Freecodecamp Scientific Computing with Python Certification; Solution for Challenge 2: Time Calculator

Overview

Assignment

Write a function named add_time that takes in two required parameters and one optional parameter:

  • a start time in the 12-hour clock format (ending in AM or PM)
  • a duration time that indicates the number of hours and minutes
  • (optional) a starting day of the week, case insensitive

The function should add the duration time to the start time and return the result.

If the result will be the next day, it should show (next day) after the time. If the result will be more than one day later, it should show (n days later) after the time, where "n" is the number of days later.

If the function is given the optional starting day of the week parameter, then the output should display the day of the week of the result. The day of the week in the output should appear after the time and before the number of days later.

Below are some examples of different cases the function should handle. Pay close attention to the spacing and punctuation of the results.

add_time("3:00 PM", "3:10")
# Returns: 6:10 PM

add_time("11:30 AM", "2:32", "Monday")
# Returns: 2:02 PM, Monday

add_time("11:43 AM", "00:20")
# Returns: 12:03 PM

add_time("10:10 PM", "3:30")
# Returns: 1:40 AM (next day)

add_time("11:43 PM", "24:20", "tueSday")
# Returns: 12:03 AM, Thursday (2 days later)

add_time("6:30 PM", "205:12")
# Returns: 7:42 AM (9 days later)

Do not import any Python libraries. Assume that the start times are valid times. The minutes in the duration time will be a whole number less than 60, but the hour can be any whole number.

Development

Write your code in time_calculator.py. For development, you can use main.py to test your time_calculator() function. Click the "run" button and main.py will run.

Testing

The unit tests for this project are in test_module.py. We imported the tests from test_module.py to main.py for your convenience. The tests will run automatically whenever you hit the "run" button.

Submitting

Copy your project's URL and submit it to freeCodeCamp.

Owner
Hellen Namulinda
JavaScript/Python Developer
Hellen Namulinda
Here I will explain the flow to deploy your custom deep learning models on Ultra96V2.

Xilinx_Vitis_AI This repo will help you to Deploy your Deep Learning Model on Ultra96v2 Board. Prerequisites Vitis Core Development Kit 2019.2 This co

Amin Mamandipoor 1 Feb 08, 2022
Weakly-supervised object detection.

Wetectron Wetectron is a software system that implements state-of-the-art weakly-supervised object detection algorithms. Project CVPR'20, ECCV'20 | Pa

NVIDIA Research Projects 342 Jan 05, 2023
Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.

Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner

NVIDIA Corporation 147 Dec 17, 2022
On the model-based stochastic value gradient for continuous reinforcement learning

On the model-based stochastic value gradient for continuous reinforcement learning This repository is by Brandon Amos, Samuel Stanton, Denis Yarats, a

Facebook Research 46 Dec 15, 2022
Cookiecutter PyTorch Lightning

Cookiecutter PyTorch Lightning Instructions # install cookiecutter pip install cookiecutter

Mazen 8 Nov 06, 2022
LRBoost is a scikit-learn compatible approach to performing linear residual based stacking/boosting.

LRBoost is a sckit-learn compatible package for linear residual boosting. LRBoost combines a linear estimator and a non-linear estimator to leverage t

Andrew Patton 5 Nov 23, 2022
Image to Image translation, image generataton, few shot learning

Semi-supervised Learning for Few-shot Image-to-Image Translation [paper] Abstract: In the last few years, unpaired image-to-image translation has witn

yaxingwang 49 Nov 18, 2022
Code for the paper Open Sesame: Getting Inside BERT's Linguistic Knowledge.

Open Sesame This repository contains the code for the paper Open Sesame: Getting Inside BERT's Linguistic Knowledge. Credits We built the project on t

9 Jul 24, 2022
Continual Learning of Long Topic Sequences in Neural Information Retrieval

ContinualPassageRanking Repository for the paper "Continual Learning of Long Topic Sequences in Neural Information Retrieval". In this repository you

0 Apr 12, 2022
PyTorch implementation of "ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global Context" (INTERSPEECH 2020)

ContextNet ContextNet has CNN-RNN-transducer architecture and features a fully convolutional encoder that incorporates global context information into

Sangchun Ha 24 Nov 24, 2022
Equivariant CNNs for the sphere and SO(3) implemented in PyTorch

Equivariant CNNs for the sphere and SO(3) implemented in PyTorch

Jonas Köhler 893 Dec 28, 2022
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110

RuiLiu 65 Dec 20, 2022
Files for a tutorial to train SegNet for road scenes using the CamVid dataset

SegNet and Bayesian SegNet Tutorial This repository contains all the files for you to complete the 'Getting Started with SegNet' and the 'Bayesian Seg

Alex Kendall 800 Dec 31, 2022
Fast and Easy Infinite Neural Networks in Python

Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural

Google 1.9k Jan 09, 2023
Training deep models using anime, illustration images.

animeface deep models for anime images. Datasets anime-face-dataset Anime faces collected from Getchu.com. Based on Mckinsey666's dataset. 63.6K image

Tomoya Sawada 61 Dec 25, 2022
A vision library for performing sliced inference on large images/small objects

SAHI: Slicing Aided Hyper Inference A vision library for performing sliced inference on large images/small objects Overview Object detection and insta

Open Business Software Solutions 2.3k Jan 04, 2023
Official implementation of the paper 'High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network' in CVPR 2021

LPTN Paper | Supplementary Material | Poster High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network Ji

372 Dec 26, 2022
fcn by tensorflow

Update An example on how to integrate this code into your own semantic segmentation pipeline can be found in my KittiSeg project repository. tensorflo

9 May 22, 2022
Implementation of the Point Transformer layer, in Pytorch

Point Transformer - Pytorch Implementation of the Point Transformer self-attention layer, in Pytorch. The simple circuit above seemed to have allowed

Phil Wang 501 Jan 03, 2023
Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation (ICCV 2021)

Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation Home | PyTorch BigGAN Discovery | TensorFlow ProGAN Regulariza

Yuxiang Wei 54 Dec 30, 2022