1 .. _tut-io: 2 3 **************** 4 Input and Output 5 **************** 6 7 There are several ways to present the output of a program; data can be printed 8 in a human-readable form, or written to a file for future use. This chapter will 9 discuss some of the possibilities. 10 11 12 .. _tut-formatting: 13 14 Fancier Output Formatting 15 ========================= 16 17 So far we've encountered two ways of writing values: *expression statements* and 18 the :func:`print` function. (A third way is using the :meth:`write` method 19 of file objects; the standard output file can be referenced as ``sys.stdout``. 20 See the Library Reference for more information on this.) 21 22 Often you'll want more control over the formatting of your output than simply 23 printing space-separated values. There are several ways to format output. 24 25 * To use :ref:`formatted string literals <tut-f-strings>`, begin a string 26 with ``f`` or ``F`` before the opening quotation mark or triple quotation mark. 27 Inside this string, you can write a Python expression between ``{`` and ``}`` 28 characters that can refer to variables or literal values. 29 30 :: 31 32 >>> year = 2016 33 >>> event = 'Referendum' 34 >>> f'Results of the {year} {event}' 35 'Results of the 2016 Referendum' 36 37 * The :meth:`str.format` method of strings requires more manual 38 effort. You'll still use ``{`` and ``}`` to mark where a variable 39 will be substituted and can provide detailed formatting directives, 40 but you'll also need to provide the information to be formatted. 41 42 :: 43 44 >>> yes_votes = 42_572_654 45 >>> no_votes = 43_132_495 46 >>> percentage = yes_votes / (yes_votes + no_votes) 47 >>> '{:-9} YES votes {:2.2%}'.format(yes_votes, percentage) 48 ' 42572654 YES votes 49.67%' 49 50 * Finally, you can do all the string handling yourself by using string slicing and 51 concatenation operations to create any layout you can imagine. The 52 string type has some methods that perform useful operations for padding 53 strings to a given column width. 54 55 When you don't need fancy output but just want a quick display of some 56 variables for debugging purposes, you can convert any value to a string with 57 the :func:`repr` or :func:`str` functions. 58 59 The :func:`str` function is meant to return representations of values which are 60 fairly human-readable, while :func:`repr` is meant to generate representations 61 which can be read by the interpreter (or will force a :exc:`SyntaxError` if 62 there is no equivalent syntax). For objects which don't have a particular 63 representation for human consumption, :func:`str` will return the same value as 64 :func:`repr`. Many values, such as numbers or structures like lists and 65 dictionaries, have the same representation using either function. Strings, in 66 particular, have two distinct representations. 67 68 Some examples:: 69 70 >>> s = 'Hello, world.' 71 >>> str(s) 72 'Hello, world.' 73 >>> repr(s) 74 "'Hello, world.'" 75 >>> str(1/7) 76 '0.14285714285714285' 77 >>> x = 10 * 3.25 78 >>> y = 200 * 200 79 >>> s = 'The value of x is ' + repr(x) + ', and y is ' + repr(y) + '...' 80 >>> print(s) 81 The value of x is 32.5, and y is 40000... 82 >>> # The repr() of a string adds string quotes and backslashes: 83 ... hello = 'hello, world\n' 84 >>> hellos = repr(hello) 85 >>> print(hellos) 86 'hello, world\n' 87 >>> # The argument to repr() may be any Python object: 88 ... repr((x, y, ('spam', 'eggs'))) 89 "(32.5, 40000, ('spam', 'eggs'))" 90 91 The :mod:`string` module contains a :class:`~string.Template` class that offers 92 yet another way to substitute values into strings, using placeholders like 93 ``$x`` and replacing them with values from a dictionary, but offers much less 94 control of the formatting. 95 96 97 .. _tut-f-strings: 98 99 Formatted String Literals 100 ------------------------- 101 102 :ref:`Formatted string literals <f-strings>` (also called f-strings for 103 short) let you include the value of Python expressions inside a string by 104 prefixing the string with ``f`` or ``F`` and writing expressions as 105 ``{expression}``. 106 107 An optional format specifier can follow the expression. This allows greater 108 control over how the value is formatted. The following example rounds pi to 109 three places after the decimal:: 110 111 >>> import math 112 >>> print(f'The value of pi is approximately {math.pi:.3f}.') 113 The value of pi is approximately 3.142. 114 115 Passing an integer after the ``':'`` will cause that field to be a minimum 116 number of characters wide. This is useful for making columns line up. :: 117 118 >>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 7678} 119 >>> for name, phone in table.items(): 120 ... print(f'{name:10} ==> {phone:10d}') 121 ... 122 Sjoerd ==> 4127 123 Jack ==> 4098 124 Dcab ==> 7678 125 126 Other modifiers can be used to convert the value before it is formatted. 