truffle
hypothesis
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truffle | hypothesis | |
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72 | 20 | |
14,014 | 7,254 | |
- | 1.2% | |
9.4 | 9.9 | |
5 months ago | 11 days ago | |
TypeScript | Python | |
MIT License | GNU General Public License v3.0 or later |
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.
truffle
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Projects to contribute to
Truffle (13700 GitHub Stars) https://github.com/trufflesuite/truffle
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SKALE Ecosystem Update. Explore the Thriving Ecosystem that is Driving Innovation on SKALE
Truffle
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Write a Smart Contract with ChatGPT MetaMask Infura, and Truffle
You’ve probably heard that Generative AI has demonstrated the potential to disrupt a huge number of industries and jobs — and web3 is no exception. But how well can ChatGPT create smart contracts? Can using ChatGPT to code smart contracts make you a 10x developer? In this article, we’ll try it out and see. We’ll walk through writing and deploying an Ethereum smart contract using MetaMask, Infura, and Truffle … and we will ask ChatGPT for instructions on how to do everything from the code to the deployment.
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Solidity digest fortnightly / 17-30 apr 2023
truffle v5.8.3 and v5.8.4 — update Ganache to the most recent version which supports Shanghai and small fixes
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Learn To Become a Web3 Developer by Exploring the Web3 Stack
For example, I used the Truffle Suite to write, compile, and deploy my first smart contracts, which includes Ganache to create a local blockchain and Drizzle to create a front-end dapp interface.
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Solidity digest / mar 2023
truffle v5.8.0 - Truffle introduces the Truffle Dashboard Hardhat plugin, which allows developers to see decoded transaction information when using Truffle Dashboard with their Hardhat projects.
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How to Build on Linea - a zk-rollup on Ethereum
In this article, we’ll explore what makes Linea so exciting. Then, we’ll walk through a tutorial on how to build a dapp on the Linea testnet. Finally, we’ll create our own cryptocurrency on Linea using Solidity, MetaMask, and Truffle: all mature ecosystem tools that are used by blockchain developers to build dapps.
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The 4 Best dApp Frameworks for First-Time Ethereum Developers
Truffle is a popular development and testing framework for dApps, both for first time and experienced Ethereum developers. As well as containing a web3.js library, Truffle is simple, user friendly and, with over 56K GitHub users, trusted. To install Truffle you need to have Node, NPM and Python. You can install Truffle via NPM with the command ‘npm install -g truffle.’
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Advancing dApp development with Hardhat Indexing: A Game-Changer for Ethereum Devs
The inspiration for the article came from a project I had built a little over a month earlier, for which I wrote a different article. In this initial project, I was actually using a Hardhat local node for my smart contract development. I decided to switch to Truffle for the final article, because it had a more intuitive demo contract, and because the command line tool made it easier to create manual transactions.
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The power of zero-knowledge proofs - exploring the new ConsenSys zkEVM
Easy for devs — The zkEVM supports most popular tools out of the box. You can build, test, debug, and deploy your smart contracts with Hardhat, Infura, Truffle, etc. All the tools you use now, you can keep using. And there is already a bridge to move tokens onto and off the network.
hypothesis
- Hypothesis
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A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
Hypothesis for Property-Based Testing: Hypothesis is a Python library facilitating property-based testing. It offers a distinct advantage by generating a wide array of input data based on specified properties or invariants within the code. The perks of Hypothesis include:
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Pix2tex: Using a ViT to convert images of equations into LaTeX code
But then add tests! Tests for LaTeX equations that had never been executable as code.
https://github.com/HypothesisWorks/hypothesis :
> Hypothesis is a family of testing libraries which let you write tests parametrized by a source of examples. A Hypothesis implementation then generates simple and comprehensible examples that make your tests fail. This simplifies writing your tests and makes them more powerful at the same time, by letting software automate the boring bits and do them to a higher standard than a human would, freeing you to focus on the higher level test logic.
> This sort of testing is often called "property-based testing", and the most widely known implementation of the concept is the Haskell library QuickCheck, but Hypothesis differs significantly from QuickCheck and is designed to fit idiomatically and easily into existing styles of testing that you are used to, with absolutely no familiarity with Haskell or functional programming needed.
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pgregory.net/rapid v1.0.0, modern Go property-based testing library
pgregory.net/rapid is a modern Go property-based testing library initially inspired by the power and convenience of Python's Hypothesis.
- Was muss man als nicht-technischer Quereinsteiger in Data Science *wirklich* können?
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Python toolkits
Hypothesis to generate dummy data for test.
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Best way to test GraphQL API using Python?
To create your own test cases, I recommend you use hypothesis-graphql in combination with hypothesis. hypothesis is a property-based testing library. Property-based testing is an approach to testing in which you make assertions about the result of a test given certain conditions and parameters. For example, if you have a mutation that requires a boolean parameter, you can assert that the client will receive an error if it sends a different type. hypothesis-graphql is a GraphQL testing library that knows how to use hypothesis strategies to generate query documents.
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Fuzzcheck (a structure-aware Rust fuzzer)
The Hypothesis stateful testing code is somewhat self-contained, since it mostly builds on top of internal APIs that already existed.
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Running C unit tests with pytest
We've had a lot of success combining that approach with property-based testing (https://github.com/HypothesisWorks/hypothesis) for the query engine at backtrace: https://engineering.backtrace.io/2020-03-11-how-hard-is-it-t... .
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Machine Readable Specifications at Scale
Systems I've used for this include https://agda.readthedocs.io/en/v2.6.0.1/getting-started/what... https://coq.inria.fr https://www.idris-lang.org and https://isabelle.in.tum.de
An easier alternative is to try disproving the statement, by executing it on thousands of examples and seeing if any fail. That gives us less confidence than a full proof, but can still be better than traditional "there exists" tests. This is called property checking or property-based testing. Systems I've used for this include https://hypothesis.works https://hackage.haskell.org/package/QuickCheck https://scalacheck.org and https://jsverify.github.io
What are some alternatives?
Kemono - The original paywall archiver/leaker. Deprecated in favor of Kemono 2.
pytest - The pytest framework makes it easy to write small tests, yet scales to support complex functional testing
hardhat - Hardhat is a development environment to compile, deploy, test, and debug your Ethereum software.
Robot Framework - Generic automation framework for acceptance testing and RPA
remix-ide - Documentation for Remix IDE
Behave - BDD, Python style.
foundry - Foundry is a blazing fast, portable and modular toolkit for Ethereum application development written in Rust.
nose2 - The successor to nose, based on unittest2
embark-framework - Framework for serverless Decentralized Applications using Ethereum, IPFS and other platforms
Schemathesis - Automate your API Testing: catch crashes, validate specs, and save time
openzeppelin-contracts - OpenZeppelin Contracts is a library for secure smart contract development.
nose - nose is nicer testing for python