Api for getting bin info and getting encrypted card details for adyen.

Overview

Bin Info And Adyen Cse Enc Python

api for getting bin info and getting encrypted card details for adyen.

GitHub stars GitHub forks Maintenance Website shields.io Ask Me Anything ! License

Installation

Local Installation

git clone http://www.github.com/r0ld3x/adyen-enc-and-bin-info
cd adyen-enc-and-bin-info
pip install -r requirements.txt
uvicorn index:app

Deploy

Usage

website.com = your heroku website name

BIN INFO:-

curl -X 'GET' \
  'https://adyen-enc-and-bin-info.herokuapp.com/bin/458578' \
  -H 'accept: application/json'

Request URL: https://adyen-enc-and-bin-info.herokuapp.com/bin/458578 Return:

{
  "bin": "458578",
  "bank": "PJSC CB EUROBANK",
  "country_iso": "UA",
  "country": "UA",
  "flag": "🇺🇦",
  "vendor": "VISA",
  "type": "DEBIT",
  "level": "CLASSIC",
  "prepaid": false
}

Return status code 200 if success else return 404 if bin not found

ADYEN ENC:-

curl -X 'POST' \
  'https://adyen-enc-and-bin-info.herokuapp.com/adyen/' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "card": 5415900002240330,
  "month":7,
  "year": 2024,
  "cvv": 544,
  "adyen_key": "10001|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
  "adyen_version": "_0_1_25"
}'

Request URL: https://adyen-enc-and-bin-info.herokuapp.com/bin/458578 Return:

{
  "card": "adyenjs_0_1_25%24pd91Sl9SF1eTx%2BZrn3b9uL8dh%2BmO6HJrNQsf%2BmQ%2F2185qXMACyys4OCwKEpeBuT9j4%2FdLCfqeVGS0gdRIZRKDLvO689pTqvFnJ1tTiXwEEYkvCJ73bSGjPzPNexi%2FWo3KmoiAPWLwHWf514AKSCb1luoztp%2BZKxpg6IuqwQR%2FtsFBkrq761AQw6TwMtMxSr%2Fzs%2Fl6WjkTOBv5GviiKKHjOCpr1Y5eMv6t%2F9cjuDIYF9AWNx4F9o4qraNeAKl%2BVjs%2Fpm9aFV16QeYWpvjO24Rpb865V6%2BgQJW%2F8I8jRbpy6wlS3Mo%2FOSUBrOZqcrw8GBn8Qtf8q74kUXRdhtywGQ%2Bgg%3D%3D%2465MDJ9nl42hYDvxIYIow9ydXvjc3HPHXZFziT8yCuulYjzpQU7QXPJcev0eP35n5k5KIRbep5zxVX6ZX3n8saXsWwwKiZhonmtPbzSmc6T262Zc%2FJmW8K6mofH7qyteM",
  "month": "adyenjs_0_1_25%24lpdea4MvYqJm4YRdufTpwKGiem3UqLHia4kJ0Q5rb6uvNyKlL9J18M9HPYH%2F3Y37lbmPIgMmGNCYoK5%2BaTj5uquRtQ1njRP55T%2F6EudhpIQMKYaw4M6gQjdIrqosVplnps%2FD%2BnmuwHJM0DWIzZC8z30ZCz4Sl6RFBL3DPj0OhvjR9MvoAUwOHqJYc%2FF9zmtTq8vA5XCYAhVisBiqX7fj547almWBEcthyYw6LEg3BYMcs4MdJahEwUa17zDDKwLlLhvkI3m0qsDc8cTFjmYtnTsxVVSEttbUe0ljQJfVrRRPtcMGHNSA5JzWGf5mMfevjciQeAXRVFolIG6283qUnw%3D%3D%24%2FjDUAJFl4B1563Tw2p76GjeHnz03b0jhFrINlCYln1v81Omn4BbnEGnp7dzD3dpx6krXpg0P%2FCq1i1lEnG4B1v1texUPMUZ9%2Bm6AT0QUI3u%2BeuJ%2BxDs%3D",
  "year": "adyenjs_0_1_25%24btmuqQyBocIYHkfdrzowdn5EeJMsrmMcbSUX6DtlOA4Gu%2BlrNunyCwsovndkApfE6A9PYTCrsqUkJ%2F4iDizHkX4Ri%2FY24UfGjUzDbUjyHzhlM3f3ktgU4afyPT3Nb%2FoMf7gbreBJApdbxxh4Zz5jh%2BOb2znoEMM0MgoQ0HTVDy7CkNEKtbYxA72g1rz32lVJHlnTE7Urd2NkQVR5j6Js9PVkNfwRLiUUnZJN6p68WcShP0nUiptciJnMiP%2F3W6LgsQ9rS9PKCxcySSqXaW2ncgXX2pRgmCLjzR6yHKClzrcc%2BUqQ6D6br7vbACXv8OO877JGZVJp9lEqJ1tyQAZBnA%3D%3D%24s%2BlEPjpYoMMZIH8%2B75KqLOkCnKvajNHrNuEq8YmvCT3nw42cRQOASN5Xd34hWbdStKXQNfOVfD0RT64ebbXLJoHSvgB5nnwwB4Ps4n2aPWXbbK8789fY8w%3D%3D",
  "cvv": "adyenjs_0_1_25%24pwHRvu2ys6zXTUaabbjtXW6kZGZhojK1WoxqSFxkO44vvRZUzaIzWwost4mRvyaTE%2F%2FXv%2FSanWXPW4vCPJzqred%2F2atsz%2FzYuNBbUT9C1%2Bga9rgX7gXKRujS5lZFf18QXlG%2BBDERhtav1CuxbsMTmyaa4QLJ9BwohZgDHvEZW%2BOThw2yQTi5GlgwauTJbiw%2BCYgzKEqk24yeUSLQGKz4yD0R2wvILFJaWzV%2B0NBnMQ8ZWEdtTRL2PY%2BHHb9uwTMBJKcdZn7qDWGT6Acxjh4HMLaI5%2FkgCch6JRsUEq63L6ulqcw6kDYGCaCZ%2BFvPmPssNFzJK6IpX%2F%2BKESxfGPBIRQ%3D%3D%246WruUcmWAV4a2Ve3SKzjTx1usXSSIf3RiZxZkdMly%2Fc97CWO5pRsMiXGUlZyB8KKctoM0iiMacnPcPN%2F%2B1Iamw8z1xriaPCdeCuGCqwGx1o%3D"
}