127 ``'!a'`` applies :func:`ascii`, ``'!s'`` applies :func:`str`, and ``'!r'`` 128 applies :func:`repr`:: 129 130 >>> animals = 'eels' 131 >>> print(f'My hovercraft is full of {animals}.') 132 My hovercraft is full of eels. 133 >>> print(f'My hovercraft is full of {animals!r}.') 134 My hovercraft is full of 'eels'. 135 136 For a reference on these format specifications, see 137 the reference guide for the :ref:`formatspec`. 138 139 .. _tut-string-format: 140 141 The String format() Method 142 -------------------------- 143 144 Basic usage of the :meth:`str.format` method looks like this:: 145 146 >>> print('We are the {} who say "{}!"'.format('knights', 'Ni')) 147 We are the knights who say "Ni!" 148 149 The brackets and characters within them (called format fields) are replaced with 150 the objects passed into the :meth:`str.format` method. A number in the 151 brackets can be used to refer to the position of the object passed into the 152 :meth:`str.format` method. :: 153 154 >>> print('{0} and {1}'.format('spam', 'eggs')) 155 spam and eggs 156 >>> print('{1} and {0}'.format('spam', 'eggs')) 157 eggs and spam 158 159 If keyword arguments are used in the :meth:`str.format` method, their values 160 are referred to by using the name of the argument. :: 161 162 >>> print('This {food} is {adjective}.'.format( 163 ... food='spam', adjective='absolutely horrible')) 164 This spam is absolutely horrible. 165 166 Positional and keyword arguments can be arbitrarily combined:: 167 168 >>> print('The story of {0}, {1}, and {other}.'.format('Bill', 'Manfred', 169 other='Georg')) 170 The story of Bill, Manfred, and Georg. 171 172 If you have a really long format string that you don't want to split up, it 173 would be nice if you could reference the variables to be formatted by name 174 instead of by position. This can be done by simply passing the dict and using 175 square brackets ``'[]'`` to access the keys :: 176 177 >>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678} 178 >>> print('Jack: {0[Jack]:d}; Sjoerd: {0[Sjoerd]:d}; ' 179 ... 'Dcab: {0[Dcab]:d}'.format(table)) 180 Jack: 4098; Sjoerd: 4127; Dcab: 8637678 181 182 This could also be done by passing the table as keyword arguments with the '**' 183 notation. :: 184 185 >>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678} 186 >>> print('Jack: {Jack:d}; Sjoerd: {Sjoerd:d}; Dcab: {Dcab:d}'.format(**table)) 187 Jack: 4098; Sjoerd: 4127; Dcab: 8637678 188 189 This is particularly useful in combination with the built-in function 190 :func:`vars`, which returns a dictionary containing all local variables. 191 192 As an example, the following lines produce a tidily-aligned 193 set of columns giving integers and their squares and cubes:: 194 195 >>> for x in range(1, 11): 196 ... print('{0:2d} {1:3d} {2:4d}'.format(x, x*x, x*x*x)) 197 ... 198 1 1 1 199 2 4 8 200 3 9 27 201 4 16 64 202 5 25 125 203 6 36 216 204 7 49 343 205 8 64 512 206 9 81 729 207 10 100 1000 208 209 For a complete overview of string formatting with :meth:`str.format`, see 210 :ref:`formatstrings`. 211 212 213 Manual String Formatting 214 ------------------------ 215 216 Here's the same table of squares and cubes, formatted manually:: 217 218 >>> for x in range(1, 11): 219 ... print(repr(x).rjust(2), repr(x*x).rjust(3), end=' ') 220 ... # Note use of 'end' on previous line 221 ... print(repr(x*x*x).rjust(4)) 222 ... 223 1 1 1 224 2 4 8 225 3 9 27 226 4 16 64 227 5 25 125 228 6 36 216 229 7 49 343 230 8 64 512 231 9 81 729 232 10 100 1000 233 234 (Note that the one space between each column was added by the 235 way :func:`print` works: it always adds spaces between its arguments.) 236 237 The :meth:`str.rjust` method of string objects right-justifies a string in a 238 field of a given width by padding it with spaces on the left. There are 239 similar methods :meth:`str.ljust` and :meth:`str.center`. These methods do 240 not write anything, they just return a new string. If the input string is too 241 long, they don't truncate it, but return it unchanged; this will mess up your 242 column lay-out but that's usually better than the alternative, which would be 243 lying about a value. (If you really want truncation you can always add a 244 slice operation, as in ``x.ljust(n)[:n]``.) 245 246 There is another method, :meth:`str.zfill`, which pads a numeric string on the 247 left with zeros. It understands about plus and minus signs:: 248 249 >>> '12'.zfill(5) 250 '00012' 251 >>> '-3.14'.zfill(7) 252 '-003.14' 253 >>> '3.14159265359'.zfill(5) 254 '3.14159265359' 255 256 257 Old string formatting 258 --------------------- 259 260 The ``%`` operator can also be used for string formatting. It interprets the 261 left argument much like a :c:func:`sprintf`\ -style format string to be applied 262 to the right argument, and returns the string resulting from this formatting 263 operation. For example:: 264 265 >>> import math 266 >>> print('The value of pi is approximately %5.3f.' % math.pi) 267 The value of pi is approximately 3.142. 