Introduction to Python
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1 Introduction to Python Dr. Hans van der Kwast Senior Lecturer in Ecohydrological Modelling IHE Delft Institute for Water Education
2 Schedule Monday Install software DOS and GDAL Tuesday Introduction to Python Thursday Spatial-dynamic modelling with PCRaster Python Friday PyQGIS Wednesday Python libraries Map Algebra with PCRaster Python
3 Learning objectives After this lecture you will be able to Explain what Python is and how it can be used 3
4 Why learn Python? Python is the DUCT-TAPE programming language! Open source! new job/team, same code Useful on different levels: Research: data-mining, GIS, bio-informatics, CFD-wrappers Daily use: handling textfiles, quick plotting, Pre/post processing: visualize CFD output; read txt-file, GIS and Modelling!
5 Python = jobs Source: LinkedIn 5
6 Python = jobs
7 Python = jobs
8 Python = jobs
9 Some facts Developed in the early 1990 s Developer: Guido van Rossem, CWI, Amsterdam Worked for Google Now works for Dropbox Development of Python is lead by the Python Software Foundation Named after Monty Python Source: Bernt Rostad
10 In the news yesterday Beautiful is better than ugly Explicit is better than implied Simple is better than complex Source: NRC, July
11 Specific Python Characteristics General purpose High-level Emphasize on code readability Indentation indicates layer Supports multiple programming paradigms: Object-oriented Imperative Functional/procedural style Dynamic type system Automatic memory management Comprehensive standard library
12 Specific Python Characteristics very clear, readable syntax strong introspection capabilities intuitive object orientation natural expression of procedural code full modularity, supporting hierarchical packages exception-based error handling very high level dynamic data types extensive standard libraries and third party modules for virtually every task extensions and modules easily written in C, C++ (or Java for Jython, or.net languages for IronPython) embeddable within applications as a scripting interface
13 Terminology Implementations Distributions IDE
14 Implementations CPython: standard implementation in C Alternatives: IronPython Ipython for.net Jython for JVM
15 Distributions Standard distribution by Python Software Foundation Alternative distributions for specific requirements or simplifying the installation process: Anaconda (free) Enthought
16 IDE Integrated Development Environment Examples: IDLE (default) Spyder (comes with Anaconda distribution, free) Canopy (comes with Entought, not free) Eclipse
17 Repositories and versioning Code can be stored and shared in repo s GitHub: Code hosting Version control Access control Bug tracking Feature requests Task management Wiki s Free for Open Source Projects
18 Jupyter Notebook Interactive websites where code can be executed MarkDown markup language Python scripts Loose acronym of Julia, Python and R Uses IPython implementation (Interactive Python) Server comes with Anaconda
19 Exercises Jupyter Notebook: Download to your Anaconda user folder Open Anaconda prompt Type: jupyter notebook Start Python3Tutorial\PythonIntro.ipynb
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