannot be used with binary mode file objects. For these, use file.write(. ) instead.

Whether the output is buffered is usually determined by file, but if the flush keyword argument is true, the stream is forcibly flushed.

Changed in version 3.3: Added the flush keyword argument.

Return a property attribute.

fget is a function for getting an attribute value. fset is a function for setting an attribute value. fdel is a function for deleting an attribute value. And doc creates a docstring for the attribute.

A typical use is to define a managed attribute x :

If c is an instance of C, c.x will invoke the getter, c.x = value will invoke the setter, and del c.x the deleter.

If given, doc will be the docstring of the property attribute. Otherwise, the property will copy fget’s docstring (if it exists). This makes it possible to create read-only properties easily using property() as a decorator :

The @property decorator turns the voltage() method into a “getter” for a read-only attribute with the same name, and it sets the docstring for voltage to “Get the current voltage.”

A property object has getter , setter , and deleter methods usable as decorators that create a copy of the property with the corresponding accessor function set to the decorated function. This is best explained with an example:

This code is exactly equivalent to the first example. Be sure to give the additional functions the same name as the original property ( x in this case.)

The returned property object also has the attributes fget , fset , and fdel corresponding to the constructor arguments.

Changed in version 3.5: The docstrings of property objects are now writeable.

Rather than being a function, range is actually an immutable sequence type, as documented in Ranges and Sequence Types — list, tuple, range .

Return a string containing a printable representation of an object. For many types, this function makes an attempt to return a string that would yield an object with the same value when passed to eval() ; otherwise, the representation is a string enclosed in angle brackets that contains the name of the type of the object together with additional information often including the name and address of the object. A class can control what this function returns for its instances by defining a __repr__() method. If sys.displayhook() is not accessible, this function will raise RuntimeError .

Return a reverse iterator . seq must be an object which has a __reversed__() method or supports the sequence protocol (the __len__() method and the __getitem__() method with integer arguments starting at 0 ).

round ( number , ndigits = None ) ¶

Return number rounded to ndigits precision after the decimal point. If ndigits is omitted or is None , it returns the nearest integer to its input.

For the built-in types supporting round() , values are rounded to the closest multiple of 10 to the power minus ndigits; if two multiples are equally close, rounding is done toward the even choice (so, for example, both round(0.5) and round(-0.5) are 0 , and round(1.5) is 2 ). Any integer value is valid for ndigits (positive, zero, or negative). The return value is an integer if ndigits is omitted or None . Otherwise, the return value has the same type as number.

For a general Python object number , round delegates to number.__round__ .

The behavior of round() for floats can be surprising: for example, round(2.675, 2) gives 2.67 instead of the expected 2.68 . This is not a bug: it’s a result of the fact that most decimal fractions can’t be represented exactly as a float. See Floating Point Arithmetic: Issues and Limitations for more information.

Return a new set object, optionally with elements taken from iterable. set is a built-in class. See set and Set Types — set, frozenset for documentation about this class.

For other containers see the built-in frozenset , list , tuple , and dict classes, as well as the collections module.

This is the counterpart of getattr() . The arguments are an object, a string, and an arbitrary value. The string may name an existing attribute or a new attribute. The function assigns the value to the attribute, provided the object allows it. For example, setattr(x, ‘foobar’, 123) is equivalent to x.foobar = 123 .

name need not be a Python identifier as defined in Identifiers and keywords unless the object chooses to enforce that, for example in a custom __getattribute__() or via __slots__ . An attribute whose name is not an identifier will not be accessible using the dot notation, but is accessible through getattr() etc..

Since private name mangling happens at compilation time, one must manually mangle a private attribute’s (attributes with two leading underscores) name in order to set it with setattr() .

Return a slice object representing the set of indices specified by range(start, stop, step) . The start and step arguments default to None . Slice objects have read-only data attributes start , stop , and step which merely return the argument values (or their default). They have no other explicit functionality; however, they are used by NumPy and other third-party packages. Slice objects are also generated when extended indexing syntax is used. For example: a[start:stop:step] or a[start:stop, i] . See itertools.islice() for an alternate version that returns an iterator.

Return a new sorted list from the items in iterable.

Has two optional arguments which must be specified as keyword arguments.

key specifies a function of one argument that is used to extract a comparison key from each element in iterable (for example, key=str.lower ). The default value is None (compare the elements directly).

reverse is a boolean value. If set to True , then the list elements are sorted as if each comparison were reversed.

Use functools.cmp_to_key() to convert an old-style cmp function to a key function.

The built-in sorted() function is guaranteed to be stable. A sort is stable if it guarantees not to change the relative order of elements that compare equal — this is helpful for sorting in multiple passes (for example, sort by department, then by salary grade).

