CodeInvestigator - Python
by pvergainThere is a Python version of CodeInvestigator to debug your Python scripts with. The user interface is through a web browser. For this you need: * Python. Version 2.5 and over. * A Firefox browser
There is a Python version of CodeInvestigator to debug your Python scripts with. The user interface is through a web browser. For this you need: * Python. Version 2.5 and over. * A Firefox browser
Claroline est une plate-forme Open Source de formation à distance et de travail collaboratif. Elle permet aux formateurs de créer des espaces de cours en ligne et de gérer des activités de formation sur Internet. Traduite en 35 langues, Claroline bénéficie de l'appui d'une communauté mondiale d'utilisateurs et de développeurs
Ohloh is an open source network that connects people through the software they create and use.
We have attempted to collect a variety of data about the relative popularity of programming languages, mostly out of curiousity. To some degree popularity does matter - however it is clearly not the only thing to take into account when choosing a programming language. Most experienced programmers should be able to learn the basics of a new language in a week, and be productive with it in a few more weeks, although it will likely take much longer to truly master it.
The Open Komodo Project, based on the award-winning Komodo IDE, is a new initiative by ActiveState to create an open source platform for building developer environments. ActiveState has open-sourced elements of Komodo Edit, a free multi-language editor for dynamic languages based on Komodo IDE, to create the Open Komodo code base.
Store all your favourite tips, tricks, codes and snippets in one place, accessible from anywhere.
Shtooka.net has record the pronunciation of the conjugated forms of about 160 english irregular verbs which are usually presented in school manuals. This collection like the other SWAC collections that we provide, is distributed under a "Creative Commons Paternité 2.0" licence. These words has been pronunced by Alyson Heimer, an American student from the Massachusetts. We provide the collection as Tar archive in both Ogg and Flac formats from the site www.swac-collections.org.
Veusz is a scientific plotting package written in Python. It uses PyQt (Wiki) and Numpy. Veusz is designed to produce publication-ready Postscript output.
Welcome to the lift Web Framework lift is yet another web development framework. lift runs inside a Java web container and uses the Scala programming language for coding. lift stresses security, developer productivity, ease of deployment, ease of maintainability, performance, and compatibility with existing systems. lift borrows from the best of existing frameworks including Seaside's highly granular sessions and security, Rails fast flash-to-bang, Django's "more than just CRUD is included", and Erlyweb's scalability for Comet-style applications. lift is built on Scala, a hybrid Functional and O-O language that compiles code down to the Java Virtual Machine. Scala code can call any Java code and make use of all Java classes. Java code can call some Scala code. lift applications are packaged as WAR files and can be deployed on any Servlet 2.4 engine (e.g., Tomcat 5.5.xx, Jetty 6.0, etc.)
Comet is a software concept that enables web servers to send data to the client program (normally a web browser) without having any need for the client to request it. It allows creation of event-driven web applications, enabling real-time interaction otherwise impossible in a browser.
Java 6 introduces native support for dynamic scripting languages (JSR 223, scripting languages and Java technology.) This BOF session brings together leaders, users, and critics from the Jython, Groovy, PHP, Ruby, and many other scripting camps for an exchange of ideas to develop a common understanding of the state of the art and practical examples of using dynamic scripting languages to solve problems
Enunciate is a Web service deployment framework. It is not another Web service stack implementation. Rather, Enunciate leverages existing Web service technologies to provide a mechanism to build, package, deploy, and to clearly, accurately deliver your Web service API on the Java platform. Enunciate's novel approach to Web service development centers around leveraging all components of an API that are definied and maintained in original source code (as opposed to only those that are defined by compiled bytecode). This means that Web service development is done completely in source code, where it can be maintained using your favorite IDE and where the development entry barrier is low. However, by starting with original source code, Enunciate avoids the interoperabilty issues of code-first development by forcing developers at compile time to reconcile any ambiguities or other potential hazards in the formal contract. This model is formalized as the "compiled contract" development model. Currently, Enunciate generates code for the Java 1.4 platform and the Java 5 platform, but has plans to add modules that generate code for the .NET and C/C platforms in the future. Consult the roadmap for information on other modules in the pipe and how you can help.
