Crypto Trading Bot Development using Python, Multithreading, and PyTorch

Documentary & Showcase

1. A lightweight, file-based NoSQL database for Python projects, designed for easy setup and use in small-scale applications: https://github.com/Kawai-Senpai/PotatoDB

2. A versatile Python library that enhances your command-line output with colorful text, styled formatting, and easy-to-use logging utilities: https://github.com/Kawai-Senpai/UltraPrint

Welcome to our latest update on a project that’s been two years in the making! Originally, our mission was to create an automated crypto trading robot—a behind-the-scenes genius designed to work tirelessly, effortlessly raking in profits. The idea was simple: minimize losses and maximize gains, giving us a steady net profit without lifting a finger.
Fast forward to today, and we’ve breathed new life into this project with a more advanced and secure version. While the original bot was built with a rock-solid philosophy of avoiding losses at all costs—so safe that it promised you’d never lose money but only gain—it turned out that perfection is hard to achieve. Although it was reliable, there were some challenges and limitations.
Our revamped version takes things up a notch. Instead of sticking to the old-school approach, we’ve integrated sophisticated technical indicators to pinpoint the best moments to buy and sell. This new version acknowledges that losses are a part of trading but uses advanced algorithms to maximize the probability of success. It’s smarter, faster, and designed to ensure profits over time, even if the occasional loss occurs.
Built in Python for lightning speed, this updated bot makes split-second decisions, processing data and executing trades in milliseconds. We’ve tested it with real money through the Binance API, and the results have been impressive—bringing in tangible profits and validating our improvements.

While working on this project, we also developed two helpful libraries that are not directly related to crypto or trading but could be valuable for many of you. The first one addresses a common issue in Python: logging and printing colorful, stylish output. We created a library called "UltraPrint" to make this process simple and intuitive.
UltraPrint enhances the standard print function by allowing you to print text in a variety of colors and styles, making your terminal output both organized and visually appealing. Whether you want your text in red, green, blue, or even with special effects like bold or underlined, UltraPrint has you covered. It also includes a logger class that can record messages of different severity levels—like info, warnings, errors, and more—both on the terminal and in a log file for later review.
Imagine you’re coding and you need to quickly identify important information or errors. UltraPrint makes this easy by letting you customize the color and style of your output. You can install it with a simple command, and once it’s set up, you can start printing text in any format and color you desire.
With the logger class, you can not only print messages in color but also save them to a log file, making it easy to track your program’s behavior over time. This library is perfect for developers who want to make their output more informative and engaging, and it’s available for download on PyPI and GitHub or just use pip install ultraprint to get started.

The second library we developed is called "PotatoDB." This tool was created to provide a simple, straightforward way to store data in a database that you can easily open and inspect without needing to run complex programs. Unlike more advanced databases that focus heavily on security and features, PotatoDB is designed for those who want to experiment, test ideas, or build datasets for machine learning and AI projects.
PotatoDB is ideal for situations where you need a minimalistic database solution that’s easy to use. For example, when we were working on a model to predict cryptocurrency price actions, we needed to build comprehensive datasets. Having a straightforward database like PotatoDB was incredibly useful.
With PotatoDB, you can store your data in JSON format, which is easy to read and manage. You can create multiple tables, insert, query, update, and delete records with simple commands. The data is saved automatically after each operation, ensuring that your changes persist across sessions.
Installation is a breeze—just use "pip install potatoDB" to download and install PotatoDB, or add the file directly to your project. Once installed, you can create a new PotatoDB instance, specify a folder for your data, and start using it right away. The database operates in-memory and saves to a physical JSON file, making it easy to open and view your data whenever needed.
In summary, PotatoDB is a user-friendly, no-SQL database solution that simplifies data storage and management, making it perfect for quick testing and development.

And that wraps up our overview! You can explore both "ultraprint" and "PotatoDB" by checking out the links in the description below. We're continually improving these libraries to enhance their functionality and make them even more valuable for developers. Additionally, our crypto trading bot, which we're actively using with real investments, has proven to be both reliable and effective, generating real-time profits. Stay tuned for more updates as we continue to refine and expand our tools.

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