In Python, all exceptions must be instances of a class that derives from BaseException. In a try statement with an except clause that mentions a particular class, that clause also handles any exception classes derived from that class but not exception classes from which it is derived. Two exception classes that are not related via subclassing are never equivalent, even if they have the same name.
The built-in exceptions listed below can be generated by the interpreter or built-in functions. This may be a string or a tuple of several items of information e. User code can raise built-in exceptions. The built-in exception classes can be subclassed to define new exceptions; programmers are encouraged to derive new exceptions from the Exception class or one of its subclasses, and not from BaseException.
More information on defining exceptions is available in the Python Tutorial under User-defined Exceptions. When raising a new exception rather than using a bare raise to re-raise the exception currently being handledthe implicit exception context can be supplemented with an explicit cause by using from with raise :.
The expression following from must be an exception or None. The default traceback display code shows these chained exceptions in addition to the traceback for the exception itself.
In either case, the exception itself is always shown after any chained exceptions so that the final line of the traceback always shows the last exception that was raised. The base class for all built-in exceptions. It is not meant to be directly inherited by user-defined classes for that, use Exception. If str is called on an instance of this class, the representation of the argument s to the instance are returned, or the empty string when there were no arguments.
The tuple of arguments given to the exception constructor. Some built-in exceptions like OSError expect a certain number of arguments and assign a special meaning to the elements of this tuple, while others are usually called only with a single string giving an error message. This method sets tb as the new traceback for the exception and returns the exception object.
Requests timeout in Python
It is usually used in exception handling code like this:. All built-in, non-system-exiting exceptions are derived from this class.This module defines the class FTP and a few related items.
It is also used by the module urllib. Return a new instance of the FTP class. When host is given, the method call connect host is made. When user is given, additionally the method call login user, passwd, acct is made where passwd and acct default to the empty string when not given.
The optional timeout parameter specifies a timeout in seconds for blocking operations like the connection attempt if is not specified, the global default timeout setting will be used. The FTP class supports the with statement, e. Changed in version 3. Connect as usual to port 21 implicitly securing the FTP control connection before authenticating. SSLContext object which allows bundling SSL configuration options, certificates and private keys into a single potentially long-lived structure.
Please read Security considerations for best practices. Deprecated since version 3. Please use ssl. Exception raised when an error code signifying a temporary error response codes in the range — is received.
Exception raised when an error code signifying a permanent error response codes in the range — is received. Exception raised when a reply is received from the server that does not fit the response specifications of the File Transfer Protocol, i.
The set of all exceptions as a tuple that methods of FTP instances may raise as a result of problems with the FTP connection as opposed to programming errors made by the caller. Parser for the. The file. Several methods are available in two flavors: one for handling text files and another for binary files. These are named for the command which is used followed by lines for the text version or binary for the binary version. FTP instances have the following methods:.
Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. Have a look at the Requests exception docs. In short:. In the event of a network problem e. If a request exceeds the configured number of maximum redirections, a TooManyRedirects exception is raised.
All exceptions that Requests explicitly raises inherit from requests. To answer your question, what you show will not cover all of your bases. You'll only catch connection-related errors, not ones that time out. Is it acceptable to exit? Can you go on and try again? If the error is catastrophic and you can't go on, then yes, you may abort your program by raising SystemExit a nice way to both print an error and call sys. If you want http errors e.
One additional suggestion to be explicit. It seems best to go from specific to general down the stack of errors to get the desired error to be caught, so the specific ones don't get masked by the general one.
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Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information. It times out at least once every day, and it has a variable coded in so I have to update the variable and then manually run the bot again. I am looking for a way to automatically handle these exceptions. I looked into try: and except:, but I am afraid that adding a break point after time.
I want it to keep running the loop regardless if it times out or not. There is a sample of the code below.
Moving the sleep to finally will solve your issue, I guess. Learn more. Handling a timeout exception in Python Ask Question. Asked 3 years, 7 months ago. Active 3 years, 7 months ago. Viewed 9k times. Matt T.
Active Oldest Votes. It depends on what you want to do when a timeout occurs.