The sort algorithm uses only < comparisons between items. While defining an __lt__() method will suffice for sorting, PEP 8 recommends that all six rich comparisons be implemented. This will help avoid bugs when using the same data with other ordering tools such as max() that rely on a different underlying method. Implementing all six comparisons also helps avoid confusion for mixed type comparisons which can call reflected the __gt__() method.

For sorting examples and a brief sorting tutorial, see Sorting HOW TO .

Transform a method into a static method.

A static method does not receive an implicit first argument. To declare a static method, use this idiom:

The @staticmethod form is a function decorator – see Function definitions for details.

A static method can be called either on the class (such as C.f() ) or on an instance (such as C().f() ). Moreover, they can be called as regular functions (such as f() ).

Static methods in Python are similar to those found in Java or C++. Also, see classmethod() for a variant that is useful for creating alternate class constructors.

Like all decorators, it is also possible to call staticmethod as a regular function and do something with its result. This is needed in some cases where you need a reference to a function from a class body and you want to avoid the automatic transformation to instance method. For these cases, use this idiom:

For more information on static methods, see The standard type hierarchy .

Changed in version 3.10: Static methods now inherit the method attributes ( __module__ , __name__ , __qualname__ , __doc__ and __annotations__ ), have a new __wrapped__ attribute, and are now callable as regular functions.

Return a str version of object. See str() for details.

str is the built-in string class . For general information about strings, see Text Sequence Type — str .

Sums start and the items of an iterable from left to right and returns the total. The iterable’s items are normally numbers, and the start value is not allowed to be a string.

For some use cases, there are good alternatives to sum() . The preferred, fast way to concatenate a sequence of strings is by calling ».join(sequence) . To add floating point values with extended precision, see math.fsum() . To concatenate a series of iterables, consider using itertools.chain() .

Changed in version 3.8: The start parameter can be specified as a keyword argument.

Return a proxy object that delegates method calls to a parent or sibling class of type. This is useful for accessing inherited methods that have been overridden in a class.

The object_or_type determines the method resolution order to be searched. The search starts from the class right after the type.

For example, if __mro__ of object_or_type is D -> B -> C -> A -> object and the value of type is B , then super() searches C -> A -> object .

The __mro__ attribute of the object_or_type lists the method resolution search order used by both getattr() and super() . The attribute is dynamic and can change whenever the inheritance hierarchy is updated.

If the second argument is omitted, the super object returned is unbound. If the second argument is an object, isinstance(obj, type) must be true. If the second argument is a type, issubclass(type2, type) must be true (this is useful for classmethods).

There are two typical use cases for super. In a class hierarchy with single inheritance, super can be used to refer to parent classes without naming them explicitly, thus making the code more maintainable. This use closely parallels the use of super in other programming languages.

The second use case is to support cooperative multiple inheritance in a dynamic execution environment. This use case is unique to Python and is not found in statically compiled languages or languages that only support single inheritance. This makes it possible to implement “diamond diagrams” where multiple base classes implement the same method. Good design dictates that such implementations have the same calling signature in every case (because the order of calls is determined at runtime, because that order adapts to changes in the class hierarchy, and because that order can include sibling classes that are unknown prior to runtime).

For both use cases, a typical superclass call looks like this:

In addition to method lookups, super() also works for attribute lookups. One possible use case for this is calling descriptors in a parent or sibling class.

Note that super() is implemented as part of the binding process for explicit dotted attribute lookups such as super().__getitem__(name) . It does so by implementing its own __getattribute__() method for searching classes in a predictable order that supports cooperative multiple inheritance. Accordingly, super() is undefined for implicit lookups using statements or operators such as super()[name] .

Also note that, aside from the zero argument form, super() is not limited to use inside methods. The two argument form specifies the arguments exactly and makes the appropriate references. The zero argument form only works inside a class definition, as the compiler fills in the necessary details to correctly retrieve the class being defined, as well as accessing the current instance for ordinary methods.

For practical suggestions on how to design cooperative classes using super() , see guide to using super().

class tuple class tuple ( iterable )

Rather than being a function, tuple is actually an immutable sequence type, as documented in Tuples and Sequence Types — list, tuple, range .

With one argument, return the type of an object. The return value is a type object and generally the same object as returned by object.__class__ .

The isinstance() built-in function is recommended for testing the type of an object, because it takes subclasses into account.

