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Python Programming

Submitted by Roy Schestowitz on Monday 28th of October 2019 12:27:49 AM Filed under
Development
  • Deploying with Docker and uWSGI

    While I am not going to say that I am expert with Docker by any means. This is just an analysis and example on how I plan on deploying uWSGI containers within Docker containers. I highly recommend reading my previous article from today for some additional context on my thoughts behind docker. With that said, let's get started.

  • Paolo Amoroso: How to Use Kivy on Repl.it

    I made the Kivy Python cross-platform GUI framework work in a GFX REPL on Repl.it. Repl.it is a multi-language cloud IDE with good support for Python.

    To use Kivy on Repl.it, just create a Pygame REPL, which is among the Kivy dependencies, and install Kivy with the package manager or by adding kivy to requirements.txt. Starting such a REPL in a new session takes a while to download and build the required libraries, at least several minutes. So be patient.

  • Python and Docker development

    Now, Docker isn't with it's security flaws as I recently found out. Basically, if a hacker gains access to an account which is part of the docker group on Linux, they can easily gain full root access to that system. Some may argue however, that once a hacker does get in, it is normally best to completely wipe that machine and reinstall from scratch, as there is no telling what the hacker may have done, or exploited. However, it is still best to have proper barriers in place to prevent an unauthorized person from gaining root in the first place. This way, you can still recover whatever data is on that machine with at least some certainty that it has not been tampered with. You will of course want to scrub said data and perhaps compare it to a recent backup to confirm it can be imported into the newly created machine. Basically, any user in the docker group on Linux has full access to the docker daemon to manage the images and containers. With this ability, you easily use a bind volume to map the entire root file system into the docker container, which will actually then give you full read/write access to the entire system. A hacker can then proceed to change the root password, modify various system files, and generally cause damage which could have otherwise been avoided if docker wasn't exposed. When I normally configure a Linux server, I do not install sudo, or any packages which otherwise could be abused to gain root. However, I am soon planning on using Docker on my current cloud servers as a partial experiment, and partially because I do not have enough time to upgrade my software from an aging Debian server. However, I will not be placing any user in the docker group, and instead using the stellar SaltStack, and their docker states to configure the containers on the cloud server. This provides a nice isolation between user and system processes.

»

Debugging TensorFlow coverage

Submitted by Roy Schestowitz on Monday 28th of October 2019 12:39:00 AM.
  • Debugging TensorFlow coverage

    It started with a coverage.py issue: Coverage not working for TensorFlow Model call function. A line in the code is executing, but coverage.py marks it as unexecuted. How could that be?

    TensorFlow was completely new to me. I knew it had some unusual execution semantics, but I didn’t know what it involved. What could it be doing that would interfere with coverage measurement? Once I had instructions to reproduce the issue, I could see that it was true: a line that clearly printed output during the test run was marked as unexecuted.

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