Alu Alu 5 5 silver badges 16 16 bronze badges. I should have added that one of the functions of the bot is that when it hasn't detected a comment for a while is sleeps for 10 seconds and then checks again, so that it doesn't keep spamming Reddit. Is there any way to keep that sleep in there?When you make requests to an external service, you need to wait for the response before continuing.
You should always use the timeout parameter in your code. Otherwise, the user experience will suffer, or your application will hang. First, you have to import requests. As I wrote before, you can use int and float values as the timeout parameter.
In addition to that, you can also use tuples. The tuple comes with two elements. The first element is the time to establish a connection with the remote server, and the second parameter is the time it will wait for a response from the server after the connection was established. In our case, the program will wait 3 seconds to establish a connection, and if this successful, it will wait for another 8 for the server response. We always need to remember that if something bad can go wrong, it will.
We have to be prepared for bad things to happen. In our case, it will be the timeout exception. First, you have to add the request. The request got executed. I waited far too long. Post Views: The Queue module has been renamed to queue in Python 3. The 2to3 tool will automatically adapt imports when converting your sources to Python 3. The Queue module implements multi-producer, multi-consumer queues. It is especially useful in threaded programming when information must be exchanged safely between multiple threads.
The Queue class in this module implements all the required locking semantics. It depends on the availability of thread support in Python; see the threading module. The module implements three types of queue, which differ only in the order in which the entries are retrieved.
In a FIFO queue, the first tasks added are the first retrieved. In a LIFO queue, the most recently added entry is the first retrieved operating like a stack. With a priority queue, the entries are kept sorted using the heapq module and the lowest valued entry is retrieved first. The Queue module defines the following classes and exceptions:. Constructor for a FIFO queue. Insertion will block once this size has been reached, until queue items are consumed.
If maxsize is less than or equal to zero, the queue size is infinite. Constructor for a LIFO queue. Constructor for a priority queue. The lowest valued entries are retrieved first the lowest valued entry is the one returned by sorted list entries . Return the approximate size of the queue.
Return True if the queue is empty, False otherwise. Return True if the queue is full, False otherwise. Put item into the queue.
Python - Exceptions Handling
If optional args block is true and timeout is None the defaultblock if necessary until a free slot is available. If timeout is a positive number, it blocks at most timeout seconds and raises the Full exception if no free slot was available within that time. Otherwise block is falseput an item on the queue if a free slot is immediately available, else raise the Full exception timeout is ignored in that case.
How can I raise an exception in Python so that it can later be caught via an except block?Handling Timeouts in Python Requests
Use the most specific Exception constructor that semantically fits your issue. Avoid raising a generic Exception. To catch it, you'll have to catch all other more specific exceptions that subclass it. Instead, use the most specific Exception constructor that semantically fits your issue.
These arguments are accessed by the args attribute on the Exception object. For example:. In Python 2. When inside an except clause, you might want to, for example, log that a specific type of error happened, and then re-raise.
The best way to do this while preserving the stack trace is to use a bare raise statement. You can preserve the stacktrace and error value with sys. If you want to, you can modify what happens with your new raise - e.
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And we have preserved the whole traceback while modifying the args. Note that this is not a best practice and it is invalid syntax in Python 3 making keeping compatibility much harder to work around. In Python 3 :. Again: avoid manually manipulating tracebacks. It's less efficient and more error prone.
And if you're using threading and sys.
These can easily hide and even get into production code. You want to raise an exception, and doing them will raise an exception, but not the one intended! Valid in Python 2, but not in Python 3 is the following:. Only valid in much older versions of Python 2. In all modern versions, this will actually raise a TypeErrorbecause you're not raising a BaseException type. If you're not checking for the right exception and don't have a reviewer that's aware of the issue, it could get into production.
You can create your own error types, if you want to indicate something specific is wrong with your application, just subclass the appropriate point in the exception hierarchy:. Raising a bare Exception is absolutely not the right thing to do; see Aaron Hall's excellent answer instead.
See the raise statement docs for python if you'd like more info. If you use raise exception args to raise an exception then the args will be printed when you print the exception object - as shown in the example below.
This is useful if you need to perform some actions after catching the exception and then want to re-raise it. But if there was no exception before, raise statement raises TypeError Exception. This statement is used to create exception chaining in which an exception that is raised in response to another exception can contain the details of the original exception - as shown in the example below.