Probably most of the gnuplot lovers in a scientific field use this program to draw a graph of some calculated results or experimental data. They see their results on their monitor, make some corrections, comparison of the calculated result with the experimental data, and so on. If it seems fine, the figure is saved in a postscript format and send it to a printer, otherwise an EPS file is included in a TeX document...
En 2004, les éditions Eyrolles avaient publié le «Cahier de l’admin Debian» de Raphaël Hertzog. Puis, en 2005, une deuxième édition. Ces deux éditions étaient focalisées sur Sarge, prenaient quelques rides avec le temps, et manquaient de détails sur certains domaines. Il fallait donc le mettre à jour. Mais ce qui n’aurait pu être qu’une troisième édition s’est en fait beaucoup enrichi, et méritait donc un nouveau titre. Le livre “Debian Etch” est donc sorti ce jeudi 29 novembre 2007. En plus d’un deuxième auteur (Roland Mas), cet ouvrage offre de nombreuses nouveautés par rapport au précédent : 1. une mise à jour complète sur tout ce qui a changé entre Sarge et Etch. La plupart des différences sont détaillées, ce qui en fait un bon bouquin même pour les lecteurs qui n’ont pas encore migré. 2. un nouveau chapitre sur l’administration avancée, qui présente RAID, LVM, les installations automatisées par FAI et par le Debian-Installer, la virtualisation avec Xen.. 3. un nouveau chapitre sur la sécurité, qui décrit les pare-feu, les systèmes de détection d’intrusion, SELinux, et surtout l’approche de la sécurité comme un processus et non comme la simple utilisation d’un ou plusieurs logiciels. 4. un « petit cours de rattrapage », qui contient des rappels qui peuvent être nécessaires pour certains lecteurs. Ça reprend le principe des encadrés « B. A. - BA », mais comme on a plus de place on peut se permettre d’entrer dans plus de détails. Ce chapitre peut ainsi constituer une introduction aux systèmes de type Unix, avec une description des concepts de processus et de système de fichiers, une explication détaillée de la séquence de démarrage d’un ordinateur, et un rappel des principales commandes de base. Le résultat est un livre complet sur Debian Etch, qui décrit à la fois les principes et les détails de la plupart des opérations d’administration d’un système Debian : installation, maintenance, supervision, migration, sécurité, mise en réseau, interface graphique, stockage, sauvegardes, automatisation, installations personnalisées avec paquets modifiés… Le lectorat ciblé reste vaste, puisque les situations décrites s’appliquent aussi bien dans le cadre d’un petit réseau familial que dans celui d’un système d’information d’entreprise. Et le « petit cours de rattrapage » pourra même être utilisé par des débutants ! Raphaël tient un site web sur le livre, où vous pourrez trouver plus de détails : le sommaire, la couverture, deux chapitres en téléchargement (1, 2), les liens cités (cliquables), des errata, la FAQ, une newsletter, mais aussi des goodies comme des fonds d’écran, et un jeu où dix exemplaires du livre seront distribués. Références : Titre : Debian Etch Auteurs : Raphaël Hertzog et Roland Mas ISBN : 978-2-212-12062-2 Site web : http://www.ouaza.com/livre/admin-debian/ Page sur Amazon: http://www.amazon.fr/exec/obidos/ASIN/2212120621/raphaelhertzo-21
There are countless reasons for parsing data, as well as tools and techniques to do it. But even the "right" tool may be insufficient when you need to do something new with the data. The same concerns exist for the integration of heterogeneous data sources. Sooner or later, the right tool for the right job happens to be a programming language. Oracle offers some very powerful utilities for loading, processing, and unloading data. SQL*Loader, Data Pump, external tables, Oracle Text, regular expressions—it's all there. Yet there is often a need to do things outside the database (or, trivially, perhaps you just weren't granted the necessary database privileges). Python delivers possibilities for efficient data parsing at a high level. The extensive standard library and many modules available for free on the Internet make it possible to work with data logic rather than dissecting bytes by hand.
