Def invalid syntax python ошибка

Ситуация: программист взял в работу математический проект — ему нужно написать код, который будет считать функции и выводить результаты. В задании написано:

«Пусть у нас есть функция f(x,y) = xy, которая перемножает два аргумента и возвращает полученное значение».

Программист садится и пишет код:

a = 10
b = 15
result = 0
def fun(x,y): 
    return x y
result = fun(a,b)
print(result)

Но при выполнении такого кода компьютер выдаёт ошибку:

File "main.py", line 13
result = x y
^
❌ SyntaxError: invalid syntax

Почему так происходит: в каждом языке программирования есть свой синтаксис — правила написания и оформления команд. В Python тоже есть свой синтаксис, по которому для умножения нельзя просто поставить рядом две переменных, как в математике. Интерпретатор находит первую переменную и думает, что ему сейчас объяснят, что с ней делать. Но вместо этого он сразу находит вторую переменную. Интерпретатор не знает, как именно нужно их обработать, потому что у него нет правила «Если две переменные стоят рядом, их нужно перемножить». Поэтому интерпретатор останавливается и говорит, что у него лапки. 

Что делать с ошибкой SyntaxError: invalid syntax

В нашем случае достаточно поставить звёздочку (знак умножения в Python) между переменными — это оператор умножения, который Python знает:

a = 10
b = 15
result = 0
def fun(x,y): 
    return x * y
result = fun(a,b)
print(result)

В общем случае найти источник ошибки SyntaxError: invalid syntax можно так:

  1. Проверьте, не идут ли у вас две команды на одной строке друг за другом.
  2. Найдите в справочнике описание команды, которую вы хотите выполнить. Возможно, где-то опечатка.
  3. Проверьте, не пропущена ли команда на месте ошибки.

Практика

Попробуйте найти ошибки в этих фрагментах кода:

x = 10 y = 15
def fun(x,y): 
    return x * y
try:  
    a = 100
    b = "PythonRu"
    assert a = b
except AssertionError:  
    print("Исключение AssertionError.")
else:  
    print("Успех, нет ошибок!")

Вёрстка:

Кирилл Климентьев

The error would be before the definition of the function. Are there any codes defined before your function. I am able to get the output for the above program.
The executable code is given below for your reference.

def median(numbers):
    numbers.sort()
    size = len(numbers)
    midPos = size/2
    if size%2==0:
        median = (numbers[midPos]+numbers[midPos-1])/2.0
    else:
        median = numbers[midPos]
    return median


if __name__ == "__main__":

    numbers = [1,2,3,4,5,6,7,8,9,10]
    print median(numbers)

Output Console:

5.5

Process finished with exit code 0

def myCode(filepath):
    with open(filepath, 'r') as f:
        data = f.read()
        return data

def default_settings():=

settings = default_settings()
credentials = settings['credentials']
password, host, port = parse_credentials(credentials)

filename = 'tcp\test.py'
code = myCode(filename)
Encoding = 'UTF-8'
origin = os.path.basename(__file__)

send_code(filename, code, encoding, password, host, port, origin)

#выдает

def default_settings():=
                          ^
SyntaxError: invalid syntax


  • Вопрос задан

    более трёх лет назад

  • 856 просмотров

def myCode(filepath):
    with open(filepath, 'r') as f:
        data = f.read()
        return data

def default_settings():

    settings = default_settings()
    credentials = settings['credentials']
    password, host, port = parse_credentials(credentials)

    filename = 'tcp\test.py'
    code = myCode(filename)
    Encoding = 'UTF-8'
    origin = os.path.basename(__file__)

send_code(filename, code, encoding, password, host, port, origin)

Не знаю, что именно вы собирались сделать, но вот такой код заработает. После функции Def должнно быть двоиточие и ниже табуляция, никаких равно и тд

Господи, научитесь читать ошибки. Видно же, невооруженным глазом, что на какой-то строчке есть какой то неправильный символ….

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Минуточку внимания

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

Invalid Syntax in Python

When you run your Python code, the interpreter will first parse it to convert it into Python byte code, which it will then execute. The interpreter will find any invalid syntax in Python during this first stage of program execution, also known as the parsing stage. If the interpreter can’t parse your Python code successfully, then this means that you used invalid syntax somewhere in your code. The interpreter will attempt to show you where that error occurred.

