AWS provides a Python SDK, "Boto3" ,which can be used to access the AWS-account from the local.

Overview

Boto3 - The AWS SDK for Python

Boto3 is the Amazon Web Services (AWS) Software Development Kit (SDK) for Python, which allows Python developers to write software that makes use of services like Amazon S3, Amazon EC2, AWS Cost Explorer, AWS Lambda and many more services.

Python Version

Boto3 was deprecated for Python2.7 and henceforth it is recommended for the developers to use latest versions of Python or pin the version of Boto3.

Getting Started

Expecting to have a pre-setup of Python Environment over the local. Moving forward, make sure that if you are using Python3.x version, then you must have updated version of pip as well.

Use the following command to get pip:

sudo apt-get install python3-pip

NOTE:

If you're running Python 2.7.9+ or Python 3.4+, Congrats, you should already have pip installed.

Then the most crucial step is to install the latest version of Boto3 in the local.

python3 -m pip3 install boto3

After the installation of Boto3, set up of AWS – Credentials is must.

[default]
aws_access_key_id = YOUR_KEY
aws_secret_access_key = YOUR_SECRET_KEY

To check the credentials in your terminal, do this:

~/.aws/credentials

Next step is to set up the region where you want to work. To know more about AWS-Regions, navigate here.

For exploring the Cost Explorer using AWS-Boto3 , the region will be us-east-1 only.

So, set up the default region with ~/.aws/config

[default]
region = us-east-1

Alternate Method to Access AWS – ARN user!!!

The alternate method to connect with any AWS Account is to create an IAM role for a user and then with the help of ARN Credentials a Session-Token can be generated which can help us access the AWS with the help of Python-boto3-sdk

Same as above, we have multiple ways of connecting boto3 with our local. You can find them HERE

Moving forward to the in depth understanding of Cost Explorer API

Owner
Shreyas Srivastava
Cloud & DevOps Enthusiast | Python | C++ | AWS | Jenkins | REST API | Flask | Boto3 | Elastic Search | Kibana
Shreyas Srivastava
Checking fibonacci - Generating the Fibonacci sequence is a classic recursive problem

Fibonaaci Series Generating the Fibonacci sequence is a classic recursive proble

Moureen Caroline O 1 Feb 15, 2022
Survival analysis in Python

What is survival analysis and why should I learn it? Survival analysis was originally developed and applied heavily by the actuarial and medical commu

Cameron Davidson-Pilon 2k Jan 08, 2023
Real-time Neural Representation Fusion for Robust Volumetric Mapping

NeuralBlox: Real-Time Neural Representation Fusion for Robust Volumetric Mapping Paper | Supplementary This repository contains the implementation of

ETHZ ASL 106 Dec 24, 2022
Python implementation of "Elliptic Fourier Features of a Closed Contour"

PyEFD An Python/NumPy implementation of a method for approximating a contour with a Fourier series, as described in [1]. Installation pip install pyef

Henrik Blidh 71 Dec 09, 2022
Official implementation of "Learning Not to Reconstruct" (BMVC 2021)

Official PyTorch implementation of "Learning Not to Reconstruct Anomalies" This is the implementation of the paper "Learning Not to Reconstruct Anomal

Marcella Astrid 13 Dec 04, 2022
Simultaneous Demand Prediction and Planning

Simultaneous Demand Prediction and Planning Dependencies Python packages: Pytorch, scikit-learn, Pandas, Numpy, PyYAML Data POI: data/poi Road network

Yizong Wang 1 Sep 01, 2022
The project page of paper: Architecture disentanglement for deep neural networks [ICCV 2021, oral]

This is the project page for the paper: Architecture Disentanglement for Deep Neural Networks, Jie Hu, Liujuan Cao, Tong Tong, Ye Qixiang, ShengChuan

Jie Hu 15 Aug 30, 2022
Implementation of Neural Style Transfer in Pytorch

PytorchNeuralStyleTransfer Code to run Neural Style Transfer from our paper Image Style Transfer Using Convolutional Neural Networks. Also includes co

Leon Gatys 396 Dec 01, 2022
A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics, sequence features, and user profiles.

CCasGNN A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics,

5 Apr 29, 2022
The fastai book, published as Jupyter Notebooks

English / Spanish / Korean / Chinese / Bengali / Indonesian The fastai book These notebooks cover an introduction to deep learning, fastai, and PyTorc

fast.ai 17k Jan 07, 2023
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding

CLUES: Few-Shot Learning Evaluation in Natural Language Understanding This repo contains the data and source code for baseline models in the NeurIPS 2

Microsoft 29 Dec 29, 2022
The implementation of CVPR2021 paper Temporal Query Networks for Fine-grained Video Understanding, by Chuhan Zhang, Ankush Gupta and Andrew Zisserman.

Temporal Query Networks for Fine-grained Video Understanding 📋 This repository contains the implementation of CVPR2021 paper Temporal_Query_Networks

55 Dec 21, 2022
SphereFace: Deep Hypersphere Embedding for Face Recognition

SphereFace: Deep Hypersphere Embedding for Face Recognition By Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj and Le Song License SphereFa

Weiyang Liu 1.5k Dec 29, 2022
BlockUnexpectedPackets - Preventing BungeeCord CPU overload due to Layer 7 DDoS attacks by scanning BungeeCord's logs

BlockUnexpectedPackets This script automatically blocks DDoS attacks that are sp

SparklyPower 3 Mar 31, 2022
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).

APPNP ⠀ A PyTorch implementation of Predict then Propagate: Graph Neural Networks meet Personalized PageRank (ICLR 2019). Abstract Neural message pass

Benedek Rozemberczki 329 Dec 30, 2022
Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling

Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling Code for the paper: Greg Ver Steeg and Aram Galstyan. "Hamiltonian Dynamics with N

Greg Ver Steeg 25 Mar 14, 2022
GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery

GLODISMO: Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery This is the code to the paper: Gradient-Based Learn

3 Feb 15, 2022
CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection

CLOCs is a novel Camera-LiDAR Object Candidates fusion network. It provides a low-complexity multi-modal fusion framework that improves the performance of single-modality detectors. CLOCs operates on

Su Pang 254 Dec 16, 2022
Fine-Tune EleutherAI GPT-Neo to Generate Netflix Movie Descriptions in Only 47 Lines of Code Using Hugginface And DeepSpeed

GPT-Neo-2.7B Fine-Tuning Example Using HuggingFace & DeepSpeed Installation cd venv/bin ./pip install -r ../../requirements.txt ./pip install deepspe

Nikita 180 Jan 05, 2023
Official implementation of the paper "Steganographer Detection via a Similarity Accumulation Graph Convolutional Network"

SAGCN - Official PyTorch Implementation | Paper | Project Page This is the official implementation of the paper "Steganographer detection via a simila

ZHANG Zhi 1 Nov 26, 2021