Open-source programming languages are rapidly transforming drug discovery, research, and development, offering powerful capabilities for study design, data analysis, visualization, and clinical reporting. This workshop introduces practical strategies for using Python to prepare tables, listings, and figures (TLFs) in a clinical study report (CSR) and to assemble submission-ready electronic Common Technical Document (eCTD) packages that include both source code and deliverables. This workshop is designed for clinical programmers, statisticians, and data scientists who are interested in exploring Python as an alternative approach for clinical trial analysis and reporting. Participants will gain hands-on experience with reproducible workflows, clinical data engineering, and end-to-end project management using the modern Python toolchain. By the end of the session, attendees will have a clear roadmap to start a Python project for clinical trial analysis and reporting. The workshop is based on the open source book Python for Clinical Study Reports and Submission (https://pycsr.org/) and is organized into four modules: Python environment setup: Use uv to create and manage reproducible Python projects. Develop and collaborate in GitHub Codespaces, Visual Studio Code, or Positron. Python packages for clinical reporting: A guided tour of essential packages such as polars, plotnine, and rtflite, with demonstrations of creating TLFs commonly used in clinical trials. Manage a clinical trial A&R project: Practical project structure, conventions, and execution from data to deliverables. Preparing eCTD submission packages: An example workflow for assembling submission-ready source code and outputs using py-pkglite, aligned with eCTD requirements.