PassAPI is a password generator in hash format and fully developed in Python, with the aim of teaching how to handle and build

Related tags

Deep LearningPassAPI
Overview

simple, elegant and safe

Introduction

PassAPI is a password generator in hash format and fully developed in Python, with the aim of teaching how to handle and build

  • Strong points:

    • Token verification by authorization header 🎉
    • Fully OpenSource 🎉
    • Already comes with ratelimit 🎉
    • Easy to understand 🎉
    • Frequently updated 🎉
  • Weak points:

    • Possible lack of functions, but we will update with time 🔍

Requirements

Recommended Python 3.6+

Developed in Python 3.10.1

Installation

$ pip install -r requirements.txt


--> 100%

Using

Starting

  • Starting the main.py, in your console it should work like this:
INFO:     Started server process [2364]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
INFO:     Uvicorn running on http://127.0.0.1:8080 (Press CTRL+C to quit)
  • Note: if this appears in your console, don't worry just add the hash in your .env
[!] You didn't generate a hash to protect your APIKEY, so we generated one for you!
 
[+] Here: "Hash"
[+] You should put it there in .env  

Using the PassAPI

  • You will need some application to inject the API (REST Client), for example:

    • REST Client which is an extension of Visual Studio Code
    • You can use FastAPI application by accessing your server url and adding /docs
      • http://127.0.0.1/docs
  • and others...

Testing

  • Here is an example POST (Using the REST Client):
POST http://127.0.0.1:8080/ HTTP/1.1
Content-Type: application/json
Authorization: "HASH"

{
    "length": 5
}
  • Output:
{
    "detail": [
      {
        "password":"phG[P",
        "timestamp":"2022-03-01 23:14:06"
      }
    ]
}
  • Note: The rate limit already configured is 50 requests in 1 minute, but you can change it in /src/routers/routers.py

License

PassAPI is released under the MIT License. Check LICENSE file for more information.

You might also like...
Build fully-functioning computer vision models with PyTorch
Build fully-functioning computer vision models with PyTorch

Detecto is a Python package that allows you to build fully-functioning computer vision and object detection models with just 5 lines of code. Inferenc

UMT is a unified and flexible framework which can handle different input modality combinations, and output video moment retrieval and/or highlight detection results.

Unified Multi-modal Transformers This repository maintains the official implementation of the paper UMT: Unified Multi-modal Transformers for Joint Vi

Finite difference solution of 2D Poisson equation. Can handle Dirichlet, Neumann and mixed boundary conditions.
Finite difference solution of 2D Poisson equation. Can handle Dirichlet, Neumann and mixed boundary conditions.

Poisson-solver-2D Finite difference solution of 2D Poisson equation Current version can handle Dirichlet, Neumann, and mixed (combination of Dirichlet

Neon: an add-on for Lightbulb making it easier to handle component interactions

Neon Neon is an add-on for Lightbulb making it easier to handle component interactions. Installation pip install git+https://github.com/neonjonn/light

A fast poisson image editing implementation that can utilize multi-core CPU or GPU to handle a high-resolution image input.
A fast poisson image editing implementation that can utilize multi-core CPU or GPU to handle a high-resolution image input.

Poisson Image Editing - A Parallel Implementation Jiayi Weng (jiayiwen), Zixu Chen (zixuc) Poisson Image Editing is a technique that can fuse two imag

An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results

EasyDatas An easy way to build PyTorch datasets. Modularly build datasets and automatically cache processed results Installation pip install git+https

Torch-ngp - A pytorch implementation of the hash encoder proposed in instant-ngp
Torch-ngp - A pytorch implementation of the hash encoder proposed in instant-ngp

HashGrid Encoder (WIP) A pytorch implementation of the HashGrid Encoder from ins

BTC-Generator - BTC Generator With Python

Что такое BTC-Generator? Это генератор чеков всеми любимого @BTC_BANKER_BOT Для

Simple ONNX operation generator. Simple Operation Generator for ONNX.
Simple ONNX operation generator. Simple Operation Generator for ONNX.

sog4onnx Simple ONNX operation generator. Simple Operation Generator for ONNX. https://github.com/PINTO0309/simple-onnx-processing-tools Key concept V

Releases(1.0.1)
Owner
Johnsz
Johnsz
A tool to estimate time varying instantaneous reproduction number during epidemics

EpiEstim A tool to estimate time varying instantaneous reproduction number during epidemics. It is described in the following paper: @article{Cori2013

MRC Centre for Global Infectious Disease Analysis 78 Dec 19, 2022
Serverless proxy for Spark cluster

Hydrosphere Mist Hydrosphere Mist is a serverless proxy for Spark cluster. Mist provides a new functional programming framework and deployment model f

hydrosphere.io 317 Dec 01, 2022
Method for facial emotion recognition compitition of Xunfei and Datawhale .

