The team has created a platform specifically designed for the distribution of pharmaceutical products. This project is a set of integrations that allows working with various internet platforms, pharmacies, as well as auxiliary services. In total, the project includes about 10 integrations, such as Authorization, Statistics, Price Generation, Decoding, Marking, and others.
Using these integrations, orders are created, canceled, and moved through statuses, as well as delivered and received. Clients include both regular buyers and over 40 marketplaces with which integration has taken place.
The team changed the price calculation logic for B2B/B2C and developed discount calculation logic. They also created a messaging service and integrated it with SMS.ru.
The development team improved the integration with the 1C ERP system for various branches, integrated with AWS S3 + OpenPIm + PimCore for uploading, updating, and deleting images, and also integrated with an FTP server to store xml feeds for goods, prices, balances, and addresses.
The team optimized the service, increased fault tolerance, added logging, monitoring, graphs, and alerts to them, as well as document flow to a number of services.
The development team created an application that has a wide range of features and offers many possibilities. The application’s capabilities include user registration, profile creation, searching for suitable partners, sending messages and notifications about new matches, as well as adjusting search parameters.
There is also the ability to make video/audio calls, send video/audio messages, and files of various extensions. The application automatically adapts search parameters based on user behavior. The application is built on an asynchronous architecture, which allows it to withstand huge loads on the server and provide flawless performance for users.
The Python programming language and FastAPI web framework were used to develop the application’s API. The application is implemented in a microservice architecture that provides high performance and efficient management of large amounts of data. The application has undergone numerous tests for fault tolerance, and user interface testing has also been performed.
The application was developed using the Python programming language and a range of libraries and frameworks, including NumPy, Pandas, Scikit-Learn, and others. Machine learning algorithms were used to create accurate predictions for sports events. The user interface was designed to be simple and easy to use, allowing users to easily configure their bets and receive recommendations for sports events.
However, there were some difficulties during the development process, such as creating an algorithm that could predict sports event outcomes with high accuracy. A large number of tests and experiments were conducted to find the best combination of parameters and to train the model.
An innovative and functional cryptocurrency trading service was developed to provide users with the ability to trade with over 150 cryptocurrencies. The service includes an automated trading functionality that allows users to create and configure trading bots for automatic buying and selling of cryptocurrencies based on specified parameters. In addition, the service provides real-time cryptocurrency quotes, customizable price and rate change alerts, and the ability to analyze the statistics of trading operations.
Security was a significant consideration in the development of the application, and as a result, the service was implemented with two-factor authentication and libraries to verify the authenticity and authorization of users. Cryptographic methods were also used to protect user data and ensure the security of data transmission between the client and server sides of the application.
To accommodate the anticipated growth in the number of users and transaction volumes, the system was designed to be easily scalable and support a large number of users and transactions. To achieve high performance of the application, its architecture was optimized, and cutting-edge technologies were used for processing large amounts of real-time data and requests.
Effective communication with the client was critical to the success of the project, and regular meetings and discussions were held to understand their requirements and expectations for the application. The client was provided with weekly progress reports and intermediate versions of the application for feedback and additional requests.