This script scrapes and stores the availability of timeslots for Car Driving Test at all RTA Serivce NSW centres in the state.

Overview

This script scrapes and stores the availability of timeslots for Car Driving Test at all RTA Serivce NSW centres in the state.

Dependencies

  1. Account with RTA NSW where you can have passed knowledge test, hazard test etc.
  2. chrome driver executable in your PATH variable
  3. Python3 and Selenium installed
  4. Optional jq and R for creating reports from results

Usage

Clone the repo

git clone https://github.com/sbmkvp/rta_booking_information

Set your working directory to the repo

cd rta_booking_information

Copy and modify the sample settings file

cp settings_sample.json settings.json

Change the username, password, if you already have a booking and the specific centres you are looking for. If you leave the centres null all centres will be searched.

Run the script (for bash based systems e.g. mac/linux/WSL)

./scrape_availability.py

Run the script (for windows)

python3 scrape_availability.py

The results should be saved in the results folder. You can convert these to csv report by using the second script (requires jq,bash and R with tidyverse)

./create_status_report result_file.json

This has been tested to work in my system but there are numerous edge cases where this might fail.

  • Your account status is different to mine
  • RTA changes website.
  • RTA IT team blocks your IP
  • The website is very slow

If the website is slow and the script fails at selecting the driving test on a new booking try increasing the wait_timer.

Disclaimer:

  • For personal use only.
  • Dont break the law or cause disruption using this.
  • Using automated scripts irresponsibily can cause booking loss, disruption of services etc. be careful and know what you are doing.
  • You are responsible for your actions.
Owner
Balamurugan Soundararaj
Post Doctoral Fellow on Data Analytics and Visualization at UNSW, Sydney. Working on visualizing property valuation models and results.
Balamurugan Soundararaj
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

Atmospheric Cloud Simulation Group @ Jagiellonian University 32 Oct 18, 2022
Stereo Hybrid Event-Frame (SHEF) Cameras for 3D Perception, IROS 2021

For academic use only. Stereo Hybrid Event-Frame (SHEF) Cameras for 3D Perception Ziwei Wang, Liyuan Pan, Yonhon Ng, Zheyu Zhuang and Robert Mahony Th

Ziwei Wang 11 Jan 04, 2023
An implementation of the efficient attention module.

Efficient Attention An implementation of the efficient attention module. Description Efficient attention is an attention mechanism that substantially

Shen Zhuoran 194 Dec 15, 2022
NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys in IEEE Transactions o

D-X-Y 137 Dec 20, 2022
[CIKM 2019] Code and dataset for "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction"

FiGNN for CTR prediction The code and data for our paper in CIKM2019: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predicti

Big Data and Multi-modal Computing Group, CRIPAC 75 Dec 30, 2022
Angular & Electron desktop UI framework. Angular components for native looking and behaving macOS desktop UI (Electron/Web)

Angular Desktop UI This is a collection for native desktop like user interface components in Angular, especially useful for Electron apps. It starts w

Marc J. Schmidt 49 Dec 22, 2022
Reproduces the results of the paper "Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations".

Finite basis physics-informed neural networks (FBPINNs) This repository reproduces the results of the paper Finite Basis Physics-Informed Neural Netwo

Ben Moseley 65 Dec 28, 2022
This project implements "virtual speed" from heart rate monito

ANT+ Virtual Stride Based Speed and Distance Monitor Overview This project imple

2 May 20, 2022
PolyTrack: Tracking with Bounding Polygons

PolyTrack: Tracking with Bounding Polygons Abstract In this paper, we present a novel method called PolyTrack for fast multi-object tracking and segme

Gaspar Faure 13 Sep 15, 2022
Official codebase for "B-Pref: Benchmarking Preference-BasedReinforcement Learning" contains scripts to reproduce experiments.

B-Pref Official codebase for B-Pref: Benchmarking Preference-BasedReinforcement Learning contains scripts to reproduce experiments. Install conda env

48 Dec 20, 2022
Official codebase for ICLR oral paper Unsupervised Vision-Language Grammar Induction with Shared Structure Modeling

CLIORA This is the official codebase for ICLR oral paper: Unsupervised Vision-Language Grammar Induction with Shared Structure Modeling. We introduce

Bo Wan 32 Dec 23, 2022
CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images

CurriculumNet Introduction This repo contains related code and models from the ECCV 2018 CurriculumNet paper. CurriculumNet is a new training strategy

156 Jul 04, 2022
Official implementation of Self-supervised Image-to-text and Text-to-image Synthesis

Self-supervised Image-to-text and Text-to-image Synthesis This is the official implementation of Self-supervised Image-to-text and Text-to-image Synth

6 Jul 31, 2022
Self-training for Few-shot Transfer Across Extreme Task Differences

Self-training for Few-shot Transfer Across Extreme Task Differences (STARTUP) Introduction This repo contains the official implementation of the follo

Cheng Perng Phoo 33 Oct 31, 2022
Source code for models described in the paper "AudioCLIP: Extending CLIP to Image, Text and Audio" (https://arxiv.org/abs/2106.13043)

AudioCLIP Extending CLIP to Image, Text and Audio This repository contains implementation of the models described in the paper arXiv:2106.13043. This

458 Jan 02, 2023
This is an early in-development version of training CLIP models with hivemind.

A transformer that does not hog your GPU memory This is an early in-development codebase: if you want a stable and documented hivemind codebase, look

<a href=[email protected]"> 4 Nov 06, 2022
Official Implementation for the "An Empirical Investigation of 3D Anomaly Detection and Segmentation" paper.

An Empirical Investigation of 3D Anomaly Detection and Segmentation Project | Paper Official PyTorch Implementation for the "An Empirical Investigatio

Eliahu Horwitz 55 Dec 14, 2022
Official Implementation of SWAD (NeurIPS 2021)

SWAD: Domain Generalization by Seeking Flat Minima (NeurIPS'21) Official PyTorch implementation of SWAD: Domain Generalization by Seeking Flat Minima.

Junbum Cha 97 Dec 20, 2022
PyTorch implementation of Value Iteration Networks (VIN): Clean, Simple and Modular. Visualization in Visdom.

VIN: Value Iteration Networks This is an implementation of Value Iteration Networks (VIN) in PyTorch to reproduce the results.(TensorFlow version) Key

Xingdong Zuo 215 Dec 07, 2022