When you’re learning Python for the first time, it can be frustrating to get a SyntaxError. Python will attempt to help you determine where the invalid syntax is in your code, but the traceback it provides can be a little confusing. Sometimes, the code it points to is perfectly fine.

You can’t handle invalid syntax in Python like other exceptions. Even if you tried to wrap a try and except block around code with invalid syntax, you’d still see the interpreter raise a SyntaxError.

SyntaxError Exception and Traceback

When the interpreter encounters invalid syntax in Python code, it will raise a SyntaxError exception and provide a traceback with some helpful information to help you debug the error. Here’s some code that contains invalid syntax in Python:

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

You can see the invalid syntax in the dictionary literal on line 4. The second entry, 'jim', is missing a comma. If you tried to run this code as-is, then you’d get the following traceback:

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

Note that the traceback message locates the error in line 5, not line 4. The Python interpreter is attempting to point out where the invalid syntax is. However, it can only really point to where it first noticed a problem. When you get a SyntaxError traceback and the code that the traceback is pointing to looks fine, then you’ll want to start moving backward through the code until you can determine what’s wrong.

In the example above, there isn’t a problem with leaving out a comma, depending on what comes after it. For example, there’s no problem with a missing comma after 'michael' in line 5. But once the interpreter encounters something that doesn’t make sense, it can only point you to the first thing it found that it couldn’t understand.

There are a few elements of a SyntaxError traceback that can help you determine where the invalid syntax is in your code:

  • The file name where the invalid syntax was encountered
  • The line number and reproduced line of code where the issue was encountered
  • A caret (^) on the line below the reproduced code, which shows you the point in the code that has a problem
  • The error message that comes after the exception type SyntaxError, which can provide information to help you determine the problem

In the example above, the file name given was theofficefacts.py, the line number was 5, and the caret pointed to the closing quote of the dictionary key michael. The SyntaxError traceback might not point to the real problem, but it will point to the first place where the interpreter couldn’t make sense of the syntax.

There are two other exceptions that you might see Python raise. These are equivalent to SyntaxError but have different names:

  1. IndentationError
  2. TabError

These exceptions both inherit from the SyntaxError class, but they’re special cases where indentation is concerned. An IndentationError is raised when the indentation levels of your code don’t match up. A TabError is raised when your code uses both tabs and spaces in the same file. You’ll take a closer look at these exceptions in a later section.

Common Syntax Problems

When you encounter a SyntaxError for the first time, it’s helpful to know why there was a problem and what you might do to fix the invalid syntax in your Python code. In the sections below, you’ll see some of the more common reasons that a SyntaxError might be raised and how you can fix them.

Misusing the Assignment Operator (=)

There are several cases in Python where you’re not able to make assignments to objects. Some examples are assigning to literals and function calls. In the code block below, you can see a few examples that attempt to do this and the resulting SyntaxError tracebacks:

>>>

>>> 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

The first example tries to assign the value 5 to the len() call. The SyntaxError message is very helpful in this case. It tells you that you can’t assign a value to a function call.

The second and third examples try to assign a string and an integer to literals. The same rule is true for other literal values. Once again, the traceback messages indicate that the problem occurs when you attempt to assign a value to a literal.

It’s likely that your intent isn’t to assign a value to a literal or a function call. For instance, this can occur if you accidentally leave off the extra equals sign (=), which would turn the assignment into a comparison. A comparison, as you can see below, would be valid:

>>>

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

Most of the time, when Python tells you that you’re making an assignment to something that can’t be assigned to, you first might want to check to make sure that the statement shouldn’t be a Boolean expression instead. You may also run into this issue when you’re trying to assign a value to a Python keyword, which you’ll cover in the next section.

Misspelling, Missing, or Misusing Python Keywords

Python keywords are a set of protected words that have special meaning in Python. These are words you can’t use as identifiers, variables, or function names in your code. They’re a part of the language and can only be used in the context that Python allows.

There are three common ways that you can mistakenly use keywords:

  1. Misspelling a keyword
  2. Missing a keyword
  3. Misusing a keyword

If you misspell a keyword in your Python code, then you’ll get a SyntaxError. For example, here’s what happens if you spell the keyword for incorrectly:

>>>

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

The message reads SyntaxError: invalid syntax, but that’s not very helpful. The traceback points to the first place where Python could detect that something was wrong. To fix this sort of error, make sure that all of your Python keywords are spelled correctly.

