Framework web SnakeServer.

Overview

SnakeServer - Framework Web 🐍

BADGE BADGE BADGE

Documentação oficial do framework SnakeServer.

Conteúdo

Sobre

O SnakeServer é um framework web sendo desenvolvido para Python com o foco em segurança. Nele, será possível receber solicitações GET e POST, definir headers de resposta, obter parâmetros de URL, retornar páginas HTML e outros tipos de conteúdo, e muitas outras funções.

Como contribuir

Veja como você pode ajudar no SnakeServer:

Enviar relatórios de segurança

Um dos nossos princípios é a segurança, para isso, semanalmente, diversos testes são feitos na última e penúltima versão lançada, para corrigir erros que possam comprometer o servidor.

Se você tem interesse em ajudar desta forma, acesse o arquivo PENTEST.txt para melhores informações.

Pull Requests

Revise o código, encontre bugs, erros, melhorias no código e faça seu pull request!

Todas as pull request são analisadas o mais rápido possível, sendo aceita caso o que você fez seja beneficiante para o código.

Primeiros passos

Aqui daremos o primeiro passo na criação de um servidor utilizando o SnakeServer!

Hello World

Veja um simples hello world utilizando nosso framework:

from snake import Snake

# Função que retorna um Hello World
def hello():
    return 'Hello World powered by SnakeServer!'

# Instanciando a classe Snake e definindo Host e Port
server = Snake(host='127.0.0.1', port=5500)

# Registrando rota e iniciando servidor
server.add_new_route(name='/', method='POST', target=hello)
server.start()

Para entender e aprender mais sobre o SnakeServer, acesse a documentação oficial.

Licença

MIT © 2021 Jaedson Silva

Owner
Jaedson Silva
Python developer in web area.
Jaedson Silva
Eth brownie struct encoding example

eth-brownie struct encoding example Overview This repository contains an example of encoding a struct, so that it can be used in a function call, usin

Ittai Svidler 2 Mar 04, 2022
SuperSDR: multiplatform KiwiSDR + CAT transceiver integrator

SuperSDR SuperSDR integrates a realtime spectrum waterfall and audio receive from any KiwiSDR around the world, together with a local (or remote) cont

Marco Cogoni 30 Nov 29, 2022
This is an official implementation of the paper "Distance-aware Quantization", accepted to ICCV2021.

PyTorch implementation of DAQ This is an official implementation of the paper "Distance-aware Quantization", accepted to ICCV2021. For more informatio

CV Lab @ Yonsei University 36 Nov 04, 2022
PyTorch implementation for paper "Full-Body Visual Self-Modeling of Robot Morphologies".

Full-Body Visual Self-Modeling of Robot Morphologies Boyuan Chen, Robert Kwiatkowskig, Carl Vondrick, Hod Lipson Columbia University Project Website |

Boyuan Chen 32 Jan 02, 2023
Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs

Project Learning Multiresolution Matrix Factorization and its Wavelet Networks on Graphs, https://arxiv.org/pdf/2111.01940.pdf. Authors Truong Son Hy

5 Jun 28, 2022
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac

12.9k Jan 09, 2023
This repository contains code used to audit the stability of personality predictions made by two algorithmic hiring systems

Stability Audit This repository contains code used to audit the stability of personality predictions made by two algorithmic hiring systems, Humantic

Data, Responsibly 4 Oct 27, 2022
😊 Python module for face feature changing

PyWarping Python module for face feature changing Installation pip install pywarping If you get an error: No such file or directory: 'cmake': 'cmake',

Dopevog 10 Sep 10, 2021
Cosine Annealing With Warmup

CosineAnnealingWithWarmup Formulation The learning rate is annealed using a cosine schedule over the course of learning of n_total total steps with an

zhuyun 4 Apr 18, 2022
Code corresponding to The Introspective Agent: Interdependence of Strategy, Physiology, and Sensing for Embodied Agents

The Introspective Agent: Interdependence of Strategy, Physiology, and Sensing for Embodied Agents This is the code corresponding to The Introspective

0 Jan 10, 2022
Source code for deep symbolic optimization.

Update July 10, 2021: This repository now supports an additional symbolic optimization task: learning symbolic policies for reinforcement learning. Th

Brenden Petersen 290 Dec 25, 2022
用opencv的dnn模块做yolov5目标检测,包含C++和Python两个版本的程序

yolov5-dnn-cpp-py yolov5s,yolov5l,yolov5m,yolov5x的onnx文件在百度云盘下载, 链接:https://pan.baidu.com/s/1d67LUlOoPFQy0MV39gpJiw 提取码:bayj python版本的主程序是main_yolov5.

365 Jan 04, 2023
A flexible framework of neural networks for deep learning

Chainer: A deep learning framework Website | Docs | Install Guide | Tutorials (ja) | Examples (Official, External) | Concepts | ChainerX Forum (en, ja

Chainer 5.8k Jan 06, 2023
State of the art Semantic Sentence Embeddings

Contrastive Tension State of the art Semantic Sentence Embeddings Published Paper · Huggingface Models · Report Bug Overview This is the official code

Fredrik Carlsson 88 Dec 30, 2022
Multilingual Image Captioning

Multilingual Image Captioning Authors: Bhavitvya Malik, Gunjan Chhablani Demo Link: https://huggingface.co/spaces/flax-community/multilingual-image-ca

Gunjan Chhablani 32 Nov 25, 2022
This repository contains the code used for Predicting Patient Outcomes with Graph Representation Learning (https://arxiv.org/abs/2101.03940).

Predicting Patient Outcomes with Graph Representation Learning This repository contains the code used for Predicting Patient Outcomes with Graph Repre

Emma Rocheteau 76 Dec 22, 2022
Rule based classification A hotel s customers dataset

Rule-based-classification-A-hotel-s-customers-dataset- Aim: Categorize new customers by segment and predict how much revenue they can generate This re

Şebnem 4 Jan 02, 2022
A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers.

ViTGAN: Training GANs with Vision Transformers A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers. Refer

Hong-Jia Chen 127 Dec 23, 2022
A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines

A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines Understanding the results of deep neural networks is

Johan van den Heuvel 2 Dec 13, 2021
End-to-end image segmentation kit based on PaddlePaddle.

English | 简体中文 PaddleSeg PaddleSeg has released the new version including the following features: Our team won the 6.2k Jan 02, 2023