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Enhancing Water Management with Python: A Forward-Thinking Approach
By: Oskar Hurst and Eric Novotny, Ph.D.
In the Water Management Systems (WMS) Division at HEC, we are embarking on a strategic initiative to integrate more Python tools into our suite of programs. Recent additions, such as cwms-python, Py-SHEF, and DSS-Py signify our commitment to modernize our approach to data management and analysis. As stewards of our mission to support the U.S. Army Corps of Engineers (USACE), water managers nationwide, and the public, we recognize the imperative of providing robust, user-friendly tools that align with the evolving needs of our stakeholders.
Our decision to develop these tools in Python is grounded in the following three fundamental principles that underpin our mission.
Usability for Water Managers
Central to our mission is the facilitation of water management tasks for professionals across all USACE districts. Leveraging Python, we aim to create tools that are intuitive and user-friendly, empowering water managers to efficiently access and analyze critical data. Python's reputation as one of the easiest languages to learn is invaluable for water managers, many of whom may not have formal training in computer programming. With Python's intuitive syntax, beginner-friendly approach and vast library of educational materials, water managers can quickly grasp scripting concepts and leverage powerful tools to analyze and visualize data. For instance, cwms-python, our Python API for interacting with CWMS databases via the CWMS Data API (CDA), and Py-SHEF, designed for parsing SHEF files, exemplify our commitment to enhancing usability and streamlining workflows for water managers nationwide. With cwms-python, water managers can effortlessly load data directly from our Cloud Database into a Python Pandas Data frame, enabling seamless data modeling, analysis, and informed decision-making.
Installing Python packages with pip is a simple process that allows non-programmers to enhance the functionality of their Python projects (Figure 1). By running a straightforward command from the Python command prompt like:
pip install cwms-python
Users can easily install and integrate new features, libraries, or tools into their codebase without the need for extensive programming knowledge (see https://pypi.org/project/cwms-python/0.3.0/ for more information). This convenience enables individuals to quickly access and leverage a vast array of resources from the Python Package Index, enhancing the capabilities of their projects with minimal effort.
Figure 1. Provides a snapshot of the pip install n overview of the installation and usage instructions for installing cwms-python library (see https://pypi.org/project/cwms-python/0.3.0/ for more information).
Accessibility for the Modern Workforce
As we transition towards a more digitally-driven landscape, ensuring that our tools remain accessible to the modern workforce is paramount. By adopting Python, we are taking proactive steps to modernize our legacy code and make it more accessible to the public, including a new generation of engineers and data scientists. Python's widespread recognition, known by 49% of programmers according to Statista.com (Figure 2), and taught in many engineering programs, positions it as the most well-known non-web development language (TIOBE, 2024). This transition from legacy codebases to Python not only facilitates knowledge transfer but also ensures continuity in development efforts, enabling easier onboarding for future team members. By embracing Python, we empower our workforce to harness the full potential of our tools with minimal barriers to entry, fostering a culture of innovation and collaboration within our organization.
Figure 2. Most commonly used programming languages among software developers worldwide, as of 2024 (provided by Statistica.com).
Future-Proofing for Tomorrow's Challenges
Anticipating the evolving needs and requirements of tomorrow is essential for fulfilling our mission effectively. Python's versatility and expansive ecosystem position us to future-proof our products, ensuring they remain relevant and adaptable to emerging challenges. With tools like DSS-Py and cwms-python, which facilitate the seamless integration of data from local DSS files or our CWMS real-time database into Python objects, we are equipping water managers with the resources they need to address tomorrow's challenges with confidence. By embracing Python, we empower water managers to perform advanced modeling, analysis, and visualization, leveraging cutting-edge technologies such as machine learning for predictive modeling. For instance, using our Python tools, water managers can easily load data and integrate it into an AI model, enabling proactive decision-making and resource management based on predictions of potential flow levels in the future. This strategic adoption of Python ensures that our tools remain scalable, innovative, and capable of meeting the evolving demands of water management practices nationwide. The Python landscape of open source modules is ever expanding and modernizing. Updating our data management approach to take advantage of the expansive community of developers and their industry-standard tools in the fields of data science, data visualization, and machine learning allows our USACE water management community to continuously grow and innovate.
In essence, our adoption of Python within the Water Management Systems Division at HEC embodies a forward-thinking approach to fulfilling our mission. By prioritizing usability, accessibility, and future-proofing, we are equipping water managers with the tools they need to navigate an increasingly complex and dynamic landscape, ultimately advancing our collective mission of sustainable water management nationwide.
References
- HEC. (2024, August, 27). Read me. HEC-DSS Python Wrapper. Retrieved August, 29, 2024, from https://github.com/HydrologicEngineeringCenter/hec-dss-python/blob/main/Readme.md
- Novotny, Eric. (Released 2024, April, 25). cwms-python 0.3.0. Corps water managerment systems (CWMS) REST API for Data Retrieval of USACE water data. Retrieved August 29, 2024, from https://pypi.org/project/cwms-python/0.3.0/
- TIOBE. (2024, August). TIOBE Index for August 2024. August Headline: Python is chasing Java's TIOBE index records. Retrieved August 29, 2024, from https://www.tiobe.com/tiobe-index/
- Sujay Vailshery, Lionel (2024, August, 7). Most widely utilized programming languages among developers worldwide 2024. Retrieved August 29, 2024, from https://www.statista.com/statistics/793628/worldwide-developer-survey-most-used-languages/