What frameworks and libraries have you used for application development using Python?

02 August 2024

Question

Can you provide some examples from your CV?

Answer

I have used several frameworks and libraries for application development in Python across various projects:

• Pandas: Utilized for data manipulation and analysis, essential in building analytics and insights frameworks for financial markets and multi-asset portfolios.
• NumPy: Employed for numerical operations and handling large datasets efficiently, particularly in quantitative and financial modeling.
• Dask: Applied for parallel computing to manage and process large datasets, enhancing performance in data-intensive applications.
• FastAPI: Leveraged to develop high-performance web APIs and microservices, particularly in building modular APIs for data integrations and analytics platforms.
• Flask: Used for creating lightweight web applications, especially in prototyping and rapid development scenarios.
• SQLAlchemy: Integrated as an ORM for seamless interaction with databases, used in data products and ETL pipelines.
• Apache Airflow: Employed for orchestrating ETL pipelines and managing complex workflows in cloud-native data processing environments.
• PySpark: Utilized for processing large datasets on Hadoop, improving data handling and analytics capabilities in financial and data engineering projects.
• Beautiful Soup: Used for web scraping to gather financial and market data efficiently.
• Scrapy: Applied for creating robust and scalable web crawlers to extract and process data from various sources. These tools have been integral to my roles in data engineering, financial modeling, and application development, enabling efficient data handling, scalable application design, and effective data integration solutions.