- 8. Errors and ExceptionsВ¶
- 8.1. Syntax ErrorsВ¶
- 8.2. ExceptionsВ¶
- 8.3. Handling ExceptionsВ¶
- 8.4. Raising ExceptionsВ¶
- 8.5. Exception ChainingВ¶
- 8.6. User-defined ExceptionsВ¶
- 8.7. Defining Clean-up ActionsВ¶
- 8.8. Predefined Clean-up ActionsВ¶
- 8.9. Raising and Handling Multiple Unrelated ExceptionsВ¶
- 8.10. Enriching Exceptions with NotesВ¶
- Get back up and try again: retrying in Python
- Julien Danjou
- Julien Danjou
- It’s OK to fail
8. Errors and ExceptionsВ¶
Until now error messages havenвЂ™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 ErrorsВ¶
Syntax errors, also known as parsing errors, are perhaps the most common kind of complaint you get while you are still learning Python:
The parser repeats the offending line and displays a little вЂarrowвЂ™ 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.
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:
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 occurred, 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 ExceptionsВ¶
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.
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/except block.
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:
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 вЂ” 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:
Note that if the except clauses were reversed (with except B first), it would have printed B, B, B вЂ” the first matching except clause is triggered.
When an exception occurs, it may have associated values, also known as the exceptionвЂ™s arguments. The presence and types of the arguments depend on the exception type.
The except clause may specify a variable after the exception name. The variable is bound to the exception instance which typically has an args attribute that stores the arguments. For convenience, builtin exception types define __str__() to print all the arguments without explicitly accessing .args .
The exceptionвЂ™s __str__() output is printed as the last part (вЂdetailвЂ™) of the message for unhandled exceptions.
BaseException is the common base class of all exceptions. One of its subclasses, Exception , is the base class of all the non-fatal exceptions. Exceptions which are not subclasses of Exception are not typically handled, because they are used to indicate that the program should terminate. They include SystemExit which is raised by sys.exit() and KeyboardInterrupt which is raised when a user wishes to interrupt the program.
Exception can be used as a wildcard that catches (almost) everything. However, it is good practice to be as specific as possible with the types of exceptions that we intend to handle, and to allow any unexpected exceptions to propagate on.
The most common pattern for handling Exception is to print or log the exception and then re-raise it (allowing a caller to handle the exception as well):
The try вЂ¦ except 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:
The use of the else clause is better than adding additional code to the try clause because it avoids accidentally catching an exception that wasnвЂ™t raised by the code being protected by the try вЂ¦ except statement.
Exception handlers do not handle only exceptions that occur immediately in the try clause, but also those that occur inside functions that are called (even indirectly) in the try clause. For example:
8.4. Raising ExceptionsВ¶
The raise statement allows the programmer to force a specified exception to occur. For example:
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 BaseException , such as Exception or one of its subclasses). If an exception class is passed, it will be implicitly instantiated by calling its constructor with no arguments:
If you need to determine whether an exception was raised but donвЂ™t intend to handle it, a simpler form of the raise statement allows you to re-raise the exception:
8.5. Exception ChainingВ¶
If an unhandled exception occurs inside an except section, it will have the exception being handled attached to it and included in the error message:
To indicate that an exception is a direct consequence of another, the raise statement allows an optional from clause:
This can be useful when you are transforming exceptions. For example:
It also allows disabling automatic exception chaining using the from None idiom:
For more information about chaining mechanics, see Built-in Exceptions .
8.6. User-defined ExceptionsВ¶
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.
Most exceptions are defined with names that end in вЂњErrorвЂќ, 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.
8.7. Defining Clean-up ActionsВ¶
The try statement has another optional clause which is intended to define clean-up actions that must be executed under all circumstances. For example:
If a finally clause is present, the finally clause will execute as the last task before the try statement completes. The finally clause runs whether or not the try statement produces an exception. The following points discuss more complex cases when an exception occurs:
If an exception occurs during execution of the try clause, the exception may be handled by an except clause. If the exception is not handled by an except clause, the exception is re-raised after the finally clause has been executed.
An exception could occur during execution of an except or else clause. Again, the exception is re-raised after the finally clause has been executed.
If the finally clause executes a break , continue or return statement, exceptions are not re-raised.
If the try statement reaches a break , continue or return statement, the finally clause will execute just prior to the break , continue or return statementвЂ™s execution.
If a finally clause includes a return statement, the returned value will be the one from the finally clauseвЂ™s return statement, not the value from the try clauseвЂ™s return statement.