人脸情绪识别挑战赛-第3名-W03KFgNOc-源代码、模型以及说明文档 队名:W03KFgNOc 排名:3 正确率: 0.75564 队员:yyMoming,xkwang,RichardoMu。 比赛链接:人脸情绪识别挑战赛 文章地址:link emotion 该项目分别训练八个模型并生成csv文

6 Oct 17, 2022
Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch

Semantic Segmentation Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch Features Applicable to followin

sithu3 530 Jan 05, 2023
PyoMyo - Python Opensource Myo library

PyoMyo Python module for the Thalmic Labs Myo armband. Cross platform and multithreaded and works without the Myo SDK. pip install pyomyo Documentati

PerlinWarp 81 Jan 08, 2023
This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 2020

Classifier-Balancing This repository contains code for the paper: Decoupling Representation and Classifier for Long-Tailed Recognition Bingyi Kang, Sa

Facebook Research 820 Dec 26, 2022
Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently generate a wide range of illumination variants of a single image.

Deep Illuminator Deep Illuminator is a data augmentation tool designed for image relighting. It can be used to easily and efficiently generate a wide

George Chogovadze 52 Nov 29, 2022
Object-aware Contrastive Learning for Debiased Scene Representation

Object-aware Contrastive Learning Official PyTorch implementation of "Object-aware Contrastive Learning for Debiased Scene Representation" by Sangwoo

43 Dec 14, 2022
Pytorch implementation of winner from VQA Chllange Workshop in CVPR'17

2017 VQA Challenge Winner (CVPR'17 Workshop) pytorch implementation of Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challeng

Mark Dong 166 Dec 11, 2022
Scale-aware Automatic Augmentation for Object Detection (CVPR 2021)

SA-AutoAug Scale-aware Automatic Augmentation for Object Detection Yukang Chen, Yanwei Li, Tao Kong, Lu Qi, Ruihang Chu, Lei Li, Jiaya Jia [Paper] [Bi

DV Lab 182 Dec 29, 2022
Official implementation of Meta-StyleSpeech and StyleSpeech

Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation Dongchan Min, Dong Bok Lee, Eunho Yang, and Sung Ju Hwang This is an official code

min95 168 Dec 28, 2022
Adversarial Reweighting for Partial Domain Adaptation

Adversarial Reweighting for Partial Domain Adaptation Code for paper "Xiang Gu, Xi Yu, Yan Yang, Jian Sun, Zongben Xu, Adversarial Reweighting for Par

12 Dec 01, 2022
A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network"

DGC-Net: Dense Geometric Correspondence Network This is a PyTorch implementation of our work "DGC-Net: Dense Geometric Correspondence Network" TL;DR A

191 Dec 16, 2022
Pytorch implementation of

EfficientTTS Unofficial Pytorch implementation of "EfficientTTS: An Efficient and High-Quality Text-to-Speech Architecture"(arXiv). Disclaimer: Somebo

Liu Songxiang 109 Nov 16, 2022
Official implementation for the paper "SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization".

SAPE Project page Paper Official implementation for the paper "SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization". Environment Cre

36 Dec 09, 2022
Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

Varun Nair 37 Dec 30, 2022
Omnidirectional Scene Text Detection with Sequential-free Box Discretization (IJCAI 2019). Including competition model, online demo, etc.

Box_Discretization_Network This repository is built on the pytorch [maskrcnn_benchmark]. The method is the foundation of our ReCTs-competition method

Yuliang Liu 266 Nov 24, 2022
Code for "Single-view robot pose and joint angle estimation via render & compare", CVPR 2021 (Oral).

Single-view robot pose and joint angle estimation via render & compare Yann Labbé, Justin Carpentier, Mathieu Aubry, Josef Sivic CVPR: Conference on C

Yann Labbé 51 Oct 14, 2022
Official implementation for ICDAR 2021 paper "Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer"

Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer Description Convert offline handwritten mathematical expressi

Wenqi Zhao 87 Dec 27, 2022
Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.

Multi-Time Attention Networks (mTANs) This repository contains the PyTorch implementation for the paper Multi-Time Attention Networks for Irregularly

The Laboratory for Robust and Efficient Machine Learning 68 Dec 17, 2022