This is a formal request to add the Bandit security linter project to the PyCQA. It’s currently part of the OpenStack umbrella, but myself as a core maintainer and others have general agreement that it would better be suited under the PyCQA since this is a tool used to create more quality code and has very little to do with OpenStack.
The code can be found on GitHub here:
But that repo is a mirror of:
Let me know if you have any more questions. Thanks!
I hope you are doing fine. I just have a question, and thought you might
have an idea on it. I have some large images (i.e. 1000x1000 pixels), and
would like to train a convolutional neural network on those images.
I used a GPU instance from Amazon Web Service (AWS), but the training takes
much time, although I picked a kind of fast instance.
My question is, would there be a better way to train such large images,
especially that they will be increasing in number day after day, and thus
expecting to have a kind of large dataset.
At the moment, I'm feeding all my data to the network and waiting until all
the epochs run on the dataset. I thought of may running the epochs on
smaller numbers, saving the model, and building on that, but for the first
small images I used, I got the accuracy of "0", and wasn't thus sure of the
reliability of using this model for the next batch of images.
Is there a way to train a large dataset with large images better than just
feeding all the data in the network and waiting, which might sometimes take
day, or that would be the normal case, and what I'm currently doing
(feeding all the dataset) would be the correct way?
Thanks so much, and apologize for my disturbance.
Hello PyCQA members,
As an update to my earlier email conversation, I'm happy to announce
snekchek (IzunaDevs/SnekChek) is getting close to being stable enough to
use for most users. I'm aware the discord-python org is already using it
for most projects, and they've been a great source of errors and debugging,
as well as possible issues that could be caused.
Furthermore, a user has made a plugin for Atom to use snekchek, over at
I look forward to hearing from you, also regarding points from my first
email (which was with Ian Stapleton)
I have what I think may be a bug in flake8. Consider this source file, test.py:
len([1, 2, 3]),
Notice that the two blocks only differ in the call to "len." If I run
flake8 on it:
$ flake8 test.py
test.py:6:5: E122 continuation line missing indentation or outdented
It passes without errors if I move the "]" on line 6 to under the
open-quote in 'c'.
I believe this file should pass flake8 without errors. But, if it
doesn't, it should have two errors, not one.
$ python -V
$ flake8 --version
3.5.0 (mccabe: 0.6.1, pycodestyle: 2.3.1, pyflakes: 1.6.0) CPython
3.5.2 on Linux
Also replicated on a fresh Docker container based on ubuntu:bionic
with Python 3.6.4 (nothing installed but the base image, python3,
python3-pip, and the pypi version of flake8).
I've been using pyflakes and now flake8 for a while and honestly it's
probably the second-most used program on my computer, second only to
Python. I am a very happy customer and want to extend my warmest
gratitude to the creators and maintainers!
I have a suggestion which I suspect is already implemented I just don't
know how to find the option:
Using Flake8, I want to be able to set up globals like you can with
eslint. This should allow me to say that there are globals present in
the file which aren't currently there.
I get that the use case is kind of non standard: I am evaling code found
in an arbitrary, and of coruse that code is inheriting the globals and
locals from the main script. To this end, I want to be able to do more
than just put # noqa: F821 at the end of each line that contains one of
the locals.. that is very inconvenient and runs the high risk of
suppressing a real live issue.
Is this already done? If not should I open an issue on Gitlab?
I'd be more than happy to dig in and try make a fix for this myself but
I have no idea how flake8 works ETC, so if I could be given some
pointers on where to start that would be awesome, even if those pointers
are simply RTFM! :)
Thank you all so much, and I hope everyone is having a wonderful day.