Robot Framework
examples
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Robot Framework | examples | |
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52 | 143 | |
9,050 | 7,742 | |
2.5% | 1.2% | |
9.7 | 6.2 | |
15 days ago | 23 days ago | |
Python | Jupyter Notebook | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Robot Framework
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Beautiful is better than ugly, but my beginner code is horrible
Well, I work with software quality and despite not having a strong foundation in automation, one fine day I decided to make a change. I have been working with Robot Framework for a few months - and that's when I got a taste of the power of python. Some time later, I dabbled a little with Cypress and Playwright, always using javascript.
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Deep Dive into API Testing - An introduction to RESTful APIs
Robot Framework
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Robot Framework VS vedro - a user suggested alternative
2 projects | 16 Jul 2023
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Embedded professionals, what kind of 'github' projects would make you hire a developer?
I've used Lua/Busted in a data-heavy environment (telemetry from hospital ventilators). I've also used robot: https://robotframework.org/
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Opensource Gui testing framework
I can't say whether any of these will work, but maybe one of: PyAutoGui pytest-qt Robot Framework + plugins
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Ask HN: What is the best way to automate a Windows desktop application in 2023?
I'm looking for tools, strategies, libraries, etc. that would be useful for automating arbitrary desktop applications. Ideally something free and open source. Robot Framework (https://robotframework.org/) looks promising, although the docs seem deliberately unclear about how useable the open source libraries are without the cloud SaaS being sold on top.
Does anyone have experience in this area? What's your secret sauce for robust desktop automations?
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How is Python used in test automation in embedded systems?
In the industry I've seen the framework "Robot framework" https://robotframework.org/ used a lot for test automation.
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Successful open source RPA solutions
Check out Robot Framework @ https://robotframework.org/
- Robot Framework: generic open source automation framework
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Gherkin and Robot Framework
Greetings! They say all good things must come to an end, and with this post, so it is with my series of posts covering Robot Framework.
examples
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
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Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
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Releasing The Force Of Machine Learning: A Novice’s Guide 😃
TensorFlow: An open-source machine learning framework for high-performance numerical computations, especially well-suited for deep learning.
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MLOps in practice: building and deploying a machine learning app
The tool used to build the model per se was TensorFlow, a very powerful and end-to-end open source platform for machine learning with a rich ecosystem of tools. And in order to to create the needed script using TensorFlow Jupyter Notebook was used, which is a web-based interactive computing platform.
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🔥14 Excellent Open-source Projects for Developers😎
10. TensorFlow - Make Machine Learning Work for You 🤖
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GPU Survival Toolkit for the AI age: The bare minimum every developer must know
AI models, particularly those built on deep learning frameworks like TensorFlow, exhibit a high degree of parallelism. Neural network training involves numerous matrix operations, and GPUs, with their expansive core count, excel in parallelizing these operations. TensorFlow, along with other popular deep learning frameworks, optimizes to leverage GPU power for accelerating model training and inference.
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
#2 TensorFlow
- Are there people out there who still like Sam atlman - AI IS AT DANGER
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Tensorflow help
I am on a new ftc team trying to get vision to work. I used the ftc machine learning tool chain but I have yet to get a good result with at best a 10% accuracy rate. I have changed everything possible in the tool chain with little luck. To fix this, I have tried making my own .tflite model using the google colab from https://www.tensorflow.org/. When ever I try to run the same code with my own .tflite model, it gives me the error "User code threw an uncaught exception: IllegalStateException - Error getting native address of native library: task_vision_jni". It gives me the same error with official tensor flow tflite test models, and when I put them on a raspberry pi, both worked just fine. Does anyone have a fix to this error or even just tips for the machine learning toolchain?
What are some alternatives?
pytest - The pytest framework makes it easy to write small tests, yet scales to support complex functional testing
cppflow - Run TensorFlow models in C++ without installation and without Bazel
Behave - BDD, Python style.
mlpack - mlpack: a fast, header-only C++ machine learning library
Selenium Wire - Extends Selenium's Python bindings to give you the ability to inspect requests made by the browser.
awesome-teachable-machine - Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
Slash - The Slash testing infrastructure
face-api.js - JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
hypothesis - Hypothesis is a powerful, flexible, and easy to use library for property-based testing.
Selenium WebDriver - A browser automation framework and ecosystem.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing