Biopython Project Update 2013
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Ironpython in Action
IronPytho IN ACTION Michael J. Foord Christian Muirhead FOREWORD BY JIM HUGUNIN MANNING IronPython in Action Download at Boykma.Com Licensed to Deborah Christiansen <[email protected]> Download at Boykma.Com Licensed to Deborah Christiansen <[email protected]> IronPython in Action MICHAEL J. FOORD CHRISTIAN MUIRHEAD MANNING Greenwich (74° w. long.) Download at Boykma.Com Licensed to Deborah Christiansen <[email protected]> For online information and ordering of this and other Manning books, please visit www.manning.com. The publisher offers discounts on this book when ordered in quantity. For more information, please contact Special Sales Department Manning Publications Co. Sound View Court 3B fax: (609) 877-8256 Greenwich, CT 06830 email: [email protected] ©2009 by Manning Publications Co. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by means electronic, mechanical, photocopying, or otherwise, without prior written permission of the publisher. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps. Recognizing the importance of preserving what has been written, it is Manning’s policy to have the books we publish printed on acid-free paper, and we exert our best efforts to that end. Recognizing also our responsibility to conserve the resources of our planet, Manning books are printed on paper that is at least 15% recycled and processed without the use of elemental chlorine. -
102-401-08 3 Fiches SOFTW.Indd
PYPY to be adapted to new platforms, to be used in education Scope and to give new answers to security questions. Traditionally, fl exible computer languages allow to write a program in short time but the program then runs slow- Contribution to standardization er at the end-user. Inversely, rather static languages run 0101 faster but are tedious to write programs in. Today, the and interoperability issues most used fl exible and productive computer languages Pypy does not contribute to formal standardization proc- are hard to get to run fast, particularly on small devices. esses. However, Pypy’s Python implementation is practi- During its EU project phase 2004-2007 Pypy challenged cally interoperable and compatible with many environ- this compromise between fl exibility and speed. Using the ments. Each night, around 12 000 automatic tests ensure platform developed in Pypy, language interpreters can that it remains robust and compatible to the mainline now be written at a higher level of abstraction. Pypy au- Python implementation. tomatically produces effi cient versions of such language interpreters for hardware and virtual target environ- Target users / sectors in business ments. Concrete examples include a full Python Inter- 010101 10 preter, whose further development is partially funded by and society the Google Open Source Center – Google itself being a Potential users are developers and companies who have strong user of Python. Pypy also showcases a new way of special needs for using productive dynamic computer combining agile open-source development and contrac- languages. tual research. It has developed methods and tools that support similar projects in the future. -
Scons API Docs Version 4.2
SCons API Docs version 4.2 SCons Project July 31, 2021 Contents SCons Project API Documentation 1 SCons package 1 Module contents 1 Subpackages 1 SCons.Node package 1 Submodules 1 SCons.Node.Alias module 1 SCons.Node.FS module 9 SCons.Node.Python module 68 Module contents 76 SCons.Platform package 85 Submodules 85 SCons.Platform.aix module 85 SCons.Platform.cygwin module 85 SCons.Platform.darwin module 86 SCons.Platform.hpux module 86 SCons.Platform.irix module 86 SCons.Platform.mingw module 86 SCons.Platform.os2 module 86 SCons.Platform.posix module 86 SCons.Platform.sunos module 86 SCons.Platform.virtualenv module 87 SCons.Platform.win32 module 87 Module contents 87 SCons.Scanner package 89 Submodules 89 SCons.Scanner.C module 89 SCons.Scanner.D module 93 SCons.Scanner.Dir module 93 SCons.Scanner.Fortran module 94 SCons.Scanner.IDL module 94 SCons.Scanner.LaTeX module 94 SCons.Scanner.Prog module 96 SCons.Scanner.RC module 96 SCons.Scanner.SWIG module 96 Module contents 96 SCons.Script package 99 Submodules 99 SCons.Script.Interactive module 99 SCons.Script.Main module 101 SCons.Script.SConsOptions module 108 SCons.Script.SConscript module 115 Module contents 122 SCons.Tool package 123 Module contents 123 SCons.Variables package 125 Submodules 125 SCons.Variables.BoolVariable module 125 SCons.Variables.EnumVariable module 125 SCons.Variables.ListVariable module 126 SCons.Variables.PackageVariable module 126 SCons.Variables.PathVariable module 127 Module contents 127 SCons.compat package 129 Module contents 129 Submodules 129 SCons.Action -
Porting of Micropython to LEON Platforms