Another common issue with keywords is when you miss them altogether:

>>>

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

Once again, the exception message isn’t that helpful, but the traceback does attempt to point you in the right direction. If you move back from the caret, then you can see that the in keyword is missing from the for loop syntax.

You can also misuse a protected Python keyword. Remember, keywords are only allowed to be used in specific situations. If you use them incorrectly, then you’ll have invalid syntax in your Python code. A common example of this is the use of continue or break outside of a loop. This can easily happen during development when you’re implementing things and happen to move logic outside of a loop:

>>>

>>> 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

Here, Python does a great job of telling you exactly what’s wrong. The messages "'break' outside loop" and "'continue' not properly in loop" help you figure out exactly what to do. If this code were in a file, then Python would also have the caret pointing right to the misused keyword.

Another example is if you attempt to assign a Python keyword to a variable or use a keyword to define a function:

>>>

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

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

When you attempt to assign a value to pass, or when you attempt to define a new function called pass, you’ll get a SyntaxError and see the "invalid syntax" message again.

It might be a little harder to solve this type of invalid syntax in Python code because the code looks fine from the outside. If your code looks good, but you’re still getting a SyntaxError, then you might consider checking the variable name or function name you want to use against the keyword list for the version of Python that you’re using.

The list of protected keywords has changed with each new version of Python. For example, in Python 3.6 you could use await as a variable name or function name, but as of Python 3.7, that word has been added to the keyword list. Now, if you try to use await as a variable or function name, this will cause a SyntaxError if your code is for Python 3.7 or later.

Another example of this is print, which differs in Python 2 vs Python 3:

Version print Type Takes A Value
Python 2 keyword no
Python 3 built-in function yes

print is a keyword in Python 2, so you can’t assign a value to it. In Python 3, however, it’s a built-in function that can be assigned values.

You can run the following code to see the list of keywords in whatever version of Python you’re running:

import keyword
print(keyword.kwlist)

keyword also provides the useful keyword.iskeyword(). If you just need a quick way to check the pass variable, then you can use the following one-liner:

>>>

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

This code will tell you quickly if the identifier that you’re trying to use is a keyword or not.

Missing Parentheses, Brackets, and Quotes

Often, the cause of invalid syntax in Python code is a missed or mismatched closing parenthesis, bracket, or quote. These can be hard to spot in very long lines of nested parentheses or longer multi-line blocks. You can spot mismatched or missing quotes with the help of Python’s tracebacks:

>>>

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

Here, the traceback points to the invalid code where there’s a t' after a closing single quote. To fix this, you can make one of two changes:

  1. Escape the single quote with a backslash ('don't')
  2. Surround the entire string in double-quotes instead ("don't")

Another common mistake is to forget to close string. With both double-quoted and single-quoted strings, the situation and traceback are the same:

>>>

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

This time, the caret in the traceback points right to the problem code. The SyntaxError message, "EOL while scanning string literal", is a little more specific and helpful in determining the problem. This means that the Python interpreter got to the end of a line (EOL) before an open string was closed. To fix this, close the string with a quote that matches the one you used to start it. In this case, that would be a double quote (").

Quotes missing from statements inside an f-string can also lead to invalid syntax in Python:

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

Here, the reference to the ages dictionary inside the printed f-string is missing the closing double quote from the key reference. The resulting traceback is as follows:

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

Python identifies the problem and tells you that it exists inside the f-string. The message "unterminated string" also indicates what the problem is. The caret in this case only points to the beginning of the f-string.

This might not be as helpful as when the caret points to the problem area of the f-string, but it does narrow down where you need to look. There’s an unterminated string somewhere inside that f-string. You just have to find out where. To fix this problem, make sure that all internal f-string quotes and brackets are present.

The situation is mostly the same for missing parentheses and brackets. If you leave out the closing square bracket from a list, for example, then Python will spot that and point it out. There are a few variations of this, however. The first is to leave the closing bracket off of the list:

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

print(foo())

When you run this code, you’ll be told that there’s a problem with the call to print():

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

What’s happening here is that Python thinks the list contains three elements: 1, 2, and 3 print(foo()). Python uses whitespace to group things logically, and because there’s no comma or bracket separating 3 from print(foo()), Python lumps them together as the third element of the list.

Another variation is to add a trailing comma after the last element in the list while still leaving off the closing square bracket:

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

print(foo())

Now you get a different traceback:

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

                ^
SyntaxError: unexpected EOF while parsing

In the previous example, 3 and print(foo()) were lumped together as one element, but here you see a comma separating the two. Now, the call to print(foo()) gets added as the fourth element of the list, and Python reaches the end of the file without the closing bracket. The traceback tells you that Python got to the end of the file (EOF), but it was expecting something else.

