Instituto Politécnico de Tomar. Python. Introduction. Ricardo Campos. Licenciatura ITM Técnicas Avançadas de Programação Abrantes, Portugal, 2018

Transcription

1 Instituto Politécnico de Tomar Python Introduction Ricardo Campos Licenciatura ITM Técnicas Avançadas de Programação Abrantes, Portugal, 2018

2 This presentation was developed by Ricardo Campos, Professor of ICT of the Polytechnic Institute of Tomar and researcher of LIAAD - INESC TEC. Part of the slides used in this presentation were adapted from presentations found in internet and from reference bibliography: Dipanjan Sarkar (2016). Text Analytics with Python Scientific-Computing-with-Python.ipynb

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4 AGENDA What is this talk about? Why History Features Advantages Setup Install Libraries Resources Q&A

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6 Python is a scientific language and it is the first choice of Scientists much due to its large community of users, easy to find help and documentation. Extensive ecosystem of scientific libraries and environments: numpy: - Numerical Python scipy: - Scientific Python matplotlib: - graphics library No license costs, no unnecessary use of research budget. Python is especially good for our purposes in that it does not have a lot of overhead before getting started. It is easy to jump in and experiment with Python in an interactive fashion.

7 Popular Domains Python is widely used in several domains including artificial intelligence (AI), game development, robotics, Internet of Things (IoT), computer vision, media processing, and network and system monitoring, just to name a few. Although Python can be used for solving a lot of problems, here are some of the most popular domains: Scripting: Python is known as a scripting language. It can be used to perform many tasks, such as interfacing with networks and hardware and handling and processing files and databases, performing OS operations, and receiving and sending . Python is also used extensively for server-side scripting and even for developing entire web servers for serving web pages.

8 Web development: There are a lot of robust and stable Python frameworks out there that are used extensively for web development, including Django, Flask, Web2Py, and Pyramid. Graphical user interfaces (GUIs): A lot of desktop-based applications with GUIs can be easily built with Python. Libraries and APIs like tkinter, PyQt, PyGTK, and wxpython allow developers to develop GUI-based apps with simple as well as complex interfaces. Systems programming: We can use Python to perform OS operations including creating, handling, searching, deleting, and managing files and directories. The Python standard library (PSL) has OS and POSIX bindings that can be used for handling files, multi-threading, multi-processing, environment variables, controlling sockets, pipes, and processes.

9 Database programming: Python is used a lot in connecting and accessing data from different types of databases, be it SQL or NoSQL. APIs and connectors exist for these databases like MySQL, MSSQL, MongoDB, Oracle, PostgreSQL, and SQLite. In fact, SQLite, a lightweight relational database, now comes as a part of the Python standard distribution itself. Scientific computing: Python really shows its flair for being multipurpose in areas like numeric and scientific computing. You can perform simple as well as complex mathematical operations with Python, including algebra and calculus. Libraries like SciPy and NumPy help researchers, scientists, and developers leverage highly optimized functions and interfaces for numeric and scientific programming. These libraries are also used as the base for developing complex algorithms in various domains like machine learning.

10 Machine learning: Python is regarded as one of the most popular languages today for machine learning. There is a wide suite of libraries and frameworks, like scikit-learn, h2o, tensorflow, theano, and even core libraries like numpy and scipy, for not only implementing machine learning algorithms but also using them to solve real-world advanced analytics problems. Text analytics: Python can handle text data very well, and this has led to several popular libraries like nltk, gensim, and pattern for NLP, information retrieval, and text analytics. You can also apply standard machine learning algorithms to solve problems related to text analytics. This ecosystem of readily available packages in Python reduces time and efforts taken for development.

11 Python was developed by Guido van Rossum in the late eighties and early nineties at the National Research Institute for Mathematics and Computer Science in the Netherlands. Guido Van Rossum published the first version of Python code (version 0.9.0) at alt.sources in February In 2008, Python 3 was released on an almost-unthinkable premise - a complete overhaul of the language, with no backwards compatibility. The decision was controversial, and born in part of the desire to clean house on Python.

12 clean and simple language: Easy-to-read and intuitive code, easy-to-learn minimalistic syntax. Reading a good Python program feels almost like reading English. Hello.java public class Hello { public static void main(string[] args){ System.out.println("Hello world!"); } } print "Hello world!" hello.py

13 expressive language: Fewer lines of code, fewer bugs, easier to maintain. dynamically typed: No need to define the type of variables, function arguments or return types. Free and Open Source software. Portable: due to its open-source nature, Python has been ported to many platforms. All your Python programs can work on several platforms without requiring any changes.

14 interpreted: You just run the program directly from the source code. Internally, Python converts the source code into an intermediate form called bytecodes and then translates this into the native language of your computer and then runs it. This also makes your Python programs much more portable, since you can just copy your Python program onto another computer and it just works!

15 Object Oriented: Python supports procedure-oriented programming as well as object-oriented programming. Python has a very powerful but simplistic way of doing OOP, especially when compared to big languages like C++, C# or Java. Interactive: You can actually sit at a Python prompt and interact with the interpreter directly to write your programs. Beginner s Language: Python is a great language for the beginner-level programmers and supports the development of a wide range of applications from simple text processing to WWW browsers to games. Databases: Python provides interfaces to all major commercial databases.

