File string python ошибка

Python известен своим простым синтаксисом. Однако, когда вы изучаете Python в первый раз или когда вы попали на Python с большим опытом работы на другом языке программирования, вы можете столкнуться с некоторыми вещами, которые Python не позволяет. Если вы когда-либо получали + SyntaxError + при попытке запустить код Python, то это руководство может вам помочь. В этом руководстве вы увидите общие примеры неправильного синтаксиса в Python и узнаете, как решить эту проблему.

*Примечание:* Если ваш код *синтаксически* правильный, то вы можете получить другие исключения, которые не являются `+ SyntaxError +`. Чтобы узнать больше о других исключениях Python и о том, как их обрабатывать, ознакомьтесь с https://realpython.com/python-exceptions/[Python Exceptions: Введение].

 1 # theofficefacts.py
 2 ages = {
 3     'pam': 24,
 4     'jim': 24
 5     'michael': 43
 6 }
 7 print(f'Michael is {ages["michael"]} years old.')

$ python theofficefacts.py
File "theofficefacts.py", line 5
    'michael': 43
            ^
SyntaxError: invalid syntax

*Примечание:* В этом руководстве предполагается, что вы знакомы с основами *tracebacks* в Python. Чтобы узнать больше о трассировке Python и о том, как их читать, ознакомьтесь с https://realpython.com/python-traceback/[Understanding Python Traceback].

>>> len('hello') = 5
  File "<stdin>", line 1
SyntaxError: can't assign to function call

>>> 'foo' = 1
  File "<stdin>", line 1
SyntaxError: can't assign to literal

>>> 1 = 'foo'
  File "<stdin>", line 1
SyntaxError: can't assign to literal

*Примечание:* В приведенных выше примерах отсутствует повторяющаяся строка кода и каретка (`+ ^ +`), указывающая на проблему в трассировке. Исключение и обратная трассировка, которые вы видите, будут другими, когда вы находитесь в REPL и пытаетесь выполнить этот код из файла. Если бы этот код был в файле, то вы бы получили повторяющуюся строку кода и указали на проблему, как вы видели в других случаях в этом руководстве.

>>> len('hello') == 5
True

>>> fro i in range(10):
  File "<stdin>", line 1
    fro i in range(10):
        ^
SyntaxError: invalid syntax

>>> for i range(10):
  File "<stdin>", line 1
    for i range(10):
              ^
SyntaxError: invalid syntax

>>> names = ['pam', 'jim', 'michael']
>>> if 'jim' in names:
...     print('jim found')
...     break
...
  File "<stdin>", line 3
SyntaxError: 'break' outside loop

>>> if 'jim' in names:
...     print('jim found')
...     continue
...
  File "<stdin>", line 3
SyntaxError: 'continue' not properly in loop

>>> pass = True
  File "<stdin>", line 1
    pass = True
         ^
SyntaxError: invalid syntax

>>> def pass():
  File "<stdin>", line 1
    def pass():
           ^
SyntaxError: invalid syntax

import keyword
print(keyword.kwlist)

>>> import keyword; keyword.iskeyword('pass')
True

>>> message = 'don't'
  File "<stdin>", line 1
    message = 'don't'
                   ^
SyntaxError: invalid syntax

>>> message = "This is an unclosed string
  File "<stdin>", line 1
    message = "This is an unclosed string
                                        ^
SyntaxError: EOL while scanning string literal

 1 # theofficefacts.py
 2 ages = {
 3     'pam': 24,
 4     'jim': 24,
 5     'michael': 43
 6 }
 7 print(f'Michael is {ages["michael]} years old.')

$ python theofficefacts.py
  File "theofficefacts.py", line 7
    print(f'Michael is {ages["michael]} years old.')
         ^
SyntaxError: f-string: unterminated string

# missing.py
def foo():
    return [1, 2, 3

print(foo())

$ python missing.py
  File "missing.py", line 5
    print(foo())
        ^
SyntaxError: invalid syntax

# missing.py
def foo():
    return [1, 2, 3,

print(foo())

$ python missing.py
  File "missing.py", line 6

                ^
SyntaxError: unexpected EOF while parsing

>>> ages = {'pam'=24}
  File "<stdin>", line 1
    ages = {'pam'=24}
                 ^
SyntaxError: invalid syntax

>>> ages = dict(pam=24)
>>> ages
{'pam': 24}

 1 # indentation.py
 2 def foo():
 3     for i in range(10):
 4         print(i)
 5   print('done')
 6
 7 foo()

$ python indentation.py
  File "indentation.py", line 5
    print('done')
                ^
IndentationError: unindent does not match any outer indentation level

 1 # indentation.py
 2 def foo():
 3     for i in range(10):
 4         print(i)
 5     print('done')
 6
 7 foo()

$ tabs 4 # Sets the shell tab width to 4 spaces
$ cat -n indentation.py
     1   # indentation.py
     2   def foo():
     3       for i in range(10)
     4           print(i)
     5       print('done')
     6
     7   foo()

$ tabs 8 # Sets the shell tab width to 8 spaces (standard)
$ cat -n indentation.py
     1   # indentation.py
     2   def foo():
     3       for i in range(10)
     4           print(i)
     5           print('done')
     6
     7   foo()

$ tabs 3 # Sets the shell tab width to 3 spaces
$ cat -n indentation.py
     1   # indentation.py
     2   def foo():
     3       for i in range(10)
     4           print(i)
     5      print('done')
     6
     7   foo()

$ python indentation.py
  File "indentation.py", line 5
    print('done')
                ^
TabError: inconsistent use of tabs and spaces in indentation

>>> def fun();
  File "<stdin>", line 1
    def fun();
             ^
SyntaxError: invalid syntax

>>> def fun(a, b):
...     print(a, b)
...
>>> fun(a=1, 2)
  File "<stdin>", line 1
SyntaxError: positional argument follows keyword argument

>>> # Valid Python 2 syntax that fails in Python 3
>>> print 'hello'
  File "<stdin>", line 1
    print 'hello'
                ^
SyntaxError: Missing parentheses in call to 'print'. Did you mean print('hello')?

>>> # Any version of python before 3.6 including 2.7
>>> w ='world'
>>> print(f'hello, {w}')
  File "<stdin>", line 1
    print(f'hello, {w}')
                      ^
SyntaxError: invalid syntax

>>> [(1,2)(2,3)]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'tuple' object is not callable

>>> [(1,2)(2,3)]
<stdin>:1: SyntaxWarning: 'tuple' object is not callable; perhaps you missed a comma?
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'tuple' object is not callable

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Identify Invalid Python Syntax

Python is known for its simple syntax. However, when you’re learning Python for the first time or when you’ve come to Python with a solid background in another programming language, you may run into some things that Python doesn’t allow. If you’ve ever received a SyntaxError when trying to run your Python code, then this guide can help you. Throughout this tutorial, you’ll see common examples of invalid syntax in Python and learn how to resolve the issue.

By the end of this tutorial, you’ll be able to:

• Identify invalid syntax in Python
• Make sense of SyntaxError tracebacks
• Resolve invalid syntax or prevent it altogether

 1# theofficefacts.py
 2ages = {
 3    'pam': 24,
 4    'jim': 24
 5    'michael': 43
 6}
 7print(f'Michael is {ages["michael"]} years old.')