Starting with the Python 2.4 release, cx_Oracle handles DATE and TIMESTAMP datatypes natively, mapping values of such columns to Python datetime objects from the datetime module. This offers certain advantages as datetime objects support arithmetic operations in-place. Built-in time zone support and several dedicated modules make Python a real time machine. The transition between Python and Oracle date/time datatypes is completely transparent to developers thanks to cx_Oracle's mapping mechanisms. Python developers might find Oracle's date arithmetic a bit odd at first, but only with a few tips it becomes completely clear and very reasonable. This part of the series will give you an in-depth understanding of date arithmetic from both Oracle and Python's point of view. Each of them offers rich support for handling date/time datatypes, so it is the programmer's choice which one to rely on. If you tend to put application logic inside the database or whether you prefer to encapsulate date/time operations in the application itself, the seamless integration of Oracle with Python offers you maximum flexibility with limited programming effort.
Among the core principles of Python's way of doing things there is a rule about having high-level interfaces to APIs. The Database API (in this case the Oracle API) is one example. Using the cx_Oracle Python module from Computronix, you can take command over the Oracle query model while maintaining compatibility with Python Database API Specification v2.0. The model of querying databases using DB API 2.0 remains consistent for all client libraries conforming to the specification. On top of this, Anthony Tuininga, the principal developer of cx_Oracle, has added a wide set of properties and methods that expose Oracle-specific features to developers. It is absolutely possible to use only the standard methods and forget about the "extra" ones, but in this installment you won't be doing that. The concept of universal database wrappers might work in some cases but at the same time, you lose all the optimizations that the RDBMS offers.
OpenStreetMap is a free editable map of the whole world. It is made by people like you. OpenStreetMap allows you to view, edit and use geographical data in a collaborative way from anywhere on Earth.
Geniusql is a public domain, low-level Object-Relational Mapper for Python applications. If you're familiar with Martin Fowler's work, you can think of Geniusql as providing a Data Source layer. It primarily uses a generic Table Data Gateway architecture (as opposed to the more tightly-coupled Active Record architecture recently popularized by Ruby On Rails and Django). If you want a more powerful solution, we recommend skipping Active Record and going straight to a Data Mapper like Dejavu. Dejavu uses Geniusql behind the scenes for RDBMS back ends, but allows you to mix and match them with RAM, filesystem, and other stores.
A few years ago I «fell in love» with Python , which is a dynamically typed interactive, object oriented scripting language. With a few extensions I found it very suitable for efficient visualization and problem solving in Scientific computing. So can it replace Matlab? For me its pretty close! For you? It depends on your needs, but have a look! Why I use Python * Python is a small, high level scripting language that sits on top of a efficient C library. Because of this, Python code is compact, and the resulting code can run at a speed close to C if the computationally intensive parts are done via library calls. * Short learning curve - I was almost instantly productive. * Python can be used interactively (like matlab), and documentation for most functions can be accessed via a built in help facility. * It is free (also in this regard) * The syntax invites you to write clean code. No ;'s at the end of lines, the block structure is described by indentation instead of Begin-End or {..}. Through the Numeric/numarray modules one gets powerful array syntax - inspired by languages such as Fortran 90, Matlab, Octave, Yorick etc. Python itself has also borrowed features from e.g. Lisp, with its interactivity and built in support for list manipulation. * Python has many other useful modules built in, one may for instance write a web server in just a few lines of code or work transparently with gzipped files (handy for analyzing large ascii data files) * Linking in and reusing Fortran subroutines is very easy using e.g. f2py mentioned below, or the Pyfort module found on www.python.org. Integration with C is of course even tighter since the most popular python is written in C. (yes. there is a java python...) * It is possible to work in single precision, which is sufficient for most scientific purposes. This makes it easier to work with large datasets/arrays using only half the memory compared to e.g. matlab. As my basic setup I use Python with the following extensions: Numpy: a.k.a. Numeric python, contain the advanced array syntax, as well as powerful and commonly used functions that can be applied to the multi dimensional arrays. Pygist: Gist is a very fast graphics library for 2D and 3D plots written directly for X11, but also ported to Mac and Windows. Gist is a part of the Yorick language. Pygist contain the Python bindings, read about it here. A recent version of Pygist can be found here. Pygist is currently also a part of a distribution of Python packages called Scipy, that can be found here. f2py: Makes connecting Fortran subroutines a breeze! Also a part of Scipy. A complete example: wrