✔️ Visual, reactive testing library for Julia. Time machine included.

Overview

PlutoTest.jl (alpha release)

Visual, reactive testing library for Julia

A macro @test that you can use to verify your code's correctness. But instead of just saying "Pass" or "Fail", let's try to show you why a test failed.

  • time travel to replay the execution step-by-step
  • ⭐️ multimedia display ⭐️ to make results easy to read

Demo screencap

Try this demo in your browser

Install & use

First, update Pluto to at least 0.15! That's it, Pluto will automatically install the package when you import/using it.

Inside your notebook, use the @test macro to test whether something returns true:

julia> using PlutoTest

julia> @test 1 + 1 == 2

This package is still an alpha release, don't use it to @test is_safe(crazy_new_bike_design).

Reactive

This testing library is designed to be used inside Pluto.jl, a reactive notebook. If you write your tests in the same notebook as your code, then Pluto will automatically re-run the affected tests after you make a change. Tests that are unaffected will not need to re-run. Neat!

Navigation

When a test gets re-run and it fails outside of your viewport, you will be notified with a red dot on the edge of the screen. You can click on a dot to jump to the test, multiple dots indicate multiple tests.

(Only enabled on Chrome and Firefox for now.)

Future: GitHub Action

In the future, it will be easy to run Pluto-based, PlutoTest-based tests automatically on GitHub Actions or Travis CI. In addition to running your tests, it will upload a rendered notebook as artifact to the test run (sample). If a test failed, you can open the notebook and see why.

How does it work?

Take a look at the source code! (It's a Pluto notebook 🌝 )

You might also like...
Pythonic particle-based (super-droplet) warm-rain/aqueous-chemistry cloud microphysics package with box, parcel & 1D/2D prescribed-flow examples in Python, Julia and Matlab
Pythonic particle-based (super-droplet) warm-rain/aqueous-chemistry cloud microphysics package with box, parcel & 1D/2D prescribed-flow examples in Python, Julia and Matlab

PySDM PySDM is a package for simulating the dynamics of population of particles. It is intended to serve as a building block for simulation systems mo

A numpy-based implementation of RANSAC for fundamental matrix and homography estimation. The degeneracy updating and local optimization components are included and optional.
A numpy-based implementation of RANSAC for fundamental matrix and homography estimation. The degeneracy updating and local optimization components are included and optional.

Description A numpy-based implementation of RANSAC for fundamental matrix and homography estimation. The degeneracy updating and local optimization co

Accelerated SMPL operation, commonly used in generate 3D human mesh, STAR included.

SMPL2 An enchanced and accelerated SMPL operation which commonly used in 3D human mesh generation. It takes a poses, shapes, cam_trans as inputs, outp

improvement of CLIP features over the traditional resnet features on the visual question answering, image captioning, navigation and visual entailment tasks.

CLIP-ViL In our paper "How Much Can CLIP Benefit Vision-and-Language Tasks?", we show the improvement of CLIP features over the traditional resnet fea

A set of tools for creating and testing machine learning features, with a scikit-learn compatible API

Feature Forge This library provides a set of tools that can be useful in many machine learning applications (classification, clustering, regression, e

STMTrack: Template-free Visual Tracking with Space-time Memory Networks

STMTrack This is the official implementation of the paper: STMTrack: Template-free Visual Tracking with Space-time Memory Networks. Setup Prepare Anac

This application is the basic of automated online-class-joiner(for YıldızEdu) within the right time. Gets the ZOOM link by scheduled date and time.
This application is the basic of automated online-class-joiner(for YıldızEdu) within the right time. Gets the ZOOM link by scheduled date and time.

This application is the basic of automated online-class-joiner(for YıldızEdu) within the right time. Gets the ZOOM link by scheduled date and time.

Time-series-deep-learning - Developing Deep learning LSTM, BiLSTM models, and NeuralProphet for multi-step time-series forecasting of stock price.
Time-series-deep-learning - Developing Deep learning LSTM, BiLSTM models, and NeuralProphet for multi-step time-series forecasting of stock price.

Stock Price Prediction Using Deep Learning Univariate Time Series Predicting stock price using historical data of a company using Neural networks for

Comments
  • Be more similar to Test.@test interface

    Be more similar to [email protected] interface

    Specifically, and most hard to work around, getting local variables to work:

    let
      i = 10
      @test i == 10
    end
    

    It does, but I'd like to have errors and testsets too (or rather just have the notebook a bit cleaned up)

    opened by dralletje 6
  • Show test pass at first frame

    Show test pass at first frame

    Currently, we always show the second-to-last frame as the default, until you move the timeline:

    This makes sense for test failures, because probably the last function call went from computed results to false, like a == call. But for test passes, it often just shows something trivial.

    This PR makes the first frame the default for test passes. This means that you can hide all code, and sort of quickly see what was being tested:

    But as you see in the screenshot, a large test expression means that it takes up more vertical space...

    opened by fonsp 3
  • allow HyperTextLiteral v0.9

    allow HyperTextLiteral v0.9

    Currently, compat for HypertextLiteral is set to v0.6 to 0.8. The most recent version of HypertextLiteral, 0.9, is not supported. This causes issues when using PlutoTest together with other packages which require HypertextLiteral 0.9.