$ python theofficefacts.py
File "theofficefacts.py", line 5
    'michael': 43
            ^
SyntaxError: invalid syntax

>>> len('hello') = 5
  File "<stdin>", line 1
SyntaxError: can't assign to function call

>>> 'foo' = 1
  File "<stdin>", line 1
SyntaxError: can't assign to literal

>>> 1 = 'foo'
  File "<stdin>", line 1
SyntaxError: can't assign to literal

>>> len('hello') == 5
True

>>> fro i in range(10):
  File "<stdin>", line 1
    fro i in range(10):
        ^
SyntaxError: invalid syntax

>>> for i range(10):
  File "<stdin>", line 1
    for i range(10):
              ^
SyntaxError: invalid syntax

>>> names = ['pam', 'jim', 'michael']
>>> if 'jim' in names:
...     print('jim found')
...     break
...
  File "<stdin>", line 3
SyntaxError: 'break' outside loop

>>> if 'jim' in names:
...     print('jim found')
...     continue
...
  File "<stdin>", line 3
SyntaxError: 'continue' not properly in loop

>>> pass = True
  File "<stdin>", line 1
    pass = True
         ^
SyntaxError: invalid syntax

>>> def pass():
  File "<stdin>", line 1
    def pass():
           ^
SyntaxError: invalid syntax

import keyword
print(keyword.kwlist)

>>> import keyword; keyword.iskeyword('pass')
True

>>> message = 'don't'
  File "<stdin>", line 1
    message = 'don't'
                   ^
SyntaxError: invalid syntax

>>> message = "This is an unclosed string
  File "<stdin>", line 1
    message = "This is an unclosed string
                                        ^
SyntaxError: EOL while scanning string literal

 1# theofficefacts.py
 2ages = {
 3    'pam': 24,
 4    'jim': 24,
 5    'michael': 43
 6}
 7print(f'Michael is {ages["michael]} years old.')

$ python theofficefacts.py
  File "theofficefacts.py", line 7
    print(f'Michael is {ages["michael]} years old.')
         ^
SyntaxError: f-string: unterminated string

# missing.py
def foo():
    return [1, 2, 3

print(foo())

$ python missing.py
  File "missing.py", line 5
    print(foo())
        ^
SyntaxError: invalid syntax

# missing.py
def foo():
    return [1, 2, 3,

print(foo())

$ python missing.py
  File "missing.py", line 6

                ^
SyntaxError: unexpected EOF while parsing

>>> ages = {'pam'=24}
  File "<stdin>", line 1
    ages = {'pam'=24}
                 ^
SyntaxError: invalid syntax

>>> ages = dict(pam=24)
>>> ages
{'pam': 24}

 1# indentation.py
 2def foo():
 3    for i in range(10):
 4        print(i)
 5  print('done')
 6
 7foo()

$ python indentation.py
  File "indentation.py", line 5
    print('done')
                ^
IndentationError: unindent does not match any outer indentation level

 1# indentation.py
 2def foo():
 3    for i in range(10):
 4        print(i)
 5    print('done')
 6
 7foo()

$ tabs 4 # Sets the shell tab width to 4 spaces
$ cat -n indentation.py
     1   # indentation.py
     2   def foo():
     3       for i in range(10)
     4           print(i)
     5       print('done')
     6   
     7   foo()

$ tabs 8 # Sets the shell tab width to 8 spaces (standard)
$ cat -n indentation.py
     1   # indentation.py
     2   def foo():
     3       for i in range(10)
     4           print(i)
     5           print('done')
     6   
     7   foo()

$ tabs 3 # Sets the shell tab width to 3 spaces
$ cat -n indentation.py
     1   # indentation.py
     2   def foo():
     3       for i in range(10)
     4           print(i)
     5      print('done')
     6   
     7   foo()

$ python indentation.py
  File "indentation.py", line 5
    print('done')
                ^
TabError: inconsistent use of tabs and spaces in indentation

>>> def fun();
  File "<stdin>", line 1
    def fun();
             ^
SyntaxError: invalid syntax

>>> def fun(a, b):
...     print(a, b)
...
>>> fun(a=1, 2)
  File "<stdin>", line 1
SyntaxError: positional argument follows keyword argument

>>> # Valid Python 2 syntax that fails in Python 3
>>> print 'hello'
  File "<stdin>", line 1
    print 'hello'
                ^
SyntaxError: Missing parentheses in call to 'print'. Did you mean print('hello')?

>>> # Any version of python before 3.6 including 2.7
>>> w ='world'
>>> print(f'hello, {w}')
  File "<stdin>", line 1
    print(f'hello, {w}')
                      ^
SyntaxError: invalid syntax

>>> [(1,2)(2,3)]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'tuple' object is not callable

>>> [(1,2)(2,3)]
<stdin>:1: SyntaxWarning: 'tuple' object is not callable; perhaps you missed a comma?
Traceback (most recent call last):   
  File "<stdin>", line 1, in <module>    
TypeError: 'tuple' object is not callable

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Identify Invalid Python Syntax

Моя программа не работает! Что делать? В данной статье я постараюсь собрать наиболее частые ошибки начинающих программировать на python 3, а также расскажу, как их исправлять.

Проблема: Моя программа не запускается. На доли секунды появляется чёрное окошко, а затем исчезает.

Причина: после окончания выполнения программы (после выполнения всего кода или при возникновении исключения программа закрывается. И если вы её вызвали двойным кликом по иконке (а вы, скорее всего, вызвали её именно так), то она закроется вместе с окошком, в котором находится вывод программы.

Решение: запускать программу через IDLE или через консоль.

Проблема: Не работает функция input. Пишет SyntaxError.

Пример кода:

>>> a = input()
hello world
  File "<string>", line 1
    hello world
              ^
SyntaxError: unexpected EOF while parsing

Причина: Вы запустили Python 2.

Решение: Установить Python 3.

Проблема: Где-то увидел простую программу, а она не работает.

Пример кода:

name = raw_input()
print name

Ошибка:

  File "a.py", line 3
    print name
             ^
SyntaxError: invalid syntax

Причина: Вам подсунули программу на Python 2.

Решение: Прочитать об отличиях Python 2 от Python 3. Переписать её на Python 3. Например, данная программа на Python 3 будет выглядеть так:

name = input()
print(name)

Проблема: TypeError: Can’t convert ‘int’ object to str implicitly.

Пример кода:

>>> a = input() + 5
8
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: Can't convert 'int' object to str implicitly

Причина: Нельзя складывать строку с числом.

Решение: Привести строку к числу с помощью функции int(). Кстати, заметьте, что функция input() всегда возвращает строку!

>>> a = int(input()) + 5
8
>>> a
13

Проблема: SyntaxError: invalid syntax.

Пример кода:

a = 5
if a == 5
    print('Ура!')

Ошибка:

  File "a.py", line 3
    if a == 5
            ^
SyntaxError: invalid syntax

Причина: Забыто двоеточие.

Решение:

a = 5
if a == 5:
    print('Ура!')

Проблема: SyntaxError: invalid syntax.

Пример кода:

a = 5
if a = 5:
    print('Ура!')

Ошибка:

  File "a.py", line 3
    if a = 5
         ^
SyntaxError: invalid syntax

Причина: Забыто равно.

Решение:

a = 5
if a == 5:
    print('Ура!')

Проблема: NameError: name ‘a’ is not defined.

Пример кода:

print(a)

Причина: Переменная «a» не существует. Возможно, вы опечатались в названии или забыли инициализировать её.

Решение: Исправить опечатку.

a = 10
print(a)

Проблема: IndentationError: expected an indented block.

Пример кода:

a = 10
if a > 0:
print(a)

Причина: Нужен отступ.

Решение:

a = 10
if a > 0:
    print(a)

Проблема: TabError: inconsistent use of tabs and spaces in indentation.

Пример кода:

a = 10
if a > 0:
    print(a)
    print('Ура!')