Return enc_card,enc_month,enc_year,enc_cvv

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

• MADE BY > Roldex

License

MIT

Owner
Roldex Stark
BEYOND YOUR LIMITS
Roldex Stark
Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

François Chollet 16.2k Dec 30, 2022
Satellite labelling tool for manual labelling of storm top features such as overshooting tops, above-anvil plumes, cold U/Vs, rings etc.

Satellite labelling tool About this app A tool for manual labelling of storm top features such as overshooting tops, above-anvil plumes, cold U/Vs, ri

Czech Hydrometeorological Institute - Satellite Department 10 Sep 14, 2022
Open CV - Convert a picture to look like a cartoon sketch in python

Use the video https://www.youtube.com/watch?v=k7cVPGpnels for initial learning.

Sammith S Bharadwaj 3 Jan 29, 2022
My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot

Deep Q&A Table of Contents Presentation Installation Running Chatbot Web interface Results Pretrained model Improvements Upgrade Presentation This wor

Conchylicultor 2.9k Dec 28, 2022
The code of “Similarity Reasoning and Filtration for Image-Text Matching” [AAAI2021]

SGRAF PyTorch implementation for AAAI2021 paper of “Similarity Reasoning and Filtration for Image-Text Matching”. It is built on top of the SCAN and C

Ronnie_IIAU 149 Dec 22, 2022
Marine debris detection with commercial satellite imagery and deep learning.

Marine debris detection with commercial satellite imagery and deep learning. Floating marine debris is a global pollution problem which threatens mari

Inter Agency Implementation and Advanced Concepts 56 Dec 16, 2022
Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness

Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness Code for Paper "Imbalanced Gradients: A Subtle Cause of Overestimated Adv

Hanxun Huang 11 Nov 30, 2022
TensorFlow CNN for fast style transfer

Fast Style Transfer in TensorFlow Add styles from famous paintings to any photo in a fraction of a second! It takes 100ms on a 2015 Titan X to style t

1 Dec 14, 2021
Fully Convolutional DenseNets for semantic segmentation.

Introduction This repo contains the code to train and evaluate FC-DenseNets as described in The One Hundred Layers Tiramisu: Fully Convolutional Dense

485 Nov 26, 2022
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks

Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi

Giacomo Arcieri 1 Mar 21, 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
Image processing in Python

scikit-image: Image processing in Python Website (including documentation): https://scikit-image.org/ Mailing list: https://mail.python.org/mailman3/l

Image Processing Toolbox for SciPy 5.2k Dec 31, 2022
Fast, Attemptable Route Planner for Navigation in Known and Unknown Environments

FAR Planner uses a dynamically updated visibility graph for fast replanning. The planner models the environment with polygons and builds a global visi

Fan Yang 346 Dec 30, 2022
Recurrent Scale Approximation (RSA) for Object Detection

Recurrent Scale Approximation (RSA) for Object Detection Codebase for Recurrent Scale Approximation for Object Detection in CNN published at ICCV 2017

Yu Liu (Louis) 239 Dec 28, 2022
Training and Evaluation Code for Neural Volumes

Neural Volumes This repository contains training and evaluation code for the paper Neural Volumes. The method learns a 3D volumetric representation of

Meta Research 370 Dec 08, 2022
Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard.

Sarus published models Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are

Sarus Technologies 39 Aug 19, 2022
Algo-burn - Script to configure an Algorand address as a "burn" address for one or more ASA tokens

Algorand Burn Address This is a simple script to illustrate how a "burn address"

GSD 5 May 10, 2022
Example repository for custom C++/CUDA operators for TorchScript

Custom TorchScript Operators Example This repository contains examples for writing, compiling and using custom TorchScript operators. See here for the

106 Dec 14, 2022
The repo for reproducing Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study

ECIR Reproducibility Paper: Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study This code corresponds to the reproducibility

ielab 3 Mar 31, 2022
The code for "Deep Level Set for Box-supervised Instance Segmentation in Aerial Images".

Deep Levelset for Box-supervised Instance Segmentation in Aerial Images Wentong Li, Yijie Chen, Wenyu Liu, Jianke Zhu* Any questions or discussions ar

sunshine.lwt 112 Jan 05, 2023