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
Syllabic Quantity Patterns as Rhythmic Features for Latin Authorship Attribution

Syllabic Quantity Patterns as Rhythmic Features for Latin Authorship Attribution Abstract Within the Latin (and ancient Greek) production, it is well

4 Dec 03, 2022
Official PyTorch Implementation of Embedding Transfer with Label Relaxation for Improved Metric Learning, CVPR 2021

Embedding Transfer with Label Relaxation for Improved Metric Learning Official PyTorch implementation of CVPR 2021 paper Embedding Transfer with Label

Sungyeon Kim 37 Dec 06, 2022
tensorflow implementation of 'YOLO : Real-Time Object Detection'

YOLO_tensorflow (Version 0.3, Last updated :2017.02.21) 1.Introduction This is tensorflow implementation of the YOLO:Real-Time Object Detection It can

Jinyoung Choi 1.7k Nov 21, 2022
Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap

Jonathan Choi 2 Mar 17, 2022
Image reconstruction done with untrained neural networks.

PyTorch Deep Image Prior An implementation of image reconstruction methods from Deep Image Prior (Ulyanov et al., 2017) in PyTorch. The point of the p

Atiyo Ghosh 192 Nov 30, 2022
A TensorFlow implementation of the Mnemonic Descent Method.

MDM A Tensorflow implementation of the Mnemonic Descent Method. Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment G.

123 Oct 07, 2022
PyTorch implementation of Weak-shot Fine-grained Classification via Similarity Transfer

SimTrans-Weak-Shot-Classification This repository contains the official PyTorch implementation of the following paper: Weak-shot Fine-grained Classifi

BCMI 60 Dec 02, 2022
Combining Diverse Feature Priors

Combining Diverse Feature Priors This repository contains code for reproducing the results of our paper. Paper: https://arxiv.org/abs/2110.08220 Blog

Madry Lab 5 Nov 12, 2022
[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator

involution Official implementation of a neural operator as described in Involution: Inverting the Inherence of Convolution for Visual Recognition (CVP

Duo Li 1.3k Dec 28, 2022
MBPO (paper: When to trust your model: Model-based policy optimization) in offline RL settings

offline-MBPO This repository contains the code of a version of model-based RL algorithm MBPO, which is modified to perform in offline RL settings Pape

LxzGordon 1 Oct 24, 2021
A "gym" style toolkit for building lightweight Neural Architecture Search systems

A "gym" style toolkit for building lightweight Neural Architecture Search systems

Jack Turner 12 Nov 05, 2022
Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!

Serpent.AI - Game Agent Framework (Python) Update: Revival (May 2020) Development work has resumed on the framework with the aim of bringing it into 2

Serpent.AI 6.4k Jan 05, 2023
An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available actions

Agar.io_Q-Learning_AI An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available act

1 Jun 09, 2022
Metric learning algorithms in Python

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

1.3k Dec 28, 2022
The implement of papar "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization"

SIGIR2021-EGLN The implement of paper "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization" Neural graph based Col

15 Dec 27, 2022
PyTorch implementation of ShapeConv: Shape-aware Convolutional Layer for RGB-D Indoor Semantic Segmentation.

Shape-aware Convolutional Layer (ShapeConv) PyTorch implementation of ShapeConv: Shape-aware Convolutional Layer for RGB-D Indoor Semantic Segmentatio

Hanchao Leng 82 Dec 29, 2022
Chinese named entity recognization with BiLSTM using Keras

Chinese named entity recognization (Bilstm with Keras) Project Structure ./ ├── README.md ├── data │   ├── README.md │   ├── data 数据集 │   │   ├─

1 Dec 17, 2021
python 93% acc. CNN Dogs Vs Cats ( Pytorch )

English | 简体中文(测试中...敬请期待) Cnn-Classification-Dog-Vs-Cat 猫狗辨别 (pytorch版本) CNN Resnet18 的猫狗分类器,基于ResNet及其变体网路系列,对于一般的图像识别任务表现优异,模型精准度高达93%(小型样本)。 项目制作于

apple ye 1 May 22, 2022
TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning

TransZero++ This repository contains the testing code for the paper "TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning" submitted

Shiming Chen 6 Aug 16, 2022
Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

PyTorch Implementation of Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers 1 Using Colab Please notic

Hila Chefer 489 Jan 07, 2023