Defense your python project/separated file by hiding it using encryption with remaining functionality and output ❕ This tool will be useful if you want to share your Python project/separated file without revealing its source code. All contents of the files are encrypted and cannot be read by a person, while this does not affect the functionality and the output of the code. 🛠 Usage: > cd ../SourceCodeDefencer >> python run_defencer.py ./path_target_project” readability=”32″> >> cd ../SourceCodeDefencer >> python run_defencer.py ./path_target_project ℹ️ℹ️ℹ️ […]

Code for GSF learning in offline Procgen. Note: The repo is under construction right now, some experiments might still be changed/ added. Since the dataset is very large due to operating on pixel observations, we provide a way to generate it from pre-trained PPO checkpoints instead of hosting 1Tb+ of data. Instructions Clone the repo Either train a PPO agent from scratch on 200 levels (see here: here), or download provided PPO checkpoints (same repo link). TLDR, you can run […]

This modest package contains various common humanization utilities, like turninga number into a fuzzy human-readable duration (“3 minutes ago”) or into ahuman-readable size or throughput. It is localized to: Bengali Brazilian Portuguese Catalan Danish Dutch European Portuguese Finnish French German Indonesian Italian Japanese Korean Persian Polish Russian Simplified Chinese Slovak Slovenian Spanish Swedish Turkish Ukrainian Vietnamese API reference https://python-humanize.readthedocs.io Usage Integer humanization

The original repository is now located on my own git-server at https://git.goodcleanfun.de/tmeissner/cocotb_with_ghdlIt is mirrored to github with every push, so both should be in sync. At the moment, this repo is in an early state and serves as a learning tool for me. So it contains a a lot of quirks and code which can be done much better by cocotb-professionals. A collection of examples of using cocotb for functional verification of VHDL designs with GHDL. This is a project […]

About Cohort Intelligence : Cohort Intelligence ( CI ) is an optimization technique. It attempts to model the behavior often observed in a self-organizing system in which candidates in a cohort interact and compete with one another in order to achieve shared goals. Each candidate tries to improve its own behavior by observing the behavior of every other candidate in that cohort. Each candidate in the cohort follows a certain behavior which may result in the improvement of its own […]

Assists with the construction of probability distributions built from expert elicited data for use in monte carlo simulations. Usage Until this is packaged for pip, copy elicit_distibutions.py in your code. Then: elicited is just a helper tool when using numpy and scipy, so you’ll need these too. import numpy as np import scipy Lognormal See Occurance and Applications for examples of lognormal distributions in nature. Expert: I have assets at risk that would generate a wide range of losses. Elicitor: […]

An enhanced version of extractJS with even more functionality Discover JavaScript files directly from the webpage Customizable for discovering various types of files Just clone this repository $ git clone https://github.com/Dev-Ali/extractJS_2.0.git Move to the cloned directory $ cd extractJS_2.0 $ python3 extractJS_2.0.py Just enter the URL and see the magic happen 😉 How it works Your contributions are highly appreciated. Reach out to me on twitter: @am_xali GitHub https://github.com/Dev-Ali/extractJS_2.0