Search Results for "depth-violet"

...No need to generate timestamps yourself, the wrapper does it for you. Response exception handling. Websocket handling with reconnection and multiplexed connections. Symbol Depth Cache. Historical Kline/Candle fetching function. Withdraw functionality. Deposit addresses. Margin Trading. Futures Trading. Vanilla Options. 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.

This project is designed to help you make your own projects that interact with the Binance API. You can stream candlestick chart data, market depth, or use other advanced features such as setting stop losses and iceberg orders. This project seeks to have complete API coverage including WebSockets.

...The Evmos Tokenomics are designed to incentivize and reward the most inspired developers and the most active users. With modular EVM authoring, we make it easy to develop and deploy apps across both Ethereum and Cosmos ecosystems. Devs can build for the depth of Ethereum and the breadth of Cosmos, creating DeFi and diverse apps to benefit all users.

BitcoinExchangeFH is a slim application to record the price depth and trades in various exchanges. You can set it up quickly and record all the exchange data in a few minutes! If the exchange is not supported with the WebSocket API feed, it will automatically fall into using its REST API feed. The subscription section specifies the exchange and instruments to subscribe. After receiving the order book or trade update, each handler is updated.

Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. The above system combines hundreds of seed quantitative models, such as financial time series loss model, deep pattern quality assessment model, long and short pattern combination evaluation model, long pattern stop-loss strategy model, short pattern covering strategy model, big data K-line pattern Historical portfolio fitting model, trading position mentality model, dopamine quantification model, inertial residual resistance support model, long-short swap revenge probability model, strong and weak confrontation model, trend angle change rate model, etc.