With three arguments, return a new type object. This is essentially a dynamic form of the class statement. The name string is the class name and becomes the __name__ attribute. The bases tuple contains the base classes and becomes the __bases__ attribute; if empty, object , the ultimate base of all classes, is added. The dict dictionary contains attribute and method definitions for the class body; it may be copied or wrapped before becoming the __dict__ attribute. The following two statements create identical type objects:

Keyword arguments provided to the three argument form are passed to the appropriate metaclass machinery (usually __init_subclass__() ) in the same way that keywords in a class definition (besides metaclass) would.

Changed in version 3.6: Subclasses of type which don’t override type.__new__ may no longer use the one-argument form to get the type of an object.

Return the __dict__ attribute for a module, class, instance, or any other object with a __dict__ attribute.

Objects such as modules and instances have an updateable __dict__ attribute; however, other objects may have write restrictions on their __dict__ attributes (for example, classes use a types.MappingProxyType to prevent direct dictionary updates).

Without an argument, vars() acts like locals() . Note, the locals dictionary is only useful for reads since updates to the locals dictionary are ignored.

A TypeError exception is raised if an object is specified but it doesn’t have a __dict__ attribute (for example, if its class defines the __slots__ attribute).

zip ( * iterables , strict = False ) ¶

Iterate over several iterables in parallel, producing tuples with an item from each one.

More formally: zip() returns an iterator of tuples, where the i-th tuple contains the i-th element from each of the argument iterables.

Another way to think of zip() is that it turns rows into columns, and columns into rows. This is similar to transposing a matrix.

zip() is lazy: The elements won’t be processed until the iterable is iterated on, e.g. by a for loop or by wrapping in a list .

One thing to consider is that the iterables passed to zip() could have different lengths; sometimes by design, and sometimes because of a bug in the code that prepared these iterables. Python offers three different approaches to dealing with this issue:

By default, zip() stops when the shortest iterable is exhausted. It will ignore the remaining items in the longer iterables, cutting off the result to the length of the shortest iterable:

zip() is often used in cases where the iterables are assumed to be of equal length. In such cases, it’s recommended to use the strict=True option. Its output is the same as regular zip() :

Unlike the default behavior, it raises a ValueError if one iterable is exhausted before the others:

Without the strict=True argument, any bug that results in iterables of different lengths will be silenced, possibly manifesting as a hard-to-find bug in another part of the program.

Shorter iterables can be padded with a constant value to make all the iterables have the same length. This is done by itertools.zip_longest() .

Edge cases: With a single iterable argument, zip() returns an iterator of 1-tuples. With no arguments, it returns an empty iterator.

Tips and tricks:

The left-to-right evaluation order of the iterables is guaranteed. This makes possible an idiom for clustering a data series into n-length groups using zip(*[iter(s)]*n, strict=True) . This repeats the same iterator n times so that each output tuple has the result of n calls to the iterator. This has the effect of dividing the input into n-length chunks.

zip() in conjunction with the * operator can be used to unzip a list:

Changed in version 3.10: Added the strict argument.

This is an advanced function that is not needed in everyday Python programming, unlike importlib.import_module() .

This function is invoked by the import statement. It can be replaced (by importing the builtins module and assigning to builtins.__import__ ) in order to change semantics of the import statement, but doing so is strongly discouraged as it is usually simpler to use import hooks (see PEP 302) to attain the same goals and does not cause issues with code which assumes the default import implementation is in use. Direct use of __import__() is also discouraged in favor of importlib.import_module() .

The function imports the module name, potentially using the given globals and locals to determine how to interpret the name in a package context. The fromlist gives the names of objects or submodules that should be imported from the module given by name. The standard implementation does not use its locals argument at all and uses its globals only to determine the package context of the import statement.

level specifies whether to use absolute or relative imports. 0 (the default) means only perform absolute imports. Positive values for level indicate the number of parent directories to search relative to the directory of the module calling __import__() (see PEP 328 for the details).

When the name variable is of the form package.module , normally, the top-level package (the name up till the first dot) is returned, not the module named by name. However, when a non-empty fromlist argument is given, the module named by name is returned.

For example, the statement import spam results in bytecode resembling the following code:

The statement import spam.ham results in this call:

Note how __import__() returns the toplevel module here because this is the object that is bound to a name by the import statement.

On the other hand, the statement from spam.ham import eggs, sausage as saus results in

Here, the spam.ham module is returned from __import__() . From this object, the names to import are retrieved and assigned to their respective names.

If you simply want to import a module (potentially within a package) by name, use importlib.import_module() .

Changed in version 3.3: Negative values for level are no longer supported (which also changes the default value to 0).

Changed in version 3.9: When the command line options -E or -I are being used, the environment variable PYTHONCASEOK is now ignored.

Note that the parser only accepts the Unix-style end of line convention. If you are reading the code from a file, make sure to use newline conversion mode to convert Windows or Mac-style newlines.


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