In this example, Python was expecting a closing bracket (]), but the repeated line and caret are not very helpful. Missing parentheses and brackets are tough for Python to identify. Sometimes the only thing you can do is start from the caret and move backward until you can identify what’s missing or wrong.

Mistaking Dictionary Syntax

You saw earlier that you could get a SyntaxError if you leave the comma off of a dictionary element. Another form of invalid syntax with Python dictionaries is the use of the equals sign (=) to separate keys and values, instead of the colon:

>>>

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

Once again, this error message is not very helpful. The repeated line and caret, however, are very helpful! They’re pointing right to the problem character.

This type of issue is common if you confuse Python syntax with that of other programming languages. You’ll also see this if you confuse the act of defining a dictionary with a dict() call. To fix this, you could replace the equals sign with a colon. You can also switch to using dict():

>>>

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

You can use dict() to define the dictionary if that syntax is more helpful.

Using the Wrong Indentation

There are two sub-classes of SyntaxError that deal with indentation issues specifically:

  1. IndentationError
  2. TabError

While other programming languages use curly braces to denote blocks of code, Python uses whitespace. That means that Python expects the whitespace in your code to behave predictably. It will raise an IndentationError if there’s a line in a code block that has the wrong number of spaces:

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

This might be tough to see, but line 5 is only indented 2 spaces. It should be in line with the for loop statement, which is 4 spaces over. Thankfully, Python can spot this easily and will quickly tell you what the issue is.

There’s also a bit of ambiguity here, though. Is the print('done') line intended to be after the for loop or inside the for loop block? When you run the above code, you’ll see the following error:

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

Even though the traceback looks a lot like the SyntaxError traceback, it’s actually an IndentationError. The error message is also very helpful. It tells you that the indentation level of the line doesn’t match any other indentation level. In other words, print('done') is indented 2 spaces, but Python can’t find any other line of code that matches this level of indentation. You can fix this quickly by making sure the code lines up with the expected indentation level.

The other type of SyntaxError is the TabError, which you’ll see whenever there’s a line that contains either tabs or spaces for its indentation, while the rest of the file contains the other. This might go hidden until Python points it out to you!

If your tab size is the same width as the number of spaces in each indentation level, then it might look like all the lines are at the same level. However, if one line is indented using spaces and the other is indented with tabs, then Python will point this out as a problem:

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

Here, line 5 is indented with a tab instead of 4 spaces. This code block could look perfectly fine to you, or it could look completely wrong, depending on your system settings.

Python, however, will notice the issue immediately. But before you run the code to see what Python will tell you is wrong, it might be helpful for you to see an example of what the code looks like under different tab width settings:

$ 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()

Notice the difference in display between the three examples above. Most of the code uses 4 spaces for each indentation level, but line 5 uses a single tab in all three examples. The width of the tab changes, based on the tab width setting:

  • If the tab width is 4, then the print statement will look like it’s outside the for loop. The console will print 'done' at the end of the loop.
  • If the tab width is 8, which is standard for a lot of systems, then the print statement will look like it’s inside the for loop. The console will print 'done' after each number.
  • If the tab width is 3, then the print statement looks out of place. In this case, line 5 doesn’t match up with any indentation level.

When you run the code, you’ll get the following error and traceback:

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

Notice the TabError instead of the usual SyntaxError. Python points out the problem line and gives you a helpful error message. It tells you clearly that there’s a mixture of tabs and spaces used for indentation in the same file.

The solution to this is to make all lines in the same Python code file use either tabs or spaces, but not both. For the code blocks above, the fix would be to remove the tab and replace it with 4 spaces, which will print 'done' after the for loop has finished.

Defining and Calling Functions

You might run into invalid syntax in Python when you’re defining or calling functions. For example, you’ll see a SyntaxError if you use a semicolon instead of a colon at the end of a function definition:

>>>

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

The traceback here is very helpful, with the caret pointing right to the problem character. You can clear up this invalid syntax in Python by switching out the semicolon for a colon.

In addition, keyword arguments in both function definitions and function calls need to be in the right order. Keyword arguments always come after positional arguments. Failure to use this ordering will lead to a SyntaxError:

>>>

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

Here, once again, the error message is very helpful in telling you exactly what is wrong with the line.

