Rescuing data from abrubt process termination in python.
Preventing data loss of your Python3 application. Keeps important data both duplicated in memory and on disk.
Usually, after a crash through e.g. a segmentation fault or a power outage, data of running applications is lost. In environments where this is problematic – e.g. when users should not loose their work or important data is collected –,
faultguard prevents data loss in two ways:
faultguardkeeps the selected data automatically backed up in a second process. This way, if your Python application crashes - even with a segmentation fault caused e.g. by an external library -, in most cases the backup process is still running and immediately provides its data to a rescue handling function that you can define. This even allows you to e.g. provide users with a custom graphical dialog informing about the crash and providing options for the recovered data.
faultguardcan save the selected data automatically in customizable time intervals to a file from which it can be recovered on the next application launch.
An example using all features of
faultguard can be found in
To secure an application data using
faultguard, you define a
launch function that receives a custom data dictionary from
faultguard. This dictionary, although working like a usual dictionary and accepting all content that can be serialized using
pickle, is automatically backed up as described above. If the guarded application crashes, the backup process launches a crash handler in form of a
rescue function also defined by you and provides it with the backed up dictionary. Additionally, if you provide
faultguard with a time interval and a path for autosaves, it stores the data on disk and you can call the
recover method to recover the file content and call your
faultguard will raise a
RuntimeError when trying to write to an existing autosave file or reading the autosave file of a running process.
faultguard interface is very simple - you just provide it with a
launch and a
rescue function and everything else works automatically. If you use autosaving, on application launch you should additionally check for backup files and use
is_active to see if the process corresponding to an autosave file is still active. If not, that would show that
faultguard did previously not exit properly, so you can then let
recover the file.
On the technical side, the in-memory backup is realized through Python modules
collections, which are used to serialize and deserialize various types of data and provide the dictionary-like data type that is available in both the guarded application and the rescue handler process.
The Python module
signal is used to ensure signals like keyboard interrupts are handled correctly and received by the guarded process.
The autosave functionality uses the Python module
lzma for efficient compression of autosave files,
os for file handling and
time for measuring the time since a process corresponding to a backup file was last active.
Feel encouraged to look into the source code and to contribute through (well documented :D ) pull requests!
Faultguard is tested on Linux and Windows.
This module is available via
pip install faultguard or can be installed manually via
setup.py, e.g. downloading the source code and running
pip install . inside the downloaded folder.
If a crash is observed frequently or reproducibly, it should be diagnosed – e.g. with
faulthandler (another Python module) and
gdb. If you somehow manage to generate a segmentation fault in the
faultguard data dictionary, and therefore destroy the guard process, the rescue will of course not work. Preventing faults from happening in the first place is always the most important, so don't rely solely on this module, just use it as an additional safety net!
This project was initially developed for a hardware project at the University of Münster.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Hashes for faultguard-1.1.1-py3-none-any.whl