Todo

A Simple Todo Application With Python Django

Features Admin Panel Relational Model Able To Manage Admin Panel Able To Customize Admin Panel Able To Create Super Users Such as Admin Able To Use Any Type of Databases (Current Database is Sqlite3) Able To Add , Delete and Mark your Events as Completed in Your List Responsive Site (Optimization) Backend Security Language used in This Project   To finish reading, please visit source site

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Structure

Pie – A loose structured python project manager

Pie is a loose structured python project manager. A Loose structured and easy to use python project manager. Different sets ofcommands can be accessed by using the cli inside a project directory oroutside of it. Installation Install PIE Project Manager on pip pip install pie-manager pip3 install pie-manager Changelogs Changelogs Usage

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Remote

Apache APISIX Remote Code Execution (CVE-2022-24112) proof of concept exploit

Summary An attacker can abuse the batch-requests plugin to send requests tobypass the IP restriction of Admin API.A default configuration of Apache APISIX (with default API key) isvulnerable to remote code execution.When the admin key was changed or the port of Admin API was changed toa port different from the data panel, the impact is lower. But thereis still a risk to bypass the IP restriction of Apache APISIX’s datapanel. There is a check in the batch-requests plugin which overrides […]

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obfuscation

Advanced python obfuscator to obfuscate any python files using marshal, zlib, base64, base32, base16, base85 and many others

Python obfuscator / Python encoder / Python encrypter to obfuscate, encode, encrypt any python files using marshal, zlib, base64, base32, base16, base85 and many others. Download Python 3.6 and + (https://www.python.org) Simply browse and get your python file. Then enter the amount of time Monkey will obfuscate your python file (1 TIME IS RECOMMENDED). You can also add walls which will protect even more your source code and annoy people that will try to deobfuscate it. GitHub View Github   […]

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Remove

scAR (single-cell Ambient Remover) is a package for data denoising in single-cell omics

scAR (single cell Ambient Remover) is a package for denoising multiple single cell omics data. It can be used for multiple tasks, such as, sgRNA assignment for scCRISPRseq, identity barcode assignment for cell indexing, protein denoising for CITE-seq, mRNA denoising for scRNAseq, and etc… It is built using probabilistic deep learning, illustrated as follows: Installation Clone this repository, $ git clone https://github.com/CaibinSh/scAR.git To install the dependencies, create a conda environment:

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Various

Handy python interfaces to various lab test equipment

Florian DupeyronOctober 2021-January 2022 Making this work on linux Copy the udev rules : $ sudo cp udev/*.rules /etc/udev/rules.d $ sudo udevadm control –reload $ sudo udevadm trigger For usbtmc devices, create the usbtmc group and add your user to it: sudo groupadd usbtmc sudo usermod -aG usbtmc $USER Restart your session Initialize a python virtual environment inside the directory (you may need to install a distribution package): $ python3    

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Proxy

Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?

Pdf: Arxiv, Openreview Code for our ICLR 2022 paper where we show that synthetic data from diffusion models can provide a tremendous boost in the performance of robust training. We also provide synthetic data used in the paper for all five datasets, namely CIFAR-10, CIFAR-100, ImageNet, CelebA, and AFHQ. We also provide synthetic data from seven different generative models for CIFAR-10, which was used to analyze impact of different generative models in section 3.2. Despite being minimalistic, this codebase also […]

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