Changing Python Versions

Sometimes, code that works perfectly fine in one version of Python breaks in a newer version. This is due to official changes in language syntax. The most well-known example of this is the print statement, which went from a keyword in Python 2 to a built-in function in Python 3:

>>>

>>> # 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')?

This is one of the examples where the error message provided with the SyntaxError shines! Not only does it tell you that you’re missing parenthesis in the print call, but it also provides the correct code to help you fix the statement.

Another problem you might encounter is when you’re reading or learning about syntax that’s valid syntax in a newer version of Python, but isn’t valid in the version you’re writing in. An example of this is the f-string syntax, which doesn’t exist in Python versions before 3.6:

>>>

>>> # 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

In versions of Python before 3.6, the interpreter doesn’t know anything about the f-string syntax and will just provide a generic "invalid syntax" message. The problem, in this case, is that the code looks perfectly fine, but it was run with an older version of Python. When in doubt, double-check which version of Python you’re running!

Python syntax is continuing to evolve, and there are some cool new features introduced in Python 3.8:

  • Walrus operator (assignment expressions)
  • F-string syntax for debugging
  • Positional-only arguments

If you want to try out some of these new features, then you need to make sure you’re working in a Python 3.8 environment. Otherwise, you’ll get a SyntaxError.

Python 3.8 also provides the new SyntaxWarning. You’ll see this warning in situations where the syntax is valid but still looks suspicious. An example of this would be if you were missing a comma between two tuples in a list. This would be valid syntax in Python versions before 3.8, but the code would raise a TypeError because a tuple is not callable:

>>>

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

This TypeError means that you can’t call a tuple like a function, which is what the Python interpreter thinks you’re doing.

In Python 3.8, this code still raises the TypeError, but now you’ll also see a SyntaxWarning that indicates how you can go about fixing the problem:

>>>

>>> [(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

The helpful message accompanying the new SyntaxWarning even provides a hint ("perhaps you missed a comma?") to point you in the right direction!

Conclusion

In this tutorial, you’ve seen what information the SyntaxError traceback gives you. You’ve also seen many common examples of invalid syntax in Python and what the solutions are to those problems. Not only will this speed up your workflow, but it will also make you a more helpful code reviewer!

When you’re writing code, try to use an IDE that understands Python syntax and provides feedback. If you put many of the invalid Python code examples from this tutorial into a good IDE, then they should highlight the problem lines before you even get to execute your code.

Getting a SyntaxError while you’re learning Python can be frustrating, but now you know how to understand traceback messages and what forms of invalid syntax in Python you might come up against. The next time you get a SyntaxError, you’ll be better equipped to fix the problem quickly!

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

Until now error messages haven’t been more than mentioned, but if you have tried
out the examples you have probably seen some. There are (at least) two
distinguishable kinds of errors: syntax errors and exceptions.

8.1. Syntax Errors¶

Syntax errors, also known as parsing errors, are perhaps the most common kind of
complaint you get while you are still learning Python:

>>> while True print('Hello world')
  File "<stdin>", line 1
    while True print('Hello world')
                   ^
SyntaxError: invalid syntax

The parser repeats the offending line and displays a little ‘arrow’ pointing at
the earliest point in the line where the error was detected. The error is
caused by (or at least detected at) the token preceding the arrow: in the
example, the error is detected at the function print(), since a colon
(':') is missing before it. File name and line number are printed so you
know where to look in case the input came from a script.

8.2. Exceptions¶

Even if a statement or expression is syntactically correct, it may cause an
error when an attempt is made to execute it. Errors detected during execution
are called exceptions and are not unconditionally fatal: you will soon learn
how to handle them in Python programs. Most exceptions are not handled by
programs, however, and result in error messages as shown here:

>>> 10 * (1/0)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ZeroDivisionError: division by zero
>>> 4 + spam*3
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'spam' is not defined
>>> '2' + 2
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: Can't convert 'int' object to str implicitly

The last line of the error message indicates what happened. Exceptions come in
different types, and the type is printed as part of the message: the types in
the example are ZeroDivisionError, NameError and TypeError.
The string printed as the exception type is the name of the built-in exception
that occurred. This is true for all built-in exceptions, but need not be true
for user-defined exceptions (although it is a useful convention). Standard
exception names are built-in identifiers (not reserved keywords).

The rest of the line provides detail based on the type of exception and what
caused it.