16 The main advantage is ease of programming, minimizing the time required to develop, debug and maintain the code. Besides the standard library, thousands of third-party libraries are readily available on the Internet, encouraging open source and active development. The official repository for hosting third-party libraries and utilities for enhancing development in Python is the Python Package Index (PyPI). Access it at and check out the various packages. Currently there are over 118,000 packages you can install and start using. The pseudo-code nature of Python is one of its greatest strengths. It allows you to concentrate on the solution to the problem rather than the language itself.

17 Which Operating System? The beauty of Python is that is can run seamlessly on any OS without much hassle. The three most popular OSes include the following: Windows Linux MacOS

18 IDE (Integrated Development Environments) The usual components of an IDE include source editor, debugger, compiler, interpreter, and refactoring and build tools. They also have other capabilities such as code-completion, syntax highlighting, error highlighting and checks, objects, and variable explorers. You ll find a list of IDEs used specially for Python at I suggest using the Spyder IDE or IDLE, which comes with the Anaconda Python distribution for writing and executing our code. But you will play much of the time with the jupyter notebooks.

19 Installing This section covers details regarding how to set up your Python environment in Windows with minimal effort and the main components required. First, head over to the official Python website and download Python from You might also find Python installed on your Ubuntu Windows version A great alternative is to download a complete Python distribution with over 700 packages, known as the Anaconda Python distribution, from Continuum Analytics, which is built specially for data science and analytics, at

20 This package provides a lot of advantages, especially for Windows users, where installing some of the packages like numpy and scipy can sometimes cause issues. Anaconda comes with conda, an open source package and environment management system, and Spyder (Scientific Python Development Environment), an IDE for writing and executing your code.

21 Once the installation is complete, either start the Python or IPython shell from the Anaconda command prompt or start up Spyder by doubleclicking the icon

22 Python The standard way to use the Python programming language is to use the Python interpreter to run python code. The python interpreter is a program that reads and execute the python code. At the command prompt, the command python is used to invoke the Python interpreter.

23 IPython IPython is an interactive shell that addresses the limitation of the standard python interpreter, and it is a work-horse for scientific use of python

24 IDLE Type in idle in anaconda command line File New File Type in your code, for example: print('monty Python') Save your file with the name monty.py Run Run Module

25 Close idle. Now suppose you want to import your package on the ipython prompt Before you can do that, you should move to the directory where your code is. import os print os.getcwd() os.chdir('c:\\users\uname\desktop\python') Now import your package import it: from monty import *

26 If you want you can define a permanent path where your files are saved and executed, thus avoiding the need to change or specify a directory To do this go to C:\Anaconda3\Lib\site.py and on PREFIXES define your path (e.g., 'H:\\Backup\\Research\\Programming\\CodigoPython You can now import the package from python prompt: from monty import * (without the need to change directory) You can also execute your program on anaconda prompt. Go to the folder where your program is and type in: python monty.py

27 Spyder Spyder is a MATLAB-like IDE for scientific computing with python. It provides a complete IDE to write and execute code in both the regular Python and IPython shell.

28 Jupyter notebook Jupyter notebook is an HTML-based notebook environment for Python, similar to Mathematica or Maple. The working directory of Jupyter is: c:\user\nomeuser

29 If you want to change that directory do the following: (1) On anaconda command line type in the following: jupyter notebook -- generate-config This will generate a file jupyter/jupyter_notebook_config.py on the folder indicated during the execution of the command. Open that file and search for: c.notebookapp.notebook_dir Specify your new working directory (e.g., H:\\JupyterNotebooks ) and remove the #

30 If you want to change that directory do the following: 2. Search for Jupyter Notebook on Windows search feature - right click open localização do ficheiro Right click Propriedades - Atalho Em iniciar colocar o endereço definido anteriormente (e.g., H:\\JupyterNotebooks ) No destino (no final) remover: %USERPROFILE%

31 You can use either the pip or conda commands to install, uninstall, and upgrade packages. The conda package manager is better than pip in several aspects because it provides a holistic view of which dependencies are going to be upgraded and the specific versions and other details during installation. Also pip often fails to install some packages in Windows, but conda has no such issues during installation.

32 Check for libraries already installed: Or you can also do that on Anaconda navigator:

33 If you are working with anaconda and need any special packages not included in the distribution, you have two options: Try to install it within the shell (in this case launch the anaconda prompt and enter in the shell by typing python or ipython). First try:!conda install name_of_package If it fails try this:!pip install name_of_package Note that the exclamation points tell IPython to send those commands directly to the computer - not to Python itself.

34 Try to install it in the anaconda prompt (in this case launch the anaconda prompt. You must omit the exclamation mark) Try: conda install name_of_package If it fails try this: pip install name_of_package New libraries will be installed on a folder similar to this: C:\Users\campo\Anaconda2\Lib\site-packages

35 If you are working with Python directly you should work within the dos prompt or bash and type in: pip install name_package New libraries will be installed on a folder similar to this: C:\Users\campo\AppData\Local\Programs\Python\Python36\Lib\site-packages

36 What is pip? PyPI, the Python Package Index, is a collection of every public Python package. The pip command connects to PyPI online, finds the package by name, downloads the source code, and tries to install it. The conda project aims to make installation faster and more reliable than pip. It is maintained by the same people who distribute the Anaconda installer. Not every package is available through conda yet, but it's always worth trying conda first. It's always faster than pip, it's more user-friendly, and it's much less error-prone.

37 What if there is a project on GitHub? First, open the anaconda prompt. Then, use the Git to clone the repository from Github and install it manually: git clone cd tweepy python setup.py install Whatever the case you should always import the library: Import tweepy

38 Visualize the execution of your code (

39 Execute your own code online on jupyter / docker (

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