I came across this interesting Python tool that helps with real-time face detection and emotion and gender classification. Here is a more complete brief description from the project page:
Real-time face detection and emotion/gender classification using fer2013/IMDB datasets with a keras CNN model and openCV.
- IMDB gender classification test accuracy: 96%.
- fer2013 emotion classification test accuracy: 66%.
PHP vs Python vs Ruby: Detailed Comparison compares the three popular languages in a variety of categories, such as total market share, large website deployments, usability, learning curve, popularity, performance, etc. It’s a nice overview if you are about to pick one of these languages for the future projects, or if you are (like me) have been stuck with one of them for a long time, and haven’t really kept an eye on what’s going on in the rest of the world.
O’Reilly is giving away some programming ebooks for free. Not the greatest of selections, but might still come handy, as subjects vary from Java and Python to micro-services and software architecture. The books are available in ePub, Mobi, and PDF, but you’ll need to register / login to download them.
httpoxy is a set of vulnerabilities that affect application code running in CGI, or CGI-like environments.
It comes down to a simple namespace conflict:
- RFC 3875 (CGI) puts the HTTP Proxy header from a request into the environment variables as HTTP_PROXY
- HTTP_PROXY is a popular environment variable used to configure an outgoing proxy
This leads to a remotely exploitable vulnerability. If you’re running PHP or CGI, you should block the Proxy header now.
If one your New Year’s resolutions was learning Python programming language, I’ve got a resource for you – “Python Introduction, Resources and FAQs” – an excellent list of resources from online tutorials and tools to books and videos.
Nick Coghlan writes:
One of the things we do as part of the Python core development process is to look at features we appreciate having available in other languages we have experience with, and see whether or not there is a way to adapt them to be useful in making Python code easier to both read and write. This means that learning another programming language that focuses more specifically on a given style of software development can help improve anyone’s understanding of that style of programming in the context of Python.
To aid in such efforts, I’ve provided a list below of some possible areas for exploration, and other languages which may provide additional insight into those areas.
The languages and areas are:
- Procedural programming: C, Rust, Cython
- Object-oriented data modelling: Java, C#, Eiffel
- Object-oriented C derivatives: C++, D
- Array-oriented data processing: MATLAB/Octave, Julia
- Statistical data analysis: R
- Computational pipeline modelling: Haskell, Scala, Clojure, F#
- Gradual typing: TypeScript
- Dynamic metaprogramming: Hy, Ruby
- Pragmatic problem solving: Lua, PHP, Perl
- Computational thinking: Scratch, Logo
ftfy – fixes text for you
ftfy makes Unicode text less broken and more consistent. It works in Python 2.7, Python 3.2, or later.
The most interesting kind of brokenness that this resolves is when someone has encoded Unicode with one standard and decoded it with a different one. This often shows up as characters that turn into nonsense sequences
textract – extract text from any document. Currently supports .doc, .docx, .eml, .json, .html, .pptx, .pdf, and .txt.
Remember all those links to awesome PHP, Python, and Sysadmin? Well, it was only a matter of time until the Awesome Awesomeness would be done by someone. Awesome Awesomeness is a curated list of curated awesome lists. Now you can follow a single list for all the awesomeness you can find.