268 269 More information can be found in the :ref:`old-string-formatting` section. 270 271 272 .. _tut-files: 273 274 Reading and Writing Files 275 ========================= 276 277 .. index:: 278 builtin: open 279 object: file 280 281 :func:`open` returns a :term:`file object`, and is most commonly used with 282 two arguments: ``open(filename, mode)``. 283 284 :: 285 286 >>> f = open('workfile', 'w') 287 288 .. XXX str(f) is <io.TextIOWrapper object at 0x82e8dc4> 289 290 >>> print(f) 291 <open file 'workfile', mode 'w' at 80a0960> 292 293 The first argument is a string containing the filename. The second argument is 294 another string containing a few characters describing the way in which the file 295 will be used. *mode* can be ``'r'`` when the file will only be read, ``'w'`` 296 for only writing (an existing file with the same name will be erased), and 297 ``'a'`` opens the file for appending; any data written to the file is 298 automatically added to the end. ``'r+'`` opens the file for both reading and 299 writing. The *mode* argument is optional; ``'r'`` will be assumed if it's 300 omitted. 301 302 Normally, files are opened in :dfn:`text mode`, that means, you read and write 303 strings from and to the file, which are encoded in a specific encoding. If 304 encoding is not specified, the default is platform dependent (see 305 :func:`open`). ``'b'`` appended to the mode opens the file in 306 :dfn:`binary mode`: now the data is read and written in the form of bytes 307 objects. This mode should be used for all files that don't contain text. 308 309 In text mode, the default when reading is to convert platform-specific line 310 endings (``\n`` on Unix, ``\r\n`` on Windows) to just ``\n``. When writing in 311 text mode, the default is to convert occurrences of ``\n`` back to 312 platform-specific line endings. This behind-the-scenes modification 313 to file data is fine for text files, but will corrupt binary data like that in 314 :file:`JPEG` or :file:`EXE` files. Be very careful to use binary mode when 315 reading and writing such files. 316 317 It is good practice to use the :keyword:`with` keyword when dealing 318 with file objects. The advantage is that the file is properly closed 319 after its suite finishes, even if an exception is raised at some 320 point. Using :keyword:`!with` is also much shorter than writing 321 equivalent :keyword:`try`\ -\ :keyword:`finally` blocks:: 322 323 >>> with open('workfile') as f: 324 ... read_data = f.read() 325 >>> f.closed 326 True 327 328 If you're not using the :keyword:`with` keyword, then you should call 329 ``f.close()`` to close the file and immediately free up any system 330 resources used by it. If you don't explicitly close a file, Python's 331 garbage collector will eventually destroy the object and close the 332 open file for you, but the file may stay open for a while. Another 333 risk is that different Python implementations will do this clean-up at 334 different times. 335 336 After a file object is closed, either by a :keyword:`with` statement 337 or by calling ``f.close()``, attempts to use the file object will 338 automatically fail. :: 339 340 >>> f.close() 341 >>> f.read() 342 Traceback (most recent call last): 343 File "<stdin>", line 1, in <module> 344 ValueError: I/O operation on closed file. 345 346 347 .. _tut-filemethods: 348 349 Methods of File Objects 350 ----------------------- 351 352 The rest of the examples in this section will assume that a file object called 353 ``f`` has already been created. 354 355 To read a file's contents, call ``f.read(size)``, which reads some quantity of 356 data and returns it as a string (in text mode) or bytes object (in binary mode). 357 *size* is an optional numeric argument. When *size* is omitted or negative, the 358 entire contents of the file will be read and returned; it's your problem if the 359 file is twice as large as your machine's memory. Otherwise, at most *size* bytes 360 are read and returned. 361 If the end of the file has been reached, ``f.read()`` will return an empty 362 string (``''``). :: 363 364 >>> f.read() 365 'This is the entire file.\n' 366 >>> f.read() 367 '' 368 369 ``f.readline()`` reads a single line from the file; a newline character (``\n``) 370 is left at the end of the string, and is only omitted on the last line of the 371 file if the file doesn't end in a newline. This makes the return value 372 unambiguous; if ``f.readline()`` returns an empty string, the end of the file 373 has been reached, while a blank line is represented by ``'\n'``, a string 374 containing only a single newline. :: 375 376 >>> f.readline() 377 'This is the first line of the file.\n' 378 >>> f.readline() 379 'Second line of the file\n' 380 >>> f.readline() 381 '' 382 383 For reading lines from a file, you can loop over the file object. This is memory 384 efficient, fast, and leads to simple code:: 385 386 >>> for line in f: 387 ... print(line, end='') 388 ... 