Ошибка:

  File "a.py", line 5
    print('Ура!')
                 ^
TabError: inconsistent use of tabs and spaces in indentation

Причина: Смешение пробелов и табуляции в отступах.

Решение: Исправить отступы.

a = 10
if a > 0:
    print(a)
    print('Ура!')

Проблема: UnboundLocalError: local variable ‘a’ referenced before assignment.

Пример кода:

def f():
    a += 1
    print(a)

a = 10
f()

Ошибка:

Traceback (most recent call last):
  File "a.py", line 7, in <module>
    f()
  File "a.py", line 3, in f
    a += 1
UnboundLocalError: local variable 'a' referenced before assignment

Причина: Попытка обратиться к локальной переменной, которая ещё не создана.

Решение:

def f():
    global a
    a += 1
    print(a)

a = 10
f()

Проблема: Программа выполнилась, но в файл ничего не записалось / записалось не всё.

Пример кода:

>>> f = open('output.txt', 'w', encoding='utf-8')
>>> f.write('bla')
3
>>>

Причина: Не закрыт файл, часть данных могла остаться в буфере.

Решение:

>>> f = open('output.txt', 'w', encoding='utf-8')
>>> f.write('bla')
3
>>> f.close()
>>>

Проблема: Здесь может быть ваша проблема. Комментарии чуть ниже

Также вам может быть полезно это описание:

1. the file "<stdin>", line 1, in <module> Error in Python
2. Resolve the File "<stdin>", line 1, in <module> Error in Python
3. Conclusion

Errors are something that we often encounter while coding in any particular programming language. However, there are mainly three types of errors: syntax, logical, and runtime.

In this article, we will be discussing the most common syntax error that people face, which is the File "<stdin>", line 1, in <module> error. Let us see why this error occurs and how to resolve it in Python.

the file "<stdin>", line 1, in <module> Error in Python

Errors are unexpected situations that the programmers commit that result in the unusual working of the program. As discussed earlier, there are mainly three types of errors: Syntax, Logical, and Runtime.

However, we will mainly be concerned about a particular syntax error File "<stdin>", line 1, in <module> in this article that beginners or even experienced professionals often encounter while programming in Python.

Syntax errors occur when there is a problem in the program’s syntax. For example, using a keyword as a variable, incorrect indentation of the code, etc.

Therefore, this error mainly occurs if we use invalid syntax in our program.

The error File "<stdin>", line 1, in <module> is also a type of syntax error that occurs whenever we have a problem with the syntax of the program while using the Python interpreter.

The error refers to a problem in line 1 of the program followed by an error message that signifies the error in the program. Moreover, it also displays a line number to indicate where to look in the code for the mentioned error.

Now, let us see some examples of the error File "<stdin>", line 1, in <module>.

Resolve the File "<stdin>", line 1, in <module> Error in Python

Now, we will be seeing some of the examples of the File "<stdin>", line 1, in <module> error and how this error can be resolved in Python.

Running a Python File on the Interpreter Gives the File "<stdin>", line 1, in <module> Error

When we try to run a Python file in the Python interpreter, we encounter this error below.

Below is the Python file ex1.py to be executed.

print("Hello, user!")
print("Welcome to the page,")
print("Hope you will enjoy the experience.")

However, when we try to run this ex1.py file in the interpreter, we get the following output.

>>> python ex1.py
  File "<stdin>", line 1
    python ex1.py
           ^
SyntaxError: invalid syntax

However, it occurs because the file ex1.py should not be executed on the Python interpreter but should have been done on the terminal.

Python interpreters are meant to run only valid Python statements and not the whole files. Therefore, we should use the terminal for that whenever we have to run a Python file.

However, to get back to the terminal while you are using the Python interpreter, you should either type exit() and press the Enter key to take an exit from the Python interpreter or directly press CTRL+D for exiting the Python interpreter.

Let us see how to take an exit from the Python interpreter.

Now, you must have been at the terminal. Therefore, go to the specified path on which your Python file is saved and then write python <file_name> to run your file without getting the File "<stdin>", line 1, in <module> error.

The output will appear something like below on executing the desired file.

D:poll>python ex1.py
Hello, user!
Welcome to the page,
Hope you will enjoy the experience.

In this way, we can remove the File "<stdin>", line 1, in <module> error from our program.

Invalid Syntax Statements in Python Causes the File "<stdin>", line 1, in <module> Error

The invalid syntax, such as using invalid names, division of a number by 0, etc., can also cause the File "<stdin>", line 1, in <module> error. Let us now see them in detail.

Output:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'x' is not defined

Therefore, the output shows the File "<stdin>", line 1, in <module> NameError error as the answer variable is assigned a value of x which is not defined anywhere in the program.

To resolve the issue, we need to define the variable x below the answer variable.

However, another example of the File "<stdin>", line 1, in <module> error can be the division of a number by 0. Let us have a look at it.

>>> 1/0
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ZeroDivisionError: division by zero

Therefore, as you can see above, the division throws the same error.

However, all the above examples are executed on the interpreter, and they work fine because they are single statements and not files. Therefore, you must remember that you can only execute valid statements on the Python interpreter, not the whole Python file.

For executing the Python files, you must use the terminal.

Moreover, the error File "<stdin>", line 1, in <module> can also be written as File "<stdin>", line 6, in <module> depending on the line number on which the error is encountered but the meaning of the error and the way to solve it remains the same.

Conclusion

In this article, we have studied the most common error that programmers often encounter while programming in Python, which is the File "<stdin>", line 1, in <module> error. This error often occurs because of executing a file in the Python interpreter or having some syntax errors in the Python code.

However, we have discussed how these errors can be resolved that are executing a Python file in a terminal instead of the interpreter in the case of a file, whereas resolving the appropriate syntax errors in the program in the case of the Python statements.

SyntaxError — это ошибка, которая легко может ввести в ступор начинающего программиста. Стоит забыть одну запятую или не там поставить кавычку и Python наотрез откажется запускать программу. Что ещё хуже, по выводу в консоль сложно сообразить в чём дело. Выглядят сообщения страшно и непонятно. Что с этим делать — не ясно. Вот неполный список того, что можно встретить:

• SyntaxError: invalid syntax
• SyntaxError: EOL while scanning string literal
• SyntaxError: unexpected EOF while parsing

Эта статья о том, как справиться с синтаксической ошибкой SyntaxError. Дочитайте её до конца и получите безотказный простой алгоритм действий, что поможет вам в трудную минуту — ваш спасательный круг.

Работать будем с программой, которая выводит на экран список учеников. Её код выглядит немного громоздко и, возможно, непривычно. Если не всё написанное вам понятно, то не отчаивайтесь, чтению статьи это не помешает.

students = [
    ['Егор', 'Кузьмин'],
    ['Денис', 'Давыдов'],
]

for first_name, last_name in students:
    label = 'Имя ученика: {first_name} {last_name}'.format(
        first_name = first_name
        last_name = last_name
    )

    print(label)

Ожидается примерно такой результат в консоли:

$ python script.py
Имя ученика: Егор Кузьмин
Имя ученика: Денис Давыдов

Но запуск программы приводит к совсем другому результату. Скрипт сломан:

$ python script.py
  File "script.py", line 9
    last_name = last_name
            ^
SyntaxError: invalid syntax

Ошибки в программе бывают разные и каждой нужен свой особый подход. Первым делом внимательно посмотрите на вывод программы в консоль. На последней строчке написано SyntaxError: invalid syntax. Если эти слова вам не знакомы, то обратитесь за переводом к Яндекс.Переводчику:

SyntaxError: недопустимый синтаксис
SyntaxError: неверный синтаксис

Первое слово SyntaxError Яндекс не понял. Помогите ему и разделите слова пробелом:

Syntax Error: invalid syntax
Синтаксическая ошибка: неверный синтаксис

Теория. Синтаксические ошибки

Программирование — это не магия, а Python — не волшебный шар. Он не умеет предсказывать будущее, у него нет доступа к секретным знаниями, это просто автомат, это программа. Узнайте как она работает, как ищет ошибки в коде, и тогда легко найдете эффективный способ отладки. Вся необходимая теория собрана в этом разделе, дочитайте до конца.

