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

Last update: Mar 02, 2022

Related tags

Deep Learning PassAPI

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:
- Postman
- Insomnia
- 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

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

576 Dec 29, 2022

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

Applied Research Center (ARC), Tencent PCG

84 Jan 4, 2023

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

34 Dec 23, 2022

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

9 Apr 29, 2022

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

110 Dec 27, 2022

Releases(1.0.1)

1.0.1(Mar 2, 2022)

First version PassAPI!
Source code(tar.gz)
Source code(zip)

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

Overview

Introduction

Requirements

Installation

Using

Starting

Using the PassAPI

Testing

License

You might also like...

Build fully-functioning computer vision models with PyTorch

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

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

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

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

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

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

BTC-Generator - BTC Generator With Python

Simple ONNX operation generator. Simple Operation Generator for ONNX.

Releases(1.0.1)

1.0.1(Mar 2, 2022)

Owner

Johnsz

A script helps the user to update Linux and Mac systems through the terminal

Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch

Learning Representational Invariances for Data-Efficient Action Recognition

A PyTorch implementation of Implicit Q-Learning

Demo code for paper "Learning optical flow from still images", CVPR 2021.

10th place solution for Google Smartphone Decimeter Challenge at kaggle.

2nd solution of ICDAR 2021 Competition on Scientific Literature Parsing, Task B.

Official repository of DeMFI (arXiv.)

A pytorch implementation of Reading Wikipedia to Answer Open-Domain Questions.

Causal-Adversarial-Instruments - PyTorch Implementation for Developing Library of Investigating Adversarial Examples on A Causal View by Instruments

[AAAI-2021] Visual Boundary Knowledge Translation for Foreground Segmentation

Official repository for Fourier model that can generate periodic signals

This is an official implementation for "Self-Supervised Learning with Swin Transformers".

Repository relating to the CVPR21 paper TimeLens: Event-based Video Frame Interpolation

Improving the robustness and performance of biomedical NLP models through adversarial training

A Pytorch Implementation of a continuously rate adjustable learned image compression framework.

This repository provides a PyTorch implementation and model weights for HCSC (Hierarchical Contrastive Selective Coding)

This code is a toolbox that uses Torch library for training and evaluating the ERFNet architecture for semantic segmentation.

Scripts for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation and a convolutional neural network (CNN) for image classification

Code for the paper "Can Active Learning Preemptively Mitigate Fairness Issues?" presented at RAI 2021.