Porting of MicroPython to LEON Platforms Damien P. George George Robotics Limited, Cambridge, UK TEC-ED & TEC-SW Final Presentation Days ESTEC, 10th June 2016 George Robotics Limited (UK) I a limited company in the UK, founded in January 2014 I specialising in embedded systems I hardware: design, manufacturing (via 3rd party), sales I software: development and support of MicroPython code D.P. George (George Robotics Ltd) MicroPython on LEON 2/21 Motivation for MicroPython Electronics circuits now pack an enor- mous amount of functionality in a tiny package. Need a way to control all these sophisti- cated devices. Scripting languages enable rapid development. Is it possible to put Python on a microcontroller? Why is it hard? I Very little memory (RAM, ROM) on a microcontroller. D.P. George (George Robotics Ltd) MicroPython on LEON 3/21 Why Python? I High-level language with powerful features (classes, list comprehension, generators, exceptions, . ). I Large existing community. I Very easy to learn, powerful for advanced users: shallow but long learning curve. I Ideal for microcontrollers: native bitwise operations, procedural code, distinction between int and float, robust exceptions. I Lots of opportunities for optimisation (this may sound surprising, but Python is compiled). D.P. George (George Robotics Ltd) MicroPython on LEON 4/21 Why can't we use existing CPython? (or PyPy?) I Integer operations: Integer object (max 30 bits): 4 words (16 bytes) Preallocates 257+5=262 ints −! 4k RAM! Could ROM them, but that's still 4k ROM. And each integer outside the preallocated ones would be another 16 bytes. I Method calls: led.on(): creates a bound-method object, 5 words (20 bytes) led.intensity(1000) −! 36 bytes RAM! I For loops: require heap to allocate a range iterator. -
Python Data Analytics Open a File for Reading: Infile = Open("Input.Txt", "R")
DATA 301: Data Analytics (2) Python File Input/Output DATA 301 Many data processing tasks require reading and writing to files. Introduction to Data Analytics I/O Type Python Data Analytics Open a file for reading: infile = open("input.txt", "r") Dr. Ramon Lawrence Open a file for writing: University of British Columbia Okanagan outfile = open("output.txt", "w") [email protected] Open a file for read/write: myfile = open("data.txt", "r+") DATA 301: Data Analytics (3) DATA 301: Data Analytics (4) Reading from a Text File (as one String) Reading from a Text File (line by line) infile = open("input.txt", "r") infile = open("input.txt", "r") for line in infile: print(line.strip('\n')) val = infile.read() Read all file as one string infile.close() print(val) infile.close() Close file # Alternate syntax - will auto-close file with open("input.txt", "r") as infile: for line in infile: print(line.strip('\n')) DATA 301: Data Analytics (5) DATA 301: Data Analytics (6) Writing to a Text File Other File Methods outfile = open("output.txt", "w") infile = open("input.txt", "r") for n in range(1,11): # Check if a file is closed outfile.write(str(n) + "\n") print(infile.closed)# False outfile.close() # Read all lines in the file into a list lines = infile.readlines() infile.close() print(infile.closed)# True DATA 301: Data Analytics (7) DATA 301: Data Analytics (8) Use Split to Process a CSV File Using csv Module to Process a CSV File with open("data.csv", "r") as infile: import csv for line in infile: line = line.strip(" \n") with open("data.csv", "r") as infile: fields = line.split(",") csvfile = csv.reader(infile) for i in range(0,len(fields)): for row in csvfile: fields[i] = fields[i].strip() if int(row[0]) > 1: print(fields) print(row) DATA 301: Data Analytics (9) DATA 301: Data Analytics (10) List all Files in a Directory Python File I/O Question Question: How many of the following statements are TRUE? import os print(os.listdir(".")) 1) A Python file is automatically closed for you. -
Goless Documentation Release 0.6.0
goless Documentation Release 0.6.0 Rob Galanakis July 11, 2014 Contents 1 Intro 3 2 Goroutines 5 3 Channels 7 4 The select function 9 5 Exception Handling 11 6 Examples 13 7 Benchmarks 15 8 Backends 17 9 Compatibility Details 19 9.1 PyPy................................................... 19 9.2 Python 2 (CPython)........................................... 19 9.3 Python 3 (CPython)........................................... 19 9.4 Stackless Python............................................. 20 10 goless and the GIL 21 11 References 23 12 Contributing 25 13 Miscellany 27 14 Indices and tables 29 i ii goless Documentation, Release 0.6.0 • Intro • Goroutines • Channels • The select function • Exception Handling • Examples • Benchmarks • Backends • Compatibility Details • goless and the GIL • References • Contributing • Miscellany • Indices and tables Contents 1 goless Documentation, Release 0.6.0 2 Contents CHAPTER 1 Intro The goless library provides Go programming language semantics built on top of gevent, PyPy, or Stackless Python. For an example of what goless can do, here is the Go program at https://gobyexample.com/select reimplemented with goless: c1= goless.chan() c2= goless.chan() def func1(): time.sleep(1) c1.send(’one’) goless.go(func1) def func2(): time.sleep(2) c2.send(’two’) goless.go(func2) for i in range(2): case, val= goless.select([goless.rcase(c1), goless.rcase(c2)]) print(val) It is surely a testament to Go’s style that it isn’t much less Python code than Go code, but I quite like this. Don’t you? 3 goless Documentation, Release 0.6.0 4 Chapter 1. Intro CHAPTER 2 Goroutines The goless.go() function mimics Go’s goroutines by, unsurprisingly, running the routine in a tasklet/greenlet. -