SyntaxError — это синтаксическая ошибка. Она случается очень рано, еще до того, как Python запустит программу. Вот что делает компьютер, когда вы запускаете скрипт командой python script.py:

1. запускает программу python
2. python считывает текст из файла script.py
3. python превращает текст программы в инструкции
4. python исполняет инструкции

Синтаксическая ошибка SyntaxError возникает на четвёртом этапе в момент, когда Python разбирает текст программы на понятные ему компоненты. Сложные выражения в коде он разбирает на простейшие инструкции. Вот пример кода и инструкции для него:

person = {'name': 'Евгений'}

Инструкции:

1. создать строку 'Евгений'
2. создать словарь
3. в словарь добавить ключ 'name' со значением 'Евгений'
4. присвоить результат переменной person

SyntaxError случается когда Python не смог разбить сложный код на простые инструкции. Зная это, вы можете вручную разбить код на инструкции, чтобы затем проверить каждую из них по отдельности. Ошибка прячется в одной из инструкций.

1. Найдите поломанное выражение

Этот шаг сэкономит вам кучу сил. Найдите в программе сломанный участок кода. Его вам предстоит разобрать на отдельные инструкции. Посмотрите на вывод программы в консоль:

$ python script.py
  File "script.py", line 9
    last_name = last_name
            ^
SyntaxError: invalid syntax

Вторая строчка сообщает: File "script.py", line 9 — ошибка в файле script.py на девятой строчке. Но эта строка является частью более сложного выражения, посмотрите на него целиком:

label = 'Имя ученика: {first_name} {last_name}'.format(
    first_name = first_name
    last_name = last_name
)

«Девман» — авторская методика обучения программированию. Готовим к работе крутых программистов на Python. Станьте программистом, пройдите продвинутый курс Python.

2. Разбейте выражение на инструкции

В прошлых шагах вы узнали что сломан этот фрагмент кода:

label = 'Имя ученика: {first_name} {last_name}'.format(
    first_name = first_name
    last_name = last_name
)

Разберите его на инструкции:

1. создать строку 'Имя ученика: {first_name} {last_name}'
2. получить у строки метод format
3. вызвать функцию с двумя аргументами
4. результат присвоить переменной label

Так выделил бы инструкции программист, но вот Python сделать так не смог и сломался. Пора выяснить на какой инструкции нашла коса на камень.

Теперь ваша задача переписать код так, чтобы в каждой строке программы исполнялось не более одной инструкции из списка выше. Так вы сможете тестировать их по отдельности и облегчите себе задачу. Так выглядит отделение инструкции по созданию строки:

# 1. создать строку
template = 'Имя ученика: {first_name} {last_name}'

label = template.format(
    first_name = first_name
    last_name = last_name
)

Сразу запустите код, проверьте что ошибка осталась на прежнему месте. Приступайте ко второй инструкции:

# 1. создать строку
template = 'Имя ученика: {first_name} {last_name}'

# 2. получить у строки метод
format = template.format

label = format(
    first_name = first_name
    last_name = last_name
)

Строка format = template.format создает новую переменную format и кладёт в неё функцию. Да, да, это не ошибка! Python разрешает класть в переменные всё что угодно, в том числе и функции. Новая переменная переменная format теперь работает как обычная функция, и её можно вызвать: format(...).

Снова запустите код. Ошибка появится внутри format. Под сомнением остались две инструкции:

1. вызвать функцию с двумя аргументами
2. результат присвоить переменной label

Скорее всего, Python не распознал вызов функции. Проверьте это, избавьтесь от последней инструкции — от создания переменной label:

# 1. создать строку
template = 'Имя ученика: {first_name} {last_name}'

# 2. получить у строки метод
format = template.format

# 3. вызвать функцию
format(
    first_name = first_name
    last_name = last_name
)

Запустите код. Ошибка снова там же — внутри format. Выходит, код вызова функции написан с ошибкой, Python не смог его превратить в инструкцию.

3. Проверьте синтаксис вызова функции

Теперь вы знаете что проблема в коде, вызывающем функцию. Можно помедитировать еще немного над кодом программы, пройтись по нему зорким взглядом еще разок в надежде на лучшее. А можно поискать в сети примеры кода для сравнения.

Запросите у Яндекса статьи по фразе “Python синтаксис функции”, а в них поищите код, похожий на вызов format и сравните. Вот одна из первых статей в поисковой выдаче:

• Функции в Python

Уверен, теперь вы нашли ошибку. Победа!

Working with files makes your programs more relevant and usable, also it makes your programs quickly analyze lots of data.

Learning to work with files and save data will make your programs easier for people to use. Users will be able to choose what data to enter and when to enter it. People can run your program, do some work, and then close the program and pick up where they left off later. Learning to handle exceptions will help you deal with situations in which files don’t exist and deal with other problems that can cause your programs to crash. This will make your programs more robust when they encounter bad data, whether it comes from innocent mistakes or from malicious attempts to break your programs. With these skills, you’ll make your programs more applicable, usable, and stable.

Reading from a File

An incredible amount of data is available in text files. Text files can contain weather data, traffic data, socioeconomic data, literary works, and more. Reading from a file is particularly useful in data analysis applications, but it’s also applicable to any situation in which you want to analyze or modify information stored in a file. For example, you can write a program that reads in the contents of a text file and rewrites the file with formatting that allows a browser to display it.

When you want to work with the information in a text file, the first step is to read the file into memory. You can read the entire contents of a file, or you can work through the file one line at a time.

Reading an Entire File

To begin, we need a file with a few lines of text in it. Let’s start with a file that contains pi to 30 decimal places, with 10 decimal places per line, consider we have a text file (pi_digits. txt) in the same directory of your program:

3.1415926535
  8979323846
  2643383279

Here’s a program that opens this file, reads it, and prints the contents of the file to the screen:

with open('pi_digits.txt') as file_object:
    contents = file_object.read()

print(contents)

The first line of this program with open('pi_digits.txt') as file_object: has a lot going on. Let’s start by looking at the open() function. To do any work with a file, even just printing its contents, you first need to open the file to access it. The open() function needs one argument: the name of the file you want to open. Python looks for this file in the directory where the program that’s currently being executed is stored.

Here, open('pi_digits.txt') returns an object representing pi_digits.txt. Python assigns this object to file_object, which we’ll work with later in the program.

The keyword with closes the file once access to it is no longer needed. Notice how we call open() in this program but not close(). You could open and close the file by calling open() and close(), but if a bug in your program prevents the close() method from being executed, the file may never close. This may seem trivial, but improperly closed files can cause data to be lost or corrupted. And if you call close() too early in your program, you’ll find yourself trying to work with a closed file (a file you can’t access), which leads to more errors. It’s not always easy to know exactly when you should close a file, but with the structure shown here, Python will figure that out for you. All you have to do is open the file and work with it as desired, trusting that Python will close it automatically when the with block finishes execution.

Once we have a file object representing pi_digits.txt, we use the read() method in the second line of our program contents = file_object.read() to read the entire contents of the file and store it as one long string in contents. When we print the value of contents, we get the entire text file back.