The preceding part of the error message shows the context where the exception
happened, in the form of a stack traceback. In general it contains a stack
traceback listing source lines; however, it will not display lines read from
standard input.

Built-in Exceptions lists the built-in exceptions and their meanings.

8.3. Handling Exceptions¶

It is possible to write programs that handle selected exceptions. Look at the
following example, which asks the user for input until a valid integer has been
entered, but allows the user to interrupt the program (using Control-C or
whatever the operating system supports); note that a user-generated interruption
is signalled by raising the KeyboardInterrupt exception.

>>> while True:
...     try:
...         x = int(input("Please enter a number: "))
...         break
...     except ValueError:
...         print("Oops!  That was no valid number.  Try again...")
...

The try statement works as follows.

  • First, the try clause (the statement(s) between the try and
    except keywords) is executed.
  • If no exception occurs, the except clause is skipped and execution of the
    try statement is finished.
  • If an exception occurs during execution of the try clause, the rest of the
    clause is skipped. Then if its type matches the exception named after the
    except keyword, the except clause is executed, and then execution
    continues after the try statement.
  • If an exception occurs which does not match the exception named in the except
    clause, it is passed on to outer try statements; if no handler is
    found, it is an unhandled exception and execution stops with a message as
    shown above.

A try statement may have more than one except clause, to specify
handlers for different exceptions. At most one handler will be executed.
Handlers only handle exceptions that occur in the corresponding try clause, not
in other handlers of the same try statement. An except clause may
name multiple exceptions as a parenthesized tuple, for example:

... except (RuntimeError, TypeError, NameError):
...     pass

A class in an except clause is compatible with an exception if it is
the same class or a base class thereof (but not the other way around — an
except clause listing a derived class is not compatible with a base class). For
example, the following code will print B, C, D in that order:

class B(Exception):
    pass

class C(B):
    pass

class D(C):
    pass

for cls in [B, C, D]:
    try:
        raise cls()
    except D:
        print("D")
    except C:
        print("C")
    except B:
        print("B")

Note that if the except clauses were reversed (with except B first), it
would have printed B, B, B — the first matching except clause is triggered.

The last except clause may omit the exception name(s), to serve as a wildcard.
Use this with extreme caution, since it is easy to mask a real programming error
in this way! It can also be used to print an error message and then re-raise
the exception (allowing a caller to handle the exception as well):

import sys

try:
    f = open('myfile.txt')
    s = f.readline()
    i = int(s.strip())
except OSError as err:
    print("OS error: {0}".format(err))
except ValueError:
    print("Could not convert data to an integer.")
except:
    print("Unexpected error:", sys.exc_info()[0])
    raise

The tryexcept statement has an optional else
clause
, which, when present, must follow all except clauses. It is useful for
code that must be executed if the try clause does not raise an exception. For
example:

for arg in sys.argv[1:]:
    try:
        f = open(arg, 'r')
    except OSError:
        print('cannot open', arg)
    else:
        print(arg, 'has', len(f.readlines()), 'lines')
        f.close()

The use of the else clause is better than adding additional code to
the try clause because it avoids accidentally catching an exception
that wasn’t raised by the code being protected by the try
except statement.

When an exception occurs, it may have an associated value, also known as the
exception’s argument. The presence and type of the argument depend on the
exception type.

The except clause may specify a variable after the exception name. The
variable is bound to an exception instance with the arguments stored in
instance.args. For convenience, the exception instance defines
__str__() so the arguments can be printed directly without having to
reference .args. One may also instantiate an exception first before
raising it and add any attributes to it as desired.

>>> try:
...     raise Exception('spam', 'eggs')
... except Exception as inst:
...     print(type(inst))    # the exception instance
...     print(inst.args)     # arguments stored in .args
...     print(inst)          # __str__ allows args to be printed directly,
...                          # but may be overridden in exception subclasses
...     x, y = inst.args     # unpack args
...     print('x =', x)
...     print('y =', y)
...
<class 'Exception'>
('spam', 'eggs')
('spam', 'eggs')
x = spam
y = eggs

If an exception has arguments, they are printed as the last part (‘detail’) of
the message for unhandled exceptions.