Biopython BOSC 2007
The 8th annual Bioinformatics Open Source Conference (BOSC 2007) 18th July, Vienna, Austria Biopython Project Update Peter Cock, MOAC Doctoral Training Centre, University of Warwick, UK Talk Outline What is python? What is Biopython? Short history Project organisation What can you do with it? How can you contribute? Acknowledgements The 8th annual Bioinformatics Open Source Conference Biopython Project Update @ BOSC 2007, Vienna, Austria What is Python? High level programming language Object orientated Open Source, free ($$$) Cross platform: Linux, Windows, Mac OS X, … Extensible in C, C++, … The 8th annual Bioinformatics Open Source Conference Biopython Project Update @ BOSC 2007, Vienna, Austria What is Biopython? Set of libraries for computational biology Open Source, free ($$$) Cross platform: Linux, Windows, Mac OS X, … Sibling project to BioPerl, BioRuby, BioJava, … The 8th annual Bioinformatics Open Source Conference Biopython Project Update @ BOSC 2007, Vienna, Austria Popularity by Google Hits Python 98 million Biopython 252,000 Perl 101 million BioPerlBioPerl 610,000 Ruby 101 million BioRuby 122,000 Java 289 million BioJava 185,000 Both Perl and Python are strong at text Python may have the edge for numerical work (with the Numerical python libraries) The 8th annual Bioinformatics Open Source Conference Biopython Project Update @ BOSC 2007, Vienna, Austria Biopython history 1999 : Started by Jeff Chang & Andrew Dalke 2000 : Biopython 0.90, first release 2001 : Biopython 1.00, “semi-complete” 2002 -
Setting up Your Environment
APPENDIX A Setting Up Your Environment Choosing the correct tools to work with asyncio is a non-trivial choice, since it can significantly impact the availability and performance of asyncio. In this appendix, we discuss the interpreter and the packaging options that influence your asyncio experience. The Interpreter Depending on the API version of the interpreter, the syntax of declaring coroutines change and the suggestions considering API usage change. (Passing the loop parameter is considered deprecated for APIs newer than 3.6, instantiating your own loop should happen only in rare circumstances in Python 3.7, etc.) Availability Python interpreters adhere to the standard in varying degrees. This is because they are implementations/manifestations of the Python language specification, which is managed by the PSF. At the time of this writing, three relevant interpreters support at least parts of asyncio out of the box: CPython, MicroPython, and PyPy. © Mohamed Mustapha Tahrioui 2019 293 M. M. Tahrioui, asyncio Recipes, https://doi.org/10.1007/978-1-4842-4401-2 APPENDIX A SeTTinG Up YouR EnViROnMenT Since we are ideally interested in a complete or semi-complete implementation of asyncio, our choice is limited to CPython and PyPy. Both of these products have a great community. Since we are ideally using a lot powerful stdlib features, it is inevitable to pose the question of implementation completeness of a given interpreter with respect to the Python specification. The CPython interpreter is the reference implementation of the language specification and hence it adheres to the largest set of features in the language specification. At the point of this writing, CPython was targeting API version 3.7. -
The Bioperl Toolkit: Perl Modules for the Life Sciences
Downloaded from genome.cshlp.org on January 25, 2012 - Published by Cold Spring Harbor Laboratory Press The Bioperl Toolkit: Perl Modules for the Life Sciences Jason E. Stajich, David Block, Kris Boulez, et al. Genome Res. 2002 12: 1611-1618 Access the most recent version at doi:10.1101/gr.361602 Supplemental http://genome.cshlp.org/content/suppl/2002/10/20/12.10.1611.DC1.html Material References This article cites 14 articles, 9 of which can be accessed free at: http://genome.cshlp.org/content/12/10/1611.full.html#ref-list-1 Article cited in: http://genome.cshlp.org/content/12/10/1611.full.html#related-urls Email alerting Receive free email alerts when new articles cite this article - sign up in the box at the service top right corner of the article or click here To subscribe to Genome Research go to: http://genome.cshlp.org/subscriptions Cold Spring Harbor Laboratory Press Downloaded from genome.cshlp.org on January 25, 2012 - Published by Cold Spring Harbor Laboratory Press Resource The Bioperl Toolkit: Perl Modules for the Life Sciences Jason E. Stajich,1,18,19 David Block,2,18 Kris Boulez,3 Steven E. Brenner,4 Stephen A. Chervitz,5 Chris Dagdigian,6 Georg Fuellen,7 James G.R. Gilbert,8 Ian Korf,9 Hilmar Lapp,10 Heikki Lehva¨slaiho,11 Chad Matsalla,12 Chris J. Mungall,13 Brian I. Osborne,14 Matthew R. Pocock,8 Peter Schattner,15 Martin Senger,11 Lincoln D. Stein,16 Elia Stupka,17 Mark D. Wilkinson,2 and Ewan Birney11 1University Program in Genetics, Duke University, Durham, North Carolina 27710, USA; 2National Research Council of -