389 This is the first line of the file. 390 Second line of the file 391 392 If you want to read all the lines of a file in a list you can also use 393 ``list(f)`` or ``f.readlines()``. 394 395 ``f.write(string)`` writes the contents of *string* to the file, returning 396 the number of characters written. :: 397 398 >>> f.write('This is a test\n') 399 15 400 401 Other types of objects need to be converted -- either to a string (in text mode) 402 or a bytes object (in binary mode) -- before writing them:: 403 404 >>> value = ('the answer', 42) 405 >>> s = str(value) # convert the tuple to string 406 >>> f.write(s) 407 18 408 409 ``f.tell()`` returns an integer giving the file object's current position in the file 410 represented as number of bytes from the beginning of the file when in binary mode and 411 an opaque number when in text mode. 412 413 To change the file object's position, use ``f.seek(offset, from_what)``. The position is computed 414 from adding *offset* to a reference point; the reference point is selected by 415 the *from_what* argument. A *from_what* value of 0 measures from the beginning 416 of the file, 1 uses the current file position, and 2 uses the end of the file as 417 the reference point. *from_what* can be omitted and defaults to 0, using the 418 beginning of the file as the reference point. :: 419 420 >>> f = open('workfile', 'rb+') 421 >>> f.write(b'0123456789abcdef') 422 16 423 >>> f.seek(5) # Go to the 6th byte in the file 424 5 425 >>> f.read(1) 426 b'5' 427 >>> f.seek(-3, 2) # Go to the 3rd byte before the end 428 13 429 >>> f.read(1) 430 b'd' 431 432 In text files (those opened without a ``b`` in the mode string), only seeks 433 relative to the beginning of the file are allowed (the exception being seeking 434 to the very file end with ``seek(0, 2)``) and the only valid *offset* values are 435 those returned from the ``f.tell()``, or zero. Any other *offset* value produces 436 undefined behaviour. 437 438 File objects have some additional methods, such as :meth:`~file.isatty` and 439 :meth:`~file.truncate` which are less frequently used; consult the Library 440 Reference for a complete guide to file objects. 441 442 443 .. _tut-json: 444 445 Saving structured data with :mod:`json` 446 --------------------------------------- 447 448 .. index:: module: json 449 450 Strings can easily be written to and read from a file. Numbers take a bit more 451 effort, since the :meth:`read` method only returns strings, which will have to 452 be passed to a function like :func:`int`, which takes a string like ``'123'`` 453 and returns its numeric value 123. When you want to save more complex data 454 types like nested lists and dictionaries, parsing and serializing by hand 455 becomes complicated. 456 457 Rather than having users constantly writing and debugging code to save 458 complicated data types to files, Python allows you to use the popular data 459 interchange format called `JSON (JavaScript Object Notation) 460 <http://json.org>`_. The standard module called :mod:`json` can take Python 461 data hierarchies, and convert them to string representations; this process is 462 called :dfn:`serializing`. Reconstructing the data from the string representation 463 is called :dfn:`deserializing`. Between serializing and deserializing, the 464 string representing the object may have been stored in a file or data, or 465 sent over a network connection to some distant machine. 466 467 .. note:: 468 The JSON format is commonly used by modern applications to allow for data 469 exchange. Many programmers are already familiar with it, which makes 470 it a good choice for interoperability. 471 472 If you have an object ``x``, you can view its JSON string representation with a 473 simple line of code:: 474 475 >>> import json 476 >>> json.dumps([1, 'simple', 'list']) 477 '[1, "simple", "list"]' 478 479 Another variant of the :func:`~json.dumps` function, called :func:`~json.dump`, 480 simply serializes the object to a :term:`text file`. So if ``f`` is a 481 :term:`text file` object opened for writing, we can do this:: 482 483 json.dump(x, f) 484 485 To decode the object again, if ``f`` is a :term:`text file` object which has 486 been opened for reading:: 487 488 x = json.load(f) 489 490 This simple serialization technique can handle lists and dictionaries, but 491 serializing arbitrary class instances in JSON requires a bit of extra effort. 492 The reference for the :mod:`json` module contains an explanation of this. 493 494 .. seealso:: 495 496 :mod:`pickle` - the pickle module 497 498 Contrary to :ref:`JSON <tut-json>`, *pickle* is a protocol which allows 499 the serialization of arbitrarily complex Python objects. As such, it is 500 specific to Python and cannot be used to communicate with applications 501 written in other languages. It is also insecure by default: 502 deserializing pickle data coming from an untrusted source can execute 503 arbitrary code, if the data was crafted by a skilled attacker. 504