If you find a blank line appears at the end of your output that’s because read() returns an empty string when it reaches the end of the file; this empty string shows up as a blank line. If you want to remove the extra blank line, you can use rstrip() in the call to print().

print(contents.rstrip())

File Paths

When you pass a simple filename like pi_digits.txt to the open() function, Python looks in the directory where the file that’s currently being executed (that is, your . py program file) is stored.

Sometimes, depending on how you organize your work, the file you want to open won’t be in the same directory as your program file. For example, you might store your program files in a folder called python_work; inside python_work, you might have another folder called text_files to distinguish your program files from the text files they’re manipulating. Even though text_files is in python_work, just passing open()*the name of a file in *text_files won’t work, because Python will only look in python_work and stop there; it won’t go on and look in text_files.

To get Python to open files from a directory other than the one where your program file is stored, you need to provide a file path, which tells Python to look in a specific location on your system.

Because text_files is inside python_work, you could use a relative file path to open a file from text_files. A relative file path tells Python to look for a given location relative to the directory where the currently running program file is stored. For example, you’d write:

with open('text_files/filename.txt') as file_object:

This line tells Python to look for the desired . txt file in the folder text_files and assumes that text_files is located inside python_work.

Please note that, Windows systems use a backslash ( ) instead of a forward slash ( / ) when displaying file paths, but you can still use forward slashes in your code.

You can also tell Python exactly where the file is on your computer regardless of where the program that’s being executed is stored. This is called an absolute file path. You use an absolute path if a relative path doesn’t work. For instance, if you’ve put text_files in some folder other than python_work—say, a folder called other_files—then just passing open() the path ‘text_files/filename.txt’ won’t work because Python will only look for that location inside python_work. You’ll need to write out a full path to clarify where you want Python to look.

Absolute paths are usually longer than relative paths, so it’s helpful to assign them to a variable and then pass that variable to open():

file_path = '/home/ahmed/other_files/text_files/filename.txt'
with open(file_path) as file_object:

Using absolute paths, you can read files from any location on your system. For now it’s easiest to store files in the same directory as your program files or in a folder such as text_files within the directory that stores your program files.

Please note that, if you try to use backslashes in a file path, you’ll get an error because the backslash is used to escape characters in strings. For example, in the path C:pathtofile.txt, the sequence t is interpreted as a tab. If you need to use backslashes, you can escape each one in the path, like this: C:pathtofile.txt.

Reading Line by Line

When you’re reading a file, you’ll often want to examine each line of the file. You might be looking for certain information in the file, or you might want to modify the text in the file in some way. For example, you might want to read through a file of weather data and work with any line that includes the word sunny in the description of that day’s weather. In a news report, you might look for any line with the tag <headline> and rewrite that line with a specific kind of formatting.

You can use a for loop on the file object to examine each line from a file one at a time:

file_name = 'pi_digits.txt'

with open(file_name) as file_object:
    for line in file_object:
        print(line)

3.1415926535

  8979323846

  2643383279

At file_name = 'pi_digits.txt' we assign the name of the file we’re reading from to the variable filename. This is a common convention when working with files. Because the variable filename doesn’t represent the actual file—it’s just a string telling Python where to find the file—you can easily swap out ‘pi_digits. txt’ for the name of another file you want to work with.

After we call open(), an object representing the file and its contents is assigned to the variable
file_object. We again use the with syntax to let Python open and close the file properly. To examine the file’s contents, we work through each line in the file by looping over the file object.

When we print each line, we find even more blank lines. These blank lines appear because an invisible newline character is at the end of each line in the text file. The print function adds its own newline each time we call it, so we end up with two newline characters at the end of each line: one from the file and one from print(). Using rstrip() on each line in the print() call eliminates these extra blank lines.

file_name = 'pi_digits.txt'

with open(file_name) as file_object:
    for line in file_object:
        print(line.rstrip())

3.1415926535
  8979323846
  2643383279

Making a List of Lines from a File

When you use with, the file object returned by open() is only available inside the with block that contains it. If you want to retain access to a file’s contents outside the with block, you can store the file’s lines in a list inside the block and then work with that list. You can process parts of the file immediately and postpone some processing for later in the program.

The following example stores the lines of pi_digits. txt in a list inside the with block and then prints the lines outside the with block:

file_name = 'pi_digits.txt'

with open(file_name) as object_file:
    lines = object_file.readlines()

for line in lines:
    print(line.rstrip())

3.1415926535
  8979323846
  2643383279

At lines = object_file.readlines() the readlines() method takes each line from the file and stores it in a list. This list is then assigned to lines, which we can continue to work with after the with block ends.

At for line in lines: we use a simple for loop to print each line from lines. Because each item in lines corresponds to each line in the file, the output matches the contents of the file exactly.

Working with a File’s Contents

After you’ve read a file into memory, you can do whatever you want with that data, so let’s briefly explore the digits of pi. First, we’ll attempt to build a single string containing all the digits in the file with no whitespace in it:

file_name = 'pi_digits.txt'

with open(file_name) as object_file:
    lines = object_file.readlines()

pi_string = ''
for line in lines:
    pi_string += line.rstrip()

print(pi_string)
print(len(pi_string))

3.1415926535  8979323846  2643383279
36

We start by opening the file and storing each line of digits in a list, just as we did in the previous example. At pi_string = '' we create a variable, pi_string, to hold the digits of pi. We then create a loop that adds each line of digits to pi_string and removes the newline character from each line pi_string += line.rstrip().

The variable pi_string contains the whitespace that was on the left side of the digits in each line, but we can get rid of that by using strip() instead of rstrip():

--snip--

for line in lines:
    pi_string += line.strip()

print(pi_string)
print(len(pi_string))

3.141592653589793238462643383279
32

Now we have a string containing pi to 30 decimal places. The string is 32 characters long because it also includes the leading 3 and a decimal point.

Please note that, When Python reads from a text file, it interprets all text in the file as a string. If you read in a number and want to work with that value in a numerical context, you’ll have to convert it to an integer using the int() function or convert it to a float using the float() function.

Large Files: One Million Digits

So far we’ve focused on analyzing a text file that contains only three lines, but the code in these examples would work just as well on much larger files. If we start with a text file that contains pi to 1,000,000 decimal places instead of just 30, we can create a single string containing all these digits. We don’t need to change our program at all except to pass it a different file. We’ll also print just the first 50 decimal places, so we don’t have to watch a million digits scroll by in the terminal:

filename = 'pi_million_digits.txt'

with open(filename) as file_object:
    lines = file_object.readlines()

pi_string = ''
for line in lines:
    pi_string += line.strip()

print(f"{pi_string[:52]}...")
print(len(pi_string))

3.14159265358979323846264338327950288419716939937510...
1000002

The output shows that we do indeed have a string containing pi to 1,000,000 decimal places.

Python has no inherent limit to how much data you can work with; you can work with as much data as your system’s memory can handle.

Is Your Birthday Contained in Pi?

Let’s use the program we just wrote to find out if someone’s birthday appears anywhere in the first million digits of pi. We can do this by expressing each birthday as a string of digits and seeing if that string appears anywhere in pi_string:

filename = 'pi_digits.txt'

with open(filename) as object_file:
    lines = object_file.readlines()

pi_string = ''
for line in lines:
    pi_string += line.strip()

birthday = input("Enter your birthday, in the form mmddyy: ")
if birthday in pi_string:
    print("Your birthday appears in the first million digits of pi!")
else:
    print("Your birthday does not appear in the first million digits of pi.")

Once you’ve read from a file, you can analyze its contents in just about any way you can imagine.

Writing to a File

One of the simplest ways to save data is to write it to a file. When you write text to a file, the output will still be available after you close the terminal containing your program’s output. You can examine output after a program finishes running, and you can share the output files with others as well. You can also write programs that read the text back into memory and work with it again later.

