Changes between Version 1 and Version 2 of WikiStart


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Timestamp:
Oct 4, 2020, 10:44:01 AM (4 years ago)
Author:
monga
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  • WikiStart

    v1 v2  
    1 = Welcome to Trac
    2 
    3 Trac is a '''minimalistic''' approach to '''web-based''' management of
    4 '''software projects'''. Its goal is to simplify effective tracking and
    5 handling of software issues, enhancements and overall progress.
    6 
    7 All aspects of Trac have been designed with the single goal to
    8 '''help developers write great software''' while '''staying out of the way'''
    9 and imposing as little as possible on a team's established process and
    10 culture.
    11 
    12 As all Wiki pages, this page is editable, this means that you can
    13 modify the contents of this page simply by using your
    14 web-browser. Simply click on the "Edit this page" link at the bottom
    15 of the page. WikiFormatting will give you a detailed description of
    16 available Wiki formatting commands.
    17 
    18 "[wiki:TracAdmin trac-admin] ''yourenvdir'' initenv" created
    19 a new Trac environment, containing a default set of wiki pages and some sample
    20 data. This newly created environment also contains
    21 [wiki:TracGuide documentation] to help you get started with your project.
    22 
    23 You can use [wiki:TracAdmin trac-admin] to configure
    24 [http://trac.edgewall.org/ Trac] to better fit your project, especially in
    25 regard to ''components'', ''versions'' and ''milestones''.
     1= Programming in Python (for quantitative biologists)
    262
    273
    28 TracGuide is a good place to start.
     4== Learning objectives and expected learning outcomes
    295
    30 Enjoy! [[BR]]
    31 ''The Trac Team''
     6 The course introduces students to imperative programming by referring to the Python language.
    327
    33 == Starting Points
     8 The course is divided in two parts:
     9 1. Python and its object-oriented features;
     10 1. Python libraries that can be useful in scientific computation and data analysis, in particular [https://numpy.org/ NumPy] and [https://pandas.pydata.org/ pandas].
    3411
    35  * TracGuide --  Built-in Documentation
    36  * [http://trac.edgewall.org/ The Trac project] -- Trac Open Source Project
    37  * [http://trac.edgewall.org/wiki/TracFaq Trac FAQ] -- Frequently Asked Questions
    38  * TracSupport --  Trac Support
     12Students will acquire the ability to write and tune a program that automatizes simple computational tasks; they will be able to understand how a small piece of Python code works, to find the reasons of a malfunction and to correct it appropriately. Moreover, students will be able to use the [https://numpy.org/ NumPy] and [https://pandas.pydata.org/ pandas] library to analyze tabular data.
    3913
    40 For a complete list of local wiki pages, see TitleIndex.
     14== A.A. 2020/21
     15
     16The course will start in March 2021. If pandemic restrictions persist, lectures will be mainly streamed via [https://youtube.com YouTube] (with synchronous interaction with the instructors); streamed videos will be available until the conclusion of the course. Some lesson could be registered in asynchronous form. Laboratory exercises will conducted autonomously by the students and special synchronous feedback sessions will be organized.
     17
     18
     19=== Syllabus
     20
     21 * The Python programming language.
     22 * Native data types.
     23 * Functions, selections and iterations.
     24 * Basic data structures: lists, tuples, dictionaries.
     25 * Object-oriented encapsulation.
     26 * Iterators and generators.
     27 * Files.
     28 * Numpy multi-dimensional arrays and matrices.
     29 * Data manipulation and analysis with pandas.
     30
     31Any Python3 book can be used to support the learning of the general part, for example [https://link-springer-com.pros.lib.unimi.it/book/10.1007%2F978-3-030-20290-3 J. Hunt "A Beginners Guide to Python 3 Programming"] (The electronic version is free for Unimi students). [https://numpy.org/ NumPy] and [https://pandas.pydata.org/ pandas] have excellent online documentation.
     32
     33The examination is based on laboratory exercises. A final mark (on a 30 point scale) is given, by taking into account the knowledge of the subject and tools, and the clarity of the solutions.
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