    I do not think that there are breaking changes, therefore it should be sufficient just to add a compat entry for 0.9.

    opened by lungben 1
  • Be more similar to Test.@test interface

    Be more similar to [email protected] interface

    Specifically, and most hard to work around, getting local variables to work:

    let
      i = 10
      @test i == 10
    end
    

    It does, but I'd like to have errors and testsets too (or rather just have the notebook a bit cleaned up)

    opened by dralletje 0
Releases(v0.2.2)
Owner
Pluto
🎈 Simple reactive notebooks for Julia — https://github.com/fonsp/Pluto.jl
Pluto
Old Photo Restoration (Official PyTorch Implementation)

Bringing Old Photo Back to Life (CVPR 2020 oral)

Microsoft 11.3k Dec 30, 2022
competitions-v2

Codabench (formerly Codalab Competitions v2) Installation $ cp .env_sample .env $ docker-compose up -d $ docker-compose exec django ./manage.py migrat

CodaLab 21 Dec 02, 2022
automated systems to assist guarding corona Virus precautions for Closed Rooms (e.g. Halls, offices, etc..)

Automatic-precautionary-guard automated systems to assist guarding corona Virus precautions for Closed Rooms (e.g. Halls, offices, etc..) what is this

badra 0 Jan 06, 2022
Physics-informed Neural Operator for Learning Partial Differential Equation

PINO Physics-informed Neural Operator for Learning Partial Differential Equation Abstract: Machine learning methods have recently shown promise in sol

107 Jan 02, 2023
ML-Ensemble – high performance ensemble learning

A Python library for high performance ensemble learning ML-Ensemble combines a Scikit-learn high-level API with a low-level computational graph framew

Sebastian Flennerhag 764 Dec 31, 2022
Implementation of neural class expression synthesizers

NCES Implementation of neural class expression synthesizers (NCES) Installation Clone this repository: https://github.com/ConceptLengthLearner/NCES.gi

NeuralConceptSynthesis 0 Jan 06, 2022
Densely Connected Convolutional Networks, In CVPR 2017 (Best Paper Award).

Densely Connected Convolutional Networks (DenseNets) This repository contains the code for DenseNet introduced in the following paper Densely Connecte

Zhuang Liu 4.5k Jan 03, 2023
A Pose Estimator for Dense Reconstruction with the Structured Light Illumination Sensor

Phase-SLAM A Pose Estimator for Dense Reconstruction with the Structured Light Illumination Sensor This open source is written by MATLAB Run Mode Open

Xi Zheng 14 Dec 19, 2022
Python scripts for performing lane detection using the LSTR model in ONNX

ONNX LSTR Lane Detection Python scripts for performing lane detection using the Lane Shape Prediction with Transformers (LSTR) model in ONNX. Requirem

Ibai Gorordo 29 Aug 30, 2022
The Curious Layperson: Fine-Grained Image Recognition without Expert Labels (BMVC 2021)

The Curious Layperson: Fine-Grained Image Recognition without Expert Labels Subhabrata Choudhury, Iro Laina, Christian Rupprecht, Andrea Vedaldi Code

Subhabrata Choudhury 18 Dec 27, 2022
Hcaptcha-challenger - Gracefully face hCaptcha challenge with Yolov5(ONNX) embedded solution

hCaptcha Challenger 🚀 Gracefully face hCaptcha challenge with Yolov5(ONNX) embe

593 Jan 03, 2023
Code for database and frontend of webpage for Neural Fields in Visual Computing and Beyond.

Neural Fields in Visual Computing—Complementary Webpage This is based on the amazing MiniConf project from Hendrik Strobelt and Sasha Rush—thank you!

Brown University Visual Computing Group 29 Nov 30, 2022
The code for paper "Contrastive Spatio-Temporal Pretext Learning for Self-supervised Video Representation" which is accepted by AAAI 2022

Contrastive Spatio Temporal Pretext Learning for Self-supervised Video Representation (AAAI 2022) The code for paper "Contrastive Spatio-Temporal Pret

8 Jun 30, 2022
Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training

Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training Code for our paper "Predicting lncRNA–protein interactio

zhanglabNKU 1 Nov 29, 2022
Companion repo of the UCC 2021 paper "Predictive Auto-scaling with OpenStack Monasca"

Predictive Auto-scaling with OpenStack Monasca Giacomo Lanciano*, Filippo Galli, Tommaso Cucinotta, Davide Bacciu, Andrea Passarella 2021 IEEE/ACM 14t

Giacomo Lanciano 0 Dec 07, 2022
Rainbow is all you need! A step-by-step tutorial from DQN to Rainbow

Do you want a RL agent nicely moving on Atari? Rainbow is all you need! This is a step-by-step tutorial from DQN to Rainbow. Every chapter contains bo

Jinwoo Park (Curt) 1.4k Dec 29, 2022
Object Detection Projekt in GKI WS2021/22

tfObjectDetection Object Detection Projekt with tensorflow in GKI WS2021/22 Docker Container: docker run -it --name --gpus all -v path/to/project:p

Tim Eggers 1 Jul 18, 2022
[EMNLP 2021] Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training

RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p

Yu Meng 60 Dec 30, 2022
Revisiting Weakly Supervised Pre-Training of Visual Perception Models

SWAG: Supervised Weakly from hashtAGs This repository contains SWAG models from the paper Revisiting Weakly Supervised Pre-Training of Visual Percepti

Meta Research 134 Jan 05, 2023
Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks"

LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and

Adam Goodge 25 Dec 28, 2022