Writing to an Empty File

To write text to a file, you need to call open() with a second argument telling Python that you want to write to the file. To see how this works, let’s write a simple message and store it in a file instead of printing it to the screen:

filename = 'programming.txt'

with open(filename, 'w') as file_object:
    file_object.write("I Love Programming.")

The call to open() in this example has two arguments. The first argument is still the name of the file we want to open. The second argument, ‘w’, tells Python that we want to open the file in write mode.

You can open a file in:

• read mode (‘r’)
• write mode (‘w’)
• append mode (‘a’)
• a mode that allows you to read and write to the file (‘r+’)

If you omit the mode argument, Python opens the file in read-only mode by default.

The open() function automatically creates the file you’re writing to if it doesn’t already exist. However, be careful opening a file in write mode (‘w’) because if the file does exist, Python will erase the contents of the file before returning the file object.

At file_object.write("I Love Programming.") we use the write() method on the file object to write a string to the file. This program has no terminal output, but if you open the file (programming. txt), you’ll see one line.

I love programming.

This file behaves like any other file on your computer. You can open it, write new text in it, copy from it, paste to it, and so forth.

Python can only write strings to a text file. If you want to store numerical data in a text file, you’ll have to convert the data to string format first using the str() function.

Writing Multiple Lines

The write() function doesn’t add any newlines to the text you write. So if you write more than one line without including newline characters, your file may not look the way you want it to:

filename = 'programming.txt'

with open(filename, 'w') as file_object:
    file_object.write("I love programming.")
    file_object.write("I love creating new games.")

If you open (programming. txt), you’ll see the two lines squished together:

I love programming.I love creating new games.

Including newlines in your calls to write() makes each string appear on its own line:

filename = 'programming.txt'

with open(filename, 'w') as file_object:
    file_object.write("I Love Programming.n")
    file_object.write("I love creating new games.n")

I love programming.
I love creating new games.

You can also use spaces, tab characters, and blank lines to format your output, just as you’ve been doing with terminal-based output.

Appending to a File

If you want to add content to a file instead of writing over existing content, you can open the file in append mode. When you open a file in append mode, Python doesn’t erase the contents of the file before returning the file object. Any lines you write to the file will be added at the end of the file. If the file doesn’t exist yet, Python will create an empty file for you.

Let’s modify last program by adding some new reasons we love programming to the existing file (programming. txt):

filename = 'programming.txt'

with open(filename, 'a') as file_object:
    file_object.write("I also love finding meaning in large datasets.n")
    file_object.write("I love creating apps that can run in a browser.n")

At with open(filename, 'a') as file_object: we use the ‘a’ argument to open the file for appending rather
than writing over the existing file. Then we write two new lines, which are added to (programming. txt).

I love programming.
I love creating new games.
I also love finding meaning in large datasets.
I love creating apps that can run in a browser.

We end up with the original contents of the file, followed by the new content we just added.

Exceptions

Python uses special objects called exceptions to manage errors that arise during a program’s execution. Whenever an error occurs that makes Python unsure what to do next, it creates an exception object. If you write code that handles the exception, the program will continue running. If you don’t handle the exception, the program will halt and show a traceback, which includes a report of the exception that was raised.

Exceptions are handled with try-except blocks. A try-except block asks Python to do something, but it also tells Python what to do if an exception is raised. When you use try-except blocks, your programs will continue running even if things start to go wrong. Instead of tracebacks, which can be confusing for users to read, users will see friendly error messages that you write.

Handling the ZeroDivisionError Exception

Let’s look at a simple error that causes Python to raise an exception. You probably know that it’s impossible to divide a number by zero, but let’s ask Python to do it anyway:

print(5/0)

ZeroDivisionError: division by zero

Of course Python can’t do this, so we get a traceback. The error reported in the traceback ZeroDivisionError, is an exception object. Python creates this kind of object in response to a situation where it can’t do what we ask it to. When this happens, Python stops the program and tells us the kind of exception that was raised. We can use this information to modify our program. We’ll tell Python what to do when this kind of exception occurs; that way, if it happens again, we’re prepared.

Using try-except Blocks

When you think an error may occur, you can write a try-except block to handle the exception that might be raised. You tell Python to try running some code, and you tell it what to do if the code results in a particular kind of exception.

Here’s what a try-except block for handling the ZeroDivisionError exception looks like:

try:
    print(5/0)
except ZeroDivisionError:
    print("You can't divide by zero!")

We put print(5/0), the line that caused the error, inside a try block. If the code in a try block works, Python skips over the except block. If the code in the try block causes an error, Python looks for an except block whose error matches the one that was raised and runs the code in that block.

In this example, the code in the try block produces a ZeroDivisionError, so Python looks for an except block telling it how to respond. Python then runs the code in that block, and the user sees a friendly error message instead of a traceback:

You can't divide by zero!

If more code followed the try-except block, the program would continue running because we told Python how to handle the error. Let’s look at an example where catching an error can allow a program to continue running.

Using Exceptions to Prevent Crashes

Handling errors correctly is especially important when the program has more work to do after the error occurs. This happens often in programs that prompt users for input. If the program responds to invalid input appropriately, it can prompt for more valid input instead of crashing.

Let’s create a simple calculator that does only division:

while True:
    first_number = input("nFirst Number: ")
    if first_number == 'q':
        break

    second_number = input("Second Number: ")
    if second_number == 'q':
        break

    answer = int(first_number) / int(second_number)
    print(answer)

This program prompts the user to input a first_number and, if the user does not enter ‘q’ to quit, a second_number. We then divide these two numbers to get an answer w. This program does nothing to handle errors, so asking it to divide by zero causes it to crash:

Give me two numbers, and I'll divide them.
Enter 'q' to quit.

First Number: 10
Second Number: 5
2.0

First Number: 5
Second Number: 0
Traceback (most recent call last):
  File "division_calculator.py", line 13, in <module>
    answer = int(first_number) / int(second_number)
ZeroDivisionError: division by zero

It’s bad that the program crashed, but it’s also not a good idea to let users see tracebacks. Nontechnical users will be confused by them, and in a malicious setting, attackers will learn more than you want them to know from a traceback. For example, they’ll know the name of your program file, and they’ll see a part of your code that isn’t working properly. A skilled attacker can sometimes use this information to determine which kind of attacks to use against your code.

The else Block

We can make this program more error resistant by wrapping the line that might produce errors in a try-except block. The error occurs on the line that performs the division, so that’s where we’ll put the try-except block. This example also includes an else block. Any code that depends on the try block executing successfully goes in the else block:

print("Give me two numbers, and I'll divide them.")
print("Enter 'q' to quit.")

while True:
    first_number = input("nFirst Number: ")
    if first_number == 'q':
        break

    second_number = input("Second Number: ")
    if second_number == 'q':
        break

    try:
        answer = int(first_number) / int(second_number)
    except ZeroDivisionError:
        print("You can't divide by 0!")
    else:
        print(answer)

Give me two numbers, and I'll divide them.
Enter 'q' to quit.

First Number: 10
Second Number: 5
2.0

First Number: 5
Second Number: 0
You can't divide by 0!

First Number: q

We ask Python to try to complete the division operation in a try block, which includes only the code that might cause an error. Any code that depends on the try block succeeding is added to the else block. In this case if the division operation is successful, we use the else block to print the result.

The except block tells Python how to respond when a ZeroDivisionError arises. If the try block doesn’t succeed because of a division by zero error, we print a friendly message telling the user how to avoid this kind of error. The program continues to run, and the user never sees a traceback.