Optimizing and Evaluating Transient Gradual Typing
Optimizing and Evaluating Transient Gradual Typing Michael M. Vitousek Jeremy G. Siek Avik Chaudhuri Indiana University, USA Indiana University, USA Facebook Inc., USA [email protected] [email protected] [email protected] Abstract 1 Introduction Gradual typing enables programmers to combine static and Gradual typing enables programmers to gradually evolve dynamic typing in the same language. However, ensuring their programs from the dynamic typing, which allows flex- sound interaction between the static and dynamic parts can ibility, to static typing, providing security [Siek and Taha incur runtime cost. In this paper, we analyze the perfor- 2006; Tobin-Hochstadt and Felleisen 2006]. Over the last mance of the transient design for gradual typing in Retic- decade, gradual typing has been of great interest to both ulated Python, a gradually typed variant of Python. This the research community [Ahmed et al. 2011; Allende et al. approach inserts lightweight checks throughout a program 2013a; Rastogi et al. 2012; Ren et al. 2013; Siek et al. 2015b; rather than installing proxies on higher order values. We Swamy et al. 2014; Takikawa et al. 2012], and to industry, show that, when using CPython as a host, performance de- which has introduced several languages with elements of creases as programs evolve from dynamic to static types, up gradual typing, such as TypeScript [Microsoft 2012], Flow to a 6× slowdown compared to equivalent Python programs. [Facebook 2014], and Dart [Google 2011]. Many existing To reduce this overhead, we design a static analysis and gradually typed languages operate by translating a “surface optimization that removes redundant runtime checks, em- language” program (i.e. -
Bioinformatics and Computational Biology with Biopython
Biopython 1 Bioinformatics and Computational Biology with Biopython Michiel J.L. de Hoon1 Brad Chapman2 Iddo Friedberg3 [email protected] [email protected] [email protected] 1 Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan 2 Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA 3 The Burnham Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA Keywords: Python, scripting language, open source 1 Introduction In recent years, high-level scripting languages such as Python, Perl, and Ruby have gained widespread use in bioinformatics. Python [3] is particularly useful for bioinformatics as well as computational biology because of its numerical capabilities through the Numerical Python project [1], in addition to the features typically found in scripting languages. Because of its clear syntax, Python is remarkably easy to learn, making it suitable for occasional as well as experienced programmers. The open-source Biopython project [2] is an international collaboration that develops libraries for Python to facilitate common tasks in bioinformatics. 2 Summary of current features of Biopython Biopython contains parsers for a large number of file formats such as BLAST, FASTA, Swiss-Prot, PubMed, KEGG, GenBank, AlignACE, Prosite, LocusLink, and PDB. Sequences are described by a standard object-oriented representation, creating an integrated framework for manipulating and ana- lyzing such sequences. Biopython enables users to -
Introducing Python
Introducing Python Bill Lubanovic Introducing Python by Bill Lubanovic Copyright © 2015 Bill Lubanovic. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://safaribooksonline.com). For more information, contact our corporate/ institutional sales department: 800-998-9938 or [email protected]. Editors: Andy Oram and Allyson MacDonald Indexer: Judy McConville Production Editor: Nicole Shelby Cover Designer: Ellie Volckhausen Copyeditor: Octal Publishing Interior Designer: David Futato Proofreader: Sonia Saruba Illustrator: Rebecca Demarest November 2014: First Edition Revision History for the First Edition: 2014-11-07: First release 2015-02-20: Second release See http://oreilly.com/catalog/errata.csp?isbn=9781449359362 for release details. The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Introducing Python, the cover image, and related trade dress are trademarks of O’Reilly Media, Inc. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and O’Reilly Media, Inc. was aware of a trademark claim, the designations have been printed in caps or initial caps. While the publisher and the author have used good faith efforts to ensure that the information and instruc‐ tions contained in this work are accurate, the publisher and the author disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work.