A more complicated example:
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.
8.8. Predefined Clean-up ActionsВ¶
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.
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.
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.
8.9. Raising and Handling Multiple Unrelated ExceptionsВ¶
There are situations where it is necessary to report several exceptions that have occurred. This is often the case in concurrency frameworks, when several tasks may have failed in parallel, but there are also other use cases where it is desirable to continue execution and collect multiple errors rather than raise the first exception.
The builtin ExceptionGroup wraps a list of exception instances so that they can be raised together. It is an exception itself, so it can be caught like any other exception.
By using except* instead of except , we can selectively handle only the exceptions in the group that match a certain type. In the following example, which shows a nested exception group, each except* clause extracts from the group exceptions of a certain type while letting all other exceptions propagate to other clauses and eventually to be reraised.
Note that the exceptions nested in an exception group must be instances, not types. This is because in practice the exceptions would typically be ones that have already been raised and caught by the program, along the following pattern:
8.10. Enriching Exceptions with NotesВ¶
When an exception is created in order to be raised, it is usually initialized with information that describes the error that has occurred. There are cases where it is useful to add information after the exception was caught. For this purpose, exceptions have a method add_note(note) that accepts a string and adds it to the exceptionвЂ™s notes list. The standard traceback rendering includes all notes, in the order they were added, after the exception.
For example, when collecting exceptions into an exception group, we may want to add context information for the individual errors. In the following each exception in the group has a note indicating when this error has occurred.
Get back up and try again: retrying in Python
Read more posts by this author.
The library presented in this article is becoming obsolete and un-maintained. I recommend you to read this post about tenacity instead.
I don’t often write about tools I use when for my daily software development tasks. I recently realized that I really should start to share more often my workflows and weapons of choice.
One thing that I have a hard time enduring while doing Python code reviews, is people writing utility code that is not directly tied to the core of their business. This looks to me as wasted time maintaining code that should be reused from elsewhere.
So today I’d like to start with retrying, a Python package that you can use to… retry anything.
It’s OK to fail
Often in computing, you have to deal with external resources. That means accessing resources you don’t control. Resources that can fail, become flapping, unreachable or unavailable.
Most applications don’t deal with that at all, and explode in flight, leaving a skeptical user in front of the computer. A lot of software engineers refuse to deal with failure, and don’t bother handling this kind of scenario in their code.
In the best case, applications usually handle simply the case where the external reached system is out of order. They log something, and inform the user that it should try again later.
In this cloud computing area, we tend to design software components with service-oriented architecture in mind. That means having a lot of different services talking to each others over the network. And we all know that networks tend to fail, and distributed systems too. Writing software with failing being part of normal operation is a terrific idea.
In order to help applications with the handling of these potential failures, you need a plan. Leaving to the user the burden to «try again later» is rarely a good choice. Therefore, most of the time you want your application to retry.
Retrying an action is a full strategy on its own, with a lot of options. You can retry only on certain condition, and with the number of tries based on time (e.g. every second), based on a number of tentative (e.g. retry 3 times and abort), based on the problem encountered, or even on all of those.
For all of that, I use the retrying library that you can retrieve easily on PyPI.
retrying provides a decorator called retry that you can use on top of any function or method in Python to make it retry in case of failure. By default, retry calls your function endlessly until it returns rather than raising an error.
This will execute the function pick_one until 1 is returned by random.randint .
retry accepts a few arguments, such as the minimum and maximum delays to use, which also can be randomized. Randomizing delay is a good strategy to avoid detectable pattern or congestion. But more over, it supports exponential delay, which can be used to implement exponential backoff, a good solution for retrying tasks while really avoiding congestion. It’s especially handy for background tasks.
You can mix that with a maximum delay, which can give you a good strategy to retry for a while, and then fail anyway:
A pattern I use very often, is the ability to retry only based on some exception type. You can specify a function to filter out exception you want to ignore or the one you want to use to retry.
retry will call the function passed as retry_on_exception with the exception raised as first argument. It’s up to the function to then return a boolean indicating if a retry should be performed or not. In the example above, this will only retry to read the file if an IOError occurs; if any other exception type is raised, no retry will be performed.
The same pattern can be implemented using the keyword argument retry_on_result , where you can provide a function that analyses the result and retry based on it.
This example will read the file until it stops being empty. If the file does not exist, an IOError is raised, and the default behavior which triggers retry on all exceptions kicks-in – the retry is therefore performed.
That’s it! retry is really a good and small library that you should leverage rather than implementing your own half-baked solution!