The try-except-else block works like this: Python attempts to run the code in the try block. The only code that should go in a try block is code that might cause an exception to be raised. Sometimes you’ll have additional code that should run only if the try block was successful; this code goes in the else block. The except block tells Python what to do in case a certain exception arises when it tries to run the code in the try block.

By anticipating likely sources of errors, you can write robust programs that continue to run even when they encounter invalid data and missing resources. Your code will be resistant to innocent user mistakes and malicious attacks.

Handling the FileNotFoundError Exception

One common issue when working with files is handling missing files. The file you’re looking for might be in a different location, the filename may be misspelled, or the file may not exist at all. You can handle all of these situations in a straightforward way with a try-except block.

Let’s try to read a file that doesn’t exist. The following program tries to read in the contents of A*lice in Wonderland*, but we haven’t saved the file (alice. txt) in the same directory as (alice. py):

filename = 'alice.txt'

with open(filename, encoding='utf-8') as f:
    contents = f.read()

There are two changes here. One is the use of the variable f to represent the file object, which is a common convention. The second is the use of the encoding argument. This argument is needed when your system’s default encoding doesn’t match the encoding of the file that’s being read.

Python can’t read from a missing file, so it raises an exception:

Traceback (most recent call last):
File "alice.py", line 3, in <module>
with open(filename, encoding='utf-8') as f:
FileNotFoundError: [Errno 2] No such file or directory: 'alice.txt'

The last line of the traceback reports a FileNotFoundError: this is the exception Python creates when it can’t find the file it’s trying to open.

In this example, the open() function produces the error, so to handle it, the try block will begin with the line that contains open():

filename = 'alice.txt'

try:
    with open(filename, encoding='utf-8') as f:
        contents = f.read()
except FileNotFoundError:
    print(f"Sorry, the file {filename} does not exist.")

In this example, the code in the try block produces a FileNotFoundError, so Python looks for an except block that matches that error. Python then runs the code in that block, and the result is a friendly error message instead of a traceback:

Sorry, the file alice.txt does not exist.

The program has nothing more to do if the file doesn’t exist, so the error-handling code doesn’t add much to this program. Let’s build on this example and see how exception handling can help when you’re working with more than one file.

Analyzing Text

You can analyze text files containing entire books. Many classic works of literature are available as simple text files because they are in the public domain. The texts used in this section come from Project Gutenberg (http://gutenberg.org/). Project Gutenberg maintains a collection of literary works that are available in the public domain, and it’s a great resource if you’re interested in working with literary texts in your programming projects.

Let’s pull in the text of Alice in Wonderland and try to count the number of words in the text. We’ll use the string method split(), which can build a list of words from a string. Here’s what split() does with a string containing just the title «Alice in Wonderland»:

>>> title = "Alice in Wonderland"
>>> title.split()
['Alice', 'in', 'Wonderland']

The split() method separates a string into parts wherever it finds a space and stores all the parts of the string in a list. The result is a list of words from the string, although some punctuation may also appear with some of the words. To count the number of words in Alice in Wonderland, we’ll use split() on the entire text. Then we’ll count the items in the list to get a rough idea of the number of words in the text:

filename = 'alice.txt'

try:
    with open(filename, encoding='utf-8') as f:
        contents = f.read()
except FileNotFoundError:
    print(f"Sorry, the file {filename} does not exist.")
else:
    # Count the approximate number of words in the file.
    words = contents.split()
    num_words = len(words)
    print(f"The file {filename} has about {num_words} words.")

Move the file (alice. txt) to the correct directory, so the try block will work this time. At words = contents.split() we take the string contents, which now contains the entire text of Alice in Wonderland as one long string, and use the split() method to produce a list of all the words in the book. When we use len() on this list to examine its length, we get a good approximation of the number of words in the original string num_words = len(words).

Then we print a statement that reports how many words were found in the file. This code is placed in the else block because it will work only if the code in the try block was executed successfully. The output tells us how many words are in (alice. txt):

The file alice.txt has about 29465 words.

The count is a little high because extra information is provided by the publisher in the text file used here, but it’s a good approximation of the length of Alice in Wonderland.

Working with Multiple Files

Let’s add more books to analyze. But before we do, let’s move the bulk of this program to a function called count_words(). By doing so, it will be easier to run the analysis for multiple books:

def count_words(filename):
    """Count the approximate number of words in a file."""
    try:
        with open(filename, encoding='utf-8') as f:
            contents = f.read()
    except FileNotFoundError:
        print(f"Sorry, the file {filename} does not exist.")
    else:
        words = contents.split()
        num_words = len(words)
        print(f"The file {filename} has about {num_words} words.")

Most of this code is unchanged. We simply indented it and moved it into the body of count_words(). It’s a good habit to keep comments up to date when you’re modifying a program, so we changed the comment to a docstring and reworded it slightly.

Now we can write a simple loop to count the words in any text we want to analyze. We do this by storing the names of the files we want to analyze in a list, and then we call count_words() for each file in the list.

def count_words(filename):
    --snip--

filenames = ['alice.txt', 'siddhartha.txt', 'moby_dick.txt', 'little_women.txt']
for filename in filenames:
    count_words(filename)

The file alice.txt has about 29465 words.
Sorry, the file siddhartha.txt does not exist.
The file moby_dick.txt has about 215830 words.
The file little_women.txt has about 189079 words.

The siddhartha. txt file is missed from the directory but it has no effect on the rest of the program’s execution.

Using the try-except block in this example provides two significant advantages:

• We prevent our users from seeing a traceback.
• we let the program continue analyzing the texts it’s able to find.

If we don’t catch the FileNotFoundError that ‘siddhartha. txt’ raised, the user would see a full traceback, and the program would stop running after trying to analyze Siddhartha. It would never analyze Moby Dick or Little Women.

Failing Silently

In the previous example, we informed our users that one of the files was unavailable. But you don’t need to report every exception you catch. Sometimes you’ll want the program to fail silently when an exception occurs and continue on as if nothing happened. To make a program fail silently, you write a try block as usual, but you explicitly tell Python to do nothing in the except block. Python has a pass statement that tells it to do nothing in a block:

def count_words(filename):
"""Count the approximate number of words in a file."""
try:
    --snip--
except FileNotFoundError:
    pass
else:
    --snip--

filenames = ['alice.txt', 'siddhartha.txt', 'moby_dick.txt', 'little_women.txt']
for filename in filenames:
    count_words(filename)

The only difference between this listing and the previous one is the pass statement. Now when a FileNotFoundError is raised, the code in the except block runs, but nothing happens. No traceback is produced, and there’s no output in response to the error that was raised. Users see the word counts for each file that exists, but they don’t see any indication that a file wasn’t found.

The file alice.txt has about 29465 words.
The file moby_dick.txt has about 215830 words.
The file little_women.txt has about 189079 words.

The pass statement also acts as a placeholder. It’s a reminder that you’re choosing to do nothing at a specific point in your program’s execution and that you might want to do something there later. For example, in this program we might decide to write any missing filenames to a file called (missing_files. txt). Our users wouldn’t see this file, but we’d be able to read the file and deal with any missing texts.

Deciding Which Errors to Report

How do you know when to report an error to your users and when to fail silently? If users know which texts are supposed to be analyzed, they might appreciate a message informing them why some texts were not analyzed. If users expect to see some results but don’t know which books are supposed to be analyzed, they might not need to know that some texts were unavailable. Giving users information they aren’t looking for can decrease the usability of your program. Python’s error-handling structures give you fine-grained control over how much to share with users when things go wrong; it’s up to you to decide how much information to share.

