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Your on-ramp to web3 multichain. Web3Modal is a versatile library that makes it super easy to connect users with your Dapp and start interacting with the blockchain. v2 is in early alpha and we are continuously adding more features, examples and documentation. As of now we support use cases with react and evm chains. Support for more frameworks and chains is on the way. Getting started with web3modal is as easy as installing a few packages, one for your preferred front-end framework i.e....

...Support other domains (.us, .jp, etc). The breaking changes include the migration from wapi to sapi endpoints which are related to the wallet endpoints detailed in the Binance Docs.

...The recommended way to install Brownie is via pipx. pipx installs Brownie into a virtual environment and makes it available directly from the command-line. Once installed, you will never have to activate a virtual environment prior to using Brownie. Brownie documentation is hosted at Read the Docs. Use tox to run the complete suite against the full set of build targets, or pytest to run tests against a specific version of Python. If you are using pytest you must include the -p no:pytest-brownie flag to prevent it from loading the Brownie plugin.

...And to achieve that, the easiest solution is to develop based on the go-Ethereum fork, as we respect the great work of Ethereum very much. Binance Smart Chain starts its development based on go-ethereum fork. So you may see many toolings, binaries and also docs are based on Ethereum ones, such as the name “geth”. But from that baseline of EVM compatible, Binance Smart Chain introduces a system of 21 validators with Proof of Staked Authority (PoSA) consensus that can support short block time and lower fees. The most bonded validator candidates of staking will become validators and produce blocks.

Catalyst is an algorithmic trading library for crypto-assets written in Python, originally developed to let quants and developers design, backtest, and deploy trading strategies in a unified environment. It builds on top of Zipline, extending that ecosystem to support crypto exchanges and high-resolution historical data (daily and minute bars). Users can express strategies in Python, run backtests against historical price data, and analyze performance through built-in metrics and analytics...