Exception handlers don’t just handle exceptions if they occur immediately in the
try clause, but also if they occur inside functions that are called (even
indirectly) in the try clause. For example:

>>> def this_fails():
...     x = 1/0
...
>>> try:
...     this_fails()
... except ZeroDivisionError as err:
...     print('Handling run-time error:', err)
...
Handling run-time error: division by zero

8.4. Raising Exceptions¶

The raise statement allows the programmer to force a specified
exception to occur. For example:

>>> raise NameError('HiThere')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: HiThere

The sole argument to raise indicates the exception to be raised.
This must be either an exception instance or an exception class (a class that
derives from Exception). If an exception class is passed, it will
be implicitly instantiated by calling its constructor with no arguments:

raise ValueError  # shorthand for 'raise ValueError()'

If you need to determine whether an exception was raised but don’t intend to
handle it, a simpler form of the raise statement allows you to
re-raise the exception:

>>> try:
...     raise NameError('HiThere')
... except NameError:
...     print('An exception flew by!')
...     raise
...
An exception flew by!
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
NameError: HiThere

8.5. User-defined Exceptions¶

Programs may name their own exceptions by creating a new exception class (see
Classes for more about Python classes). Exceptions should typically
be derived from the Exception class, either directly or indirectly.

Exception classes can be defined which do anything any other class can do, but
are usually kept simple, often only offering a number of attributes that allow
information about the error to be extracted by handlers for the exception. When
creating a module that can raise several distinct errors, a common practice is
to create a base class for exceptions defined by that module, and subclass that
to create specific exception classes for different error conditions:

class Error(Exception):
    """Base class for exceptions in this module."""
    pass

class InputError(Error):
    """Exception raised for errors in the input.

    Attributes:
        expression -- input expression in which the error occurred
        message -- explanation of the error
    """

    def __init__(self, expression, message):
        self.expression = expression
        self.message = message

class TransitionError(Error):
    """Raised when an operation attempts a state transition that's not
    allowed.

    Attributes:
        previous -- state at beginning of transition
        next -- attempted new state
        message -- explanation of why the specific transition is not allowed
    """

    def __init__(self, previous, next, message):
        self.previous = previous
        self.next = next
        self.message = message

Most exceptions are defined with names that end in “Error,” similar to the
naming of the standard exceptions.

Many standard modules define their own exceptions to report errors that may
occur in functions they define. More information on classes is presented in
chapter Classes.

8.6. Defining Clean-up Actions¶

The try statement has another optional clause which is intended to
define clean-up actions that must be executed under all circumstances. For
example:

>>> try:
...     raise KeyboardInterrupt
... finally:
...     print('Goodbye, world!')
...
Goodbye, world!
KeyboardInterrupt
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>

A finally clause is always executed before leaving the try
statement, whether an exception has occurred or not. When an exception has
occurred in the try clause and has not been handled by an
except clause (or it has occurred in an except or
else clause), it is re-raised after the finally clause has
been executed. The finally clause is also executed “on the way out”
when any other clause of the try statement is left via a
break, continue or return statement. A more
complicated example:

>>> def divide(x, y):
...     try:
...         result = x / y
...     except ZeroDivisionError:
...         print("division by zero!")
...     else:
...         print("result is", result)
...     finally:
...         print("executing finally clause")
...
>>> divide(2, 1)
result is 2.0
executing finally clause
>>> divide(2, 0)
division by zero!
executing finally clause
>>> divide("2", "1")
executing finally clause
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 3, in divide
TypeError: unsupported operand type(s) for /: 'str' and 'str'

As you can see, the finally clause is executed in any event. The
TypeError raised by dividing two strings is not handled by the
except clause and therefore re-raised after the finally
clause has been executed.

In real world applications, the finally clause is useful for
releasing external resources (such as files or network connections), regardless
of whether the use of the resource was successful.

8.7. Predefined Clean-up Actions¶

Some objects define standard clean-up actions to be undertaken when the object
is no longer needed, regardless of whether or not the operation using the object
succeeded or failed. Look at the following example, which tries to open a file
and print its contents to the screen.

for line in open("myfile.txt"):
    print(line, end="")

The problem with this code is that it leaves the file open for an indeterminate
amount of time after this part of the code has finished executing.
This is not an issue in simple scripts, but can be a problem for larger
applications. The with statement allows objects like files to be
used in a way that ensures they are always cleaned up promptly and correctly.

with open("myfile.txt") as f:
    for line in f:
        print(line, end="")

After the statement is executed, the file f is always closed, even if a
problem was encountered while processing the lines. Objects which, like files,
provide predefined clean-up actions will indicate this in their documentation.

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