Well-written, properly tested code is not very prone to internal errors, such as syntax or logical errors. But every time your program depends on something external, such as user input, the existence of a file, or the availability of a network connection, there is a possibility of an exception being raised. A little experience will help you know where to include exception handling blocks in your program and how much to report to users about errors that arise.

Storing Data

Many of your programs will ask users to input certain kinds of information. You might allow users to store preferences in a game or provide data for a visualization. Whatever the focus of your program is, you’ll store the information users provide in data structures such as lists and dictionaries. When users close a program, you’ll almost always want to save the information they entered. A simple way to do this involves storing your data using the json module.

The json module allows you to dump simple Python data structures into a file and load the data from that file the next time the program runs. You can also use json to share data between different Python programs. Even better, the JSON data format is not specific to Python, so you can share data you store in the JSON format with people who work in many other programming languages. It’s a useful and portable format, and it’s easy to learn.

The **JSON* (JavaScript Object Notation) format was originally developed for JavaScript. However, it has since become a common format used by many languages, including Python.*

Using json.dump() and json.load()

Let’s write a short program that stores a set of numbers and another program that reads these numbers back into memory. The first program will use json.dump() to store the set of numbers, and the second program will use json.load().

The json.dump() function takes two arguments: a piece of data to store and a file object it can use to store the data. Here’s how you can use json.dump() to store a list of numbers:

import json

numbers = [1, 2, 3, 4, 5, 10, 11, 15]

filename = 'numbers.json'
with open(filename, 'w') as f:
    json.dump(numbers, f)

We first import the json module and then create a list of numbers to work with. At filename = 'numbers.json' we choose a filename in which to store the list of numbers. It’s customary to use the file extension .json to indicate that the data in the file is stored in the JSON format. Then we open the file in write mode, which allows json to write the data to the file. At json.dump(numbers, f) we use the json.dump() function to store the list numbers in the file (numbers. json).

This program has no output, but let’s open the file (numbers. json) and look at it. The data is stored in a format that looks just like Python:

[1, 2, 3, 4, 5, 10, 11, 15]

Now we’ll write a program that uses json.load() to read the list back into memory:

import json

filename = 'numbers.json'
with open(filename) as f:
    numbers = json.load(f)

print(numbers)

[1, 2, 3, 4, 5, 10, 11, 15]

At filename = 'numbers.json' we make sure to read from the same file we wrote to. This time when we open the file, we open it in read mode because Python only needs to read from the file. At numbers = json.load(f) we use the json.load() function to load the information stored in (numbers. json), and we assign it to the variable numbers. Finally we print the recovered list of numbers and see that it’s the same list created before.

This is a simple way to share data between two programs.

Saving and Reading User-Generated Data

Saving data with json is useful when you’re working with user-generated data, because if you don’t store your user’s information somehow, you’ll lose it when the program stops running. Let’s look at an example where we prompt the user for their name the first time they run a program and then remember their name when they run the program again.

Let’s start by storing the user’s name:

import json

username = input("What is you name? ")

filename = 'username.json'
with open(filename, 'w') as f:
    json.dump(username, f)
    print(f"We'll remember you when you come back, {username}!")

What is you name? Ahmed
We'll remember you when you come back, Ahmed!

Now let’s write a new program that greets a user whose name has already been stored:

import json

filename = 'username.json'
with open(filename) as f:
    username = json.load(f)
    print(f"Welcome back, {username}!")

Welcome back, Ahmed!

We need to combine these two programs into one file. When someone runs remember_me. py, we want to retrieve their username from memory if possible; therefore, we’ll start with a try block that attempts to recover the username. If the file (username. json) doesn’t exist, we’ll have the except block prompt for a username and store it in (username. json) for next time:

import json

# Load the username, if it has been stored previously.
# Otherwise, prompt for the username and store it.
filename = 'username.json'
try:
    with open(filename) as f:
        username = json.load(f)
except FileNotFoundError:
    username = input("What is your name? ")
    with open(filename, 'w') as f:
        json.dump(username, f)
        print(f"We'll remember you when you come back, {username}!")
else:
    print(f"Welcome back, {username}!")

There’s no new code here; blocks of code from the last two examples are just combined into one file. Whichever block executes, the result is a username and an appropriate greeting. If this is the first time the program runs, this is the output:

What is you name? Ahmed
We'll remember you when you come back, Ahmed!

Otherwise:

Welcome back, Ahmed!

This is the output you see if the program was already run at least once.

Refactoring

Often, you’ll come to a point where your code will work, but you’ll recognize that you could improve the code by breaking it up into a series of functions that have specific jobs. This process is called refactoring. Refactoring makes your code cleaner, easier to understand, and easier to extend.

We can refactor remember_me. py by moving the bulk of its logic into one or more functions. The focus of remember_me. py is on greeting the user, so let’s move all of our existing code into a function called greet_user():

import json

def greet_user():
    """Greet the user by name."""
    filename = 'username.json'
    try:
        with open(filename) as f:
            username = json.load(f)
    except FileNotFoundError:
        username = input("What is your name? ")
        with open(filename, 'w') as f:
            json.dump(username, f)
            print(f"We'll remember you when you come back, {username}!")
    else:
        print(f"Welcome back, {username}!")

greet_user()

Because we’re using a function now, we update the comments with a docstring that reflects how the program currently works. This file is a little cleaner, but the function greet_user() is doing more than just greeting the user—it’s also retrieving a stored username if one exists and prompting for a new username if one doesn’t exist.

Let’s refactor greet_user() so it’s not doing so many different tasks. We’ll start by moving the code for retrieving a stored username to a separate function:

import json

def get_stored_username():
    """Get stored username if available."""
    filename = 'username.json'
    try:
        with open(filename) as f:
            username = json.load(f)
    except:
        return None
    else:
        return username

def greet_user():
    """Greet the user by name."""
    username = get_stored_username()
    if username:
        print(f"Welcome back, {username}!")
    else:
        username = input("What is your name? ")
        filename = 'username.json'
        with open(filename, 'w') as f:
            json.dump(username, f)
            print(f"We'll remember you when you come back, {username}!")

greet_user()

The new function get_stored_username() has a clear purpose, as stated in the docstring. This function retrieves a stored username and returns the username if it finds one. If the file (username. json) doesn’t exist, the function returns None. This is good practice: a function should either return the value you’re expecting, or it should return None. This allows us to perform a simple test with the return value of the function.

At if username: we print a welcome back message to the user if the attempt to retrieve a username was successful, and if it doesn’t, we prompt for a new username.

We should refactor one more block of code out of greet_user(). If the username doesn’t exist, we should move the code that prompts for a new username to a function dedicated to that purpose:

import json

def get_stored_username():
    """Get stored username if available."""
    filename = 'username.json'
    try:
        with open(filename) as f:
            username = json.load(f)
    except:
        return None
    else:
        return username

def get_new_username():
    """Prompt for a new username."""
    username = input("What is your name? ")
    filename = 'username.json'
    with open(filename, 'w') as f:
        json.dump(username, f)
    return username

def greet_user():
    """Greet the user by name."""
    username = get_stored_username()
    if username:
        print(f"Welcome back, {username}!")
    else:
        username = get_new_username()
        print(f"We'll remember you when you come back, {username}!")

greet_user()

Each function in this final version has a single, clear purpose. Each function in this final version of remember_me.py has a single, clear purpose. We call greet_user(), and that function prints an appropriate message: it either welcomes back an existing user or greets a new user. It does this by calling get_stored_username(), which is responsible only for retrieving a stored username if one exists. Finally, greet_user() calls get_new_username() if necessary, which is responsible only for getting a new username and storing it. This compartmentalization of work is an essential part of writing clear code that will be easy to maintain and extend.