Python errno 5 input output error



[SOLVED] “errno 5 input/output error” fixes

Input/output error is a general error message that happens all the time under different situation. It indicates a problem in filesystem level, more specifically, the operating system cannot access a certain part of the disk drive (or virtual disk drive).

In this article, we will explain the possible reasons why the “errno 5 input/output error” message happens and a few solutions that might help solving it.

“[Errno 5] Input/output error” causes

Before we get into any further, let’s make it clear that the error indicates a problem happens with the disk while the operating system is writing or reading from it. The error is specific to Linux machines.

Sometimes, especially in situation where you’re running Linux as a virtual machine, the cause of “[Errno 5] Input/output error” might be related to the hypervisor. Try updating VMware or VirtualBox to see if the problem goes away.

Windows is currently under heavy development with changes are made every few months, that makes running a virtual machine more complex than ever. On Windows machines, you have to pay attention to Hyper-V to see if it plays nicely with VirtualBox or VMware. If Hyper-V causes the problem, you would have no choice but update VMware or VirtualBox (or reinstall Windows, of course).

“errno 5 input/output error” when trying to install Ubuntu/Debian

The error might look like the image above.

Not only happens on Ubuntu/Debian, the identical error message can also be displayed in Linux Mint (as it is a Ubuntu derivative).

Now there are several things you can try :

  • Make sure your CD/DVD or flash drive contents are not corrupted. Usually the only thing you need to do is verifying MD5 hash of the ISO file you’ve downloaded against the official value from Ubuntu/Debian/Linux Mint website.
  • Backup the existing disk (the whole HDD, not only the important partition) then delete all of them to reformat the whole disk. Or you could choose “Erase disk and install Ubuntu” to avoid manually deleting partitions.
  • Test your RAM for defects. You can use MemTest86 to conduct this type of test. If you have a defect RAM, remove or replace it.
  • Last resort : Replace the HDD to see if the error message goes away.
  • “errno 5 input/output error” when using Google Colab

    Colaboratory, also known as Google Colab, is a product from Google Research, it allows running Python code through the browser, especially suitable for data analysis, machine learning and education. Colab also allows running terminal commands prefix with the exclamation mark.

    Sometimes, running terminal commands in Colab returns “”[Errno 5] Input/output error”. Another form of this error is “OSError: [Errno 5] Input/output error” when you try to run Python code that access the filesystem.

    Google Drive integration in Colab is handy, but since these are 2 different services running in a cloud of thousands of servers, sometimes it performs not as well as if it is a physical server. If you’re connecting to Google Drive and mounted it to Colab, remember these rules of thumb to avoid input/output error :

    • Number of files or subfolders in a folder should not be too large. We recommend keeping them under 50 subfolders/files.
    • Try not to perform too many read/write operations to mounted Google Drive folder. Instead of that, write to the virtual environment disk, then move all of them to Google Drive mounted folder. The moving data functionality must have been thoroughly coded and tested before they launch Google Colab.
    • Try not to run any snippet of code for too long since it may cause Colab to raise timeout error.
    • Try not to move too much data at a short period of time. There are quota set by Google which are not necessary shown while using Colab. Basically, once the limit is passed you get the [Errno 5] Input/output error independent on the file or the operation you were doing.
    • When in doubt, move files and folders out of /content/drive before manipulating them might solve your problem.

    “OSError: errno 5 input/output error” with Python

    It doesn’t really matter that you are using Django, Odoo, PyTorch or low-level libraries like pexpect or shutil, if there’s something wrong while reading/writing data to the disk, “OSError: errno 5 input/output error” might be the first error you will see.

    There’s a couple of things you can try, depends on your specific scenario :

    • Check the disk for errors. On Windows, you can run chkdsk . On Linux, there is fsck . If there are recoverable errors, they’ll be fixed. After that, your Python program may run without any issue.
    • Carefully inspect the permissions of the folder/directory you’re working in. It should include appropriate read/write permission.
    • Replace the disk drive to see if the problem goes away. If it does, then your disk drive is faulty.

    We hope that the solutions above help you solve your problem and learn something along the way. If you’re new to Linux, you might want to checkout our guide on common error messages such as “ifconfig: command not found” and “cannot stat”. Backing up is important to avoid losing data, too, so we conducted 10+ practical Rclone examples – Rclone tutorial for beginners to get you started quicker.

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    Источник

    Creating environment fails with OSError: [Errno 5] Input/output error #1584

    Comments

    To create a a virtual environment tox runs /usr/local/bin/python -m virtualenv —no-download —python /usr/local/bin/python py37 . The command fails with an error

    Apparently it believes a symlink isn’t created. Here’s an strace output:

    It is worth noting tox fails only in a container (from a public image python:3.7 ) and runs fine on a host MacOS machine.
    All virtualenv 20.* versions are affected. Version 16.7.9 works fine.

    The text was updated successfully, but these errors were encountered:

    Workaround in tox.ini

    Can you please also post a creation output of virtualenv with -vvv —with-traceback?

    Eh dockers doesn’t like hard links?

    Please confirm if you’re using docker from Mac and if so what version 🤔 thanks

    yes, it’s docker on MacOS

    $ uname -a
    Darwin ***.com 18.7.0 Darwin Kernel Version 18.7.0: Sun Dec 1 18:59:03 PST 2019; root:xnu-4903.278.19

    1/RELEASE_X86_64 x86_64 i386 MacBookPro15,1 Darwin

    I’ve also faced this on macOS 10.13.2 and Docker for Mac 2.2.0.0 while preparing reproducible app for another issue on failing tox and coverage in gitlab-runner. In that issue some unwanted symlinks from setuptools package get into coverage report and fail project stats.
    virtualenv-issue-1584.zip

    Another option is temporarily preinstall ‘virtualenv

    While I think this is a docker bug; I think it’s reasonable to fallback to symlink here https://github.com/pypa/virtualenv/blob/master/src/virtualenv/create/via_global_ref/builtin/ref.py#L121 if the hard link fails. If anyone can create a PR for it that would be great.

    Same issue in Ubuntu 18.04.4 LTS when creating a virtualenv on a FUSE mounted NTFS partition.

    Should be resolved via #1596

    Hello, a fix for this issue has been released via virtualenv 20.0.4; see https://pypi.org/project/virtualenv/20.0.4/ (https://virtualenv.pypa.io/en/latest/changelog.html#v20-0-4-2020-02-14). Please give a try and report back if your issue has not been addressed; if not, please comment here, and we’ll reopen the ticket. We want to apologize for the inconvenience this has caused you and say thanks for having patience while we resolve the unexpected bugs with this new major release.

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    Источник

    8. Errors and Exceptions¶

    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:

    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:

    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 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.

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    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 — 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 — the first matching except clause is triggered.

    When an exception occurs, it may have associated values, also known as the exception’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 exception’s __str__() output is printed as the last part (‘detail’) 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 … 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 wasn’t raised by the code being protected by the try … 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 Exceptions¶

    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 don’t intend to handle it, a simpler form of the raise statement allows you to re-raise the exception:

    8.5. Exception Chaining¶

    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 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.

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    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 “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.

    8.7. 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:

    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 statement’s execution.

    If a finally clause includes a return statement, the returned value will be the one from the finally clause’s return statement, not the value from the try clause’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 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.

    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 Exceptions¶

    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 Notes¶

    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 exception’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.

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