Segmentation fault python linux

Understanding Segmentation Fault in Python: Causes and Solutions

A segmentation fault, also known as a segfault, is a common error that can occur in programming languages, including Python. In this blog, we will discuss what a segmentation fault is, why it occurs, and how to troubleshoot and fix it in Python.

What is a Segmentation Fault?

A segmentation fault occurs when a program tries to access a memory location that it is not allowed to access, or when it tries to write to a read-only memory location. This can happen when a program tries to access memory that has already been freed or when it tries to access memory that is outside the bounds of an array.

In Python, segmentation faults can occur when using C extensions, which allow Python to interact with native libraries and code. These extensions can be written in C or C++ and can provide significant performance benefits to Python programs. However, if these extensions are poorly written or contain bugs, they can cause segmentation faults.

Examples of Segmentation Faults in Python

Let’s look at some examples of how segmentation faults can occur in Python.

Example 1: Accessing Invalid Memory Location

In this example, we are trying to access an index that is outside the bounds of the a list. This will result in a segmentation fault because the program is trying to access memory that it is not allowed to access.

Example 2: Using C Extensions

import numpy as np a = np.zeros((10000000,)) a[10000000] = 1

In this example, we are using the NumPy library to create a large array and then attempting to write to an index that is outside the bounds of the array. This can cause a segmentation fault because the NumPy library is implemented in C and is using C code to access memory.

Can python segmentation fault be caused due to limited memory?

Yes, a segmentation fault can be caused in Python due to limited memory. When a program runs out of memory, it can result in a segmentation fault or a memory access violation.

Let’s consider an example to illustrate this:

def create_large_list(): lst = [] for i in range(100000000): lst.append(i) return lst large_list = create_large_list()

In this example, we are creating a large list with 100 million elements using the create_large_list() function. If we run this program on a machine with limited memory, such as a Raspberry Pi with only 1 GB of RAM, the program will eventually run out of memory and result in a segmentation fault.

To avoid such issues, it is important to keep track of memory usage in your Python programs and avoid creating large data structures or processing large amounts of data if your machine does not have sufficient memory. You can also use tools like memory profilers to identify memory leaks or areas of your code that are using too much memory.

Troubleshooting and Fixing Segmentation Faults

If you encounter a segmentation fault in your Python program, there are several steps you can take to troubleshoot and fix the issue:

1. Identify the source of the segmentation fault: Use a debugger or traceback to determine which line of code is causing the segmentation fault.
2. Check for out-of-bounds array access: Make sure that you are not trying to access memory that is outside the bounds of an array.
3. Check for memory leaks: Make sure that you are not trying to access memory that has already been freed.
4. Check C extensions: If you are using C extensions in your Python program, make sure they are properly written and do not contain bugs that could cause segmentation faults.
5. Use a linter and follow best practices: Use a linter to check your code for errors and follow best practices to avoid common programming mistakes that can lead to segmentation faults.

Conclusion

In conclusion, segmentation faults can occur in Python when a program tries to access memory that it is not allowed to access. These errors can be caused by a variety of issues, including out-of-bounds array access, memory leaks, and poorly written C extensions. By following best practices and using debugging tools, you can identify and fix segmentation faults in your Python programs.

Источник

Segmentation fault while installing Python 3.5: ensurepip

$ guettli@p15:~$ pyenv install 3.5.8 Downloading Python-3.5.8.tar.xz. -> https://www.python.org/ftp/python/3.5.8/Python-3.5.8.tar.xz Installing Python-3.5.8. BUILD FAILED (Ubuntu 21.10 using python-build 20180424) Inspect or clean up the working tree at /tmp/python-build.20211119144903.305257 Results logged to /tmp/python-build.20211119144903.305257.log Last 10 log lines: if test "xupgrade" != "xno" ; then \ case upgrade in \ upgrade) ensurepip="--upgrade" ;; \ install|*) ensurepip="" ;; \ esac; \ ./python -E -m ensurepip \ $ensurepip --root=/ ; \ fi Segmentation fault (core dumped) 

The same happens, when I install Python-3.5.10.tar.xz (without pyenv). What can I do now? Version: Ubuntu 21.10
Output of configure : https://pastebin.com/rie17s8Z
Output of make : https://pastebin.com/F3C4evR6
Output of make install : https://paste2.org/LKxHUYkM With PYTHONFAULTHANDLER:

