2.2. Software engineering

Table of contents

• 2.2.1. An introduction to Python
  • 2.2.1.1. Key concepts
  • 2.2.1.2. Installing Python and Python development tools
  • 2.2.1.3. Data types
  • 2.2.1.4. Variables
  • 2.2.1.5. Boolean statements
  • 2.2.1.6. If statements
  • 2.2.1.7. Loops
  • 2.2.1.8. Functions
  • 2.2.1.9. Classes
  • 2.2.1.10. Modules
  • 2.2.1.11. String formatting
  • 2.2.1.12. Printing to the command line
  • 2.2.1.13. Reading and writing to/from files with csv and pyexcel
  • 2.2.1.14. Warnings and exceptions
  • 2.2.1.15. Other Python languages features
  • 2.2.1.16. Exercises
• 2.2.2. Numerical computing with NumPy
  • 2.2.2.1. Array construction
  • 2.2.2.2. Concatenation
  • 2.2.2.3. Query the shape of an array
  • 2.2.2.4. Reshaping
  • 2.2.2.5. Selection and slicing
  • 2.2.2.6. Transposition
  • 2.2.2.7. Algebra
  • 2.2.2.8. Trigonometry
  • 2.2.2.9. Other mathematical functions
  • 2.2.2.10. Data reduction
  • 2.2.2.11. Random number generation
  • 2.2.2.12. NaN and infinity
  • 2.2.2.13. Exercises
  • 2.2.2.14. NumPy introduction for MATLAB users
• 2.2.3. Plotting data with matplotlib
  • 2.2.3.1. Plot types
• 2.2.4. Developing database, command line, and web-based programs with Python
  • 2.2.4.1. Using databases with SQLAlchemy and SQLite
  • 2.2.4.2. Building command line programs with Cement
  • 2.2.4.3. Building web-based programs with Flask
• 2.2.5. Writing code for Python 2 and 3
• 2.2.6. Organizing Python code into functions, classes, and modules
• 2.2.7. Structuring Python projects
• 2.2.8. Revisioning code with Git, GitHub, and Meld
  • 2.2.8.1. Installing and configuring the required software
  • 2.2.8.2. Instructions
• 2.2.9. Testing Python code with unittest, pytest, and Coverage
  • 2.2.9.1. Required packages
  • 2.2.9.2. File naming and organization
  • 2.2.9.3. Writing tests
  • 2.2.9.4. Testing stochastic algorithms
  • 2.2.9.5. Testing standard output
  • 2.2.9.6. Testing cement command line programs
  • 2.2.9.7. Testing for multiple version of Python
  • 2.2.9.8. Running your tests
  • 2.2.9.9. Analyzing the coverage of your tests
  • 2.2.9.10. Additional tutorials
• 2.2.10. Debugging Python code using the PyCharm debugger
• 2.2.11. Documenting Python code with Sphinx
  • 2.2.11.1. Required packages
  • 2.2.11.2. File naming and organization
  • 2.2.11.3. Generating a Sphinx configuration file
  • 2.2.11.4. Writing documentation
  • 2.2.11.5. Compiling the documentation
• 2.2.12. Continuously testing Python code with CircleCI, Coveralls, Code Climate, and the Karr Lab’s dashboards
  • 2.2.12.1. Required packages
  • 2.2.12.2. Using the CircleCI cloud-based continuous integration system
  • 2.2.12.3. Code Climate
  • 2.2.12.4. Coveralls
  • 2.2.12.5. Karr Lab test results dashboard (tests.karrlab.org)
  • 2.2.12.6. Karr Lab software development dashboard (code.karrlab.org)
• 2.2.13. Distributing Python software with GitHub, PyPI, Docker Hub, and Read The Docs
  • 2.2.13.1. Required packages
  • 2.2.13.2. Prepare your package for distribution
  • 2.2.13.3. Distributing source code with GitHub
  • 2.2.13.4. Distributing Python packages with PyPI
  • 2.2.13.5. Distributing containers with Docker Hub
  • 2.2.13.6. Distributing documentation with Read The Docs
• 2.2.14. Recommended Python development tools
  • 2.2.14.1. Installation
• 2.2.15. Comparison between Python and other languages
  • 2.2.15.1. Python vs MATLAB