PyLibAPIs.7z : contains public API data (MongoDB dump) for these frameworks:

• TensorFlow
• Keras
• Scikit-learn
• Pandas
• Flask
• Django

Label.xlsx: contains issues and their labels

Breaking Changes for All Frameworks.pdf: contains the breaking change distributions of all six frameworks

PyLibAPIs.7z : contains public API data (mongodb dump) for these frameworks:

TensorFlow

Keras

scikit-learn

Pandas

Flask

Django

Label.xlsx: cintains issues and their labels

The Python Package Software market is experiencing robust growth, driven by the increasing adoption of Python in various industries and the rising demand for efficient and specialized software solutions. The market's expansion is fueled by the large and active Python community constantly developing and refining packages for diverse applications, from web development and data science to machine learning and automation. While precise market sizing is unavailable, considering the widespread use of Python and the significant contribution of open-source packages, a reasonable estimate for the 2025 market size could be around $5 billion, projecting a Compound Annual Growth Rate (CAGR) of 15% over the forecast period (2025-2033). This growth is primarily driven by the increasing complexity of software projects demanding specialized functionality readily available through packages, the need for faster development cycles, and the cost-effectiveness of leveraging pre-built components. Key trends include the rise of cloud-based Python package management, the growing importance of security and maintainability in package selection, and the increasing specialization of packages for niche applications. Constraints on market growth might include challenges in ensuring package quality and security, as well as the learning curve associated with integrating and managing diverse packages within large projects. The market is segmented into cloud-based and web-based solutions, catering to large enterprises and SMEs, with North America and Europe currently holding the largest market shares. The diverse range of packages, from those focusing on data manipulation (Pandas, NumPy) and web frameworks (Django, Flask) to machine learning libraries (Scikit-learn, TensorFlow) and GUI development (Tkinter, PyQt), underscores the market's versatility. The significant contribution of open-source packages fosters a collaborative environment and continuous improvement. However, challenges remain in effectively managing the vast ecosystem of packages, addressing security vulnerabilities, and ensuring interoperability. The future growth will hinge on addressing these challenges, fostering standardization, and further improving the accessibility and user experience of Python package management systems. Continued innovation within the Python ecosystem and broader industry trends such as the rise of AI and big data will further propel the market's expansion.