guettli@p15:~/Downloads/Python-3.5.10$ PYTHONFAULTHANDLER=1 LANG=C python3.5 -m ensurepip Fatal Python error: Segmentation fault Current thread 0x00007fb703b40740 (most recent call first): File "/usr/local/lib/python3.5/ctypes/__init__.py", line 276 in _reset_cache File "/usr/local/lib/python3.5/ctypes/__init__.py", line 541 in File "", line 222 in _call_with_frames_removed File "", line 697 in exec_module File "", line 673 in _load_unlocked File "", line 957 in _find_and_load_unlocked File "", line 968 in _find_and_load File "/usr/local/lib/python3.5/uuid.py", line 464 in File "", line 222 in _call_with_frames_removed File "", line 697 in exec_module File "", line 673 in _load_unlocked File "", line 957 in _find_and_load_unlocked File "", line 968 in _find_and_load File "/tmp/tmppx73eqwt/pip-9.0.1-py2.py3-none-any.whl/pip/_vendor/requests/packages/urllib3/filepost.py", line 4 in File "", line 634 in _load_backward_compatible File "", line 664 in _load_unlocked File "", line 957 in _find_and_load_unlocked File "", line 968 in _find_and_load File "/tmp/tmppx73eqwt/pip-9.0.1-py2.py3-none-any.whl/pip/_vendor/requests/packages/urllib3/request.py", line 7 in File "", line 634 in _load_backward_compatible File "", line 664 in _load_unlocked File "", line 957 in _find_and_load_unlocked File "", line 968 in _find_and_load File "/tmp/tmppx73eqwt/pip-9.0.1-py2.py3-none-any.whl/pip/_vendor/requests/packages/urllib3/connectionpool.py", line 41 in File "", line 634 in _load_backward_compatible File "", line 664 in _load_unlocked File "", line 957 in _find_and_load_unlocked File "", line 968 in _find_and_load File "/tmp/tmppx73eqwt/pip-9.0.1-py2.py3-none-any.whl/pip/_vendor/requests/packages/urllib3/__init__.py", line 8 in File "", line 634 in _load_backward_compatible File "", line 664 in _load_unlocked File "", line 957 in _find_and_load_unlocked File "", line 968 in _find_and_load File "", line 222 in _call_with_frames_removed File "", line 1015 in _handle_fromlist File "/tmp/tmppx73eqwt/pip-9.0.1-py2.py3-none-any.whl/pip/_vendor/requests/packages/__init__.py", line 27 in File "", line 634 in _load_backward_compatible File "", line 664 in _load_unlocked File "", line 957 in _find_and_load_unlocked File "", line 968 in _find_and_load File "", line 222 in _call_with_frames_removed File "", line 943 in _find_and_load_unlocked File "", line 968 in _find_and_load File "", line 222 in _call_with_frames_removed File "", line 943 in _find_and_load_unlocked File "", line 968 in _find_and_load File "/tmp/tmppx73eqwt/pip-9.0.1-py2.py3-none-any.whl/pip/_vendor/requests/__init__.py", line 62 in File "", line 634 in _load_backward_compatible File "", line 664 in _load_unlocked File "", line 957 in _find_and_load_unlocked File "", line 968 in _find_and_load File "", line 222 in _call_with_frames_removed File "", line 943 in _find_and_load_unlocked File "", line 968 in _find_and_load File "", line 222 in _call_with_frames_removed File "", line 943 in _find_and_load_unlocked File "", line 968 in _find_and_load File "", line 222 in _call_with_frames_removed File "", line 943 in _find_and_load_unlocked File "", line 968 in _find_and_load File "/tmp/tmppx73eqwt/pip-9.0.1-py2.py3-none-any.whl/pip/__init__.py", line 21 in File "", line 634 in _load_backward_compatible File "", line 664 in _load_unlocked File "", line 957 in _find_and_load_unlocked File "", line 968 in _find_and_load File "/usr/local/lib/python3.5/ensurepip/__init__.py", line 40 in _run_pip File "/usr/local/lib/python3.5/ensurepip/__init__.py", line 116 in bootstrap File "/usr/local/lib/python3.5/ensurepip/__init__.py", line 209 in _main File "/usr/local/lib/python3.5/ensurepip/__main__.py", line 4 in File "/usr/local/lib/python3.5/runpy.py", line 85 in _run_code File "/usr/local/lib/python3.5/runpy.py", line 193 in _run_module_as_main Segmentation fault (core dumped) 

Источник

Error: Segmentation fault (core dumped)

This part of code is reading from a program’s stdout.When i execute myfunc out of the thread it works ! But when i execute it in the thread fais. Any suggestion?

@JasonSperske: Yes, but the question is which one—if it’s queue.Queue , it’s probably a Python configuration problem, and the best solution is to uninstall and reinstall Python; if it’s foomodule.Queue , it’s likely to be a bug in the foo library.

9 Answers 9

«Segmentation fault (core dumped)» is the string that Linux prints when a program exits with a SIGSEGV signal and you have core creation enabled. This means some program has crashed.

If you’re actually getting this error from running Python, this means the Python interpreter has crashed. There are only a few reasons this can happen:

1. You’re using a third-party extension module written in C, and that extension module has crashed.
2. You’re (directly or indirectly) using the built-in module ctypes , and calling external code that crashes.
3. There’s something wrong with your Python installation.
4. You’ve discovered a bug in Python that you should report.

The first is by far the most common. If your q is an instance of some object from some third-party extension module, you may want to look at the documentation.

Often, when C modules crash, it’s because you’re doing something which is invalid, or at least uncommon and untested. But whether it’s your «fault» in that sense or not — that doesn’t matter. The module should raise a Python exception that you can debug, instead of crashing. So, you should probably report a bug to whoever wrote the extension. But meanwhile, rather than waiting 6 months for the bug to be fixed and a new version to come out, you need to figure out what you did that triggered the crash, and whether there’s some different way to do what you want. Or switch to a different library.

On the other hand, since you’re reading and printing out data from somewhere else, it’s possible that your Python interpreter just read the line «Segmentation fault (core dumped)» and faithfully printed what it read. In that case, some other program upstream presumably crashed. (It’s even possible that nobody crashed—if you fetched this page from the web and printed it out, you’d get that same line, right?) In your case, based on your comment, it’s probably the Java program that crashed.

If you’re not sure which case it is (and don’t want to learn how to do process management, core-file inspection, or C-level debugging today), there’s an easy way to test: After print line add a line saying print «And I’m OK» . If you see that after the Segmentation fault line, then Python didn’t crash, someone else did. If you don’t see it, then it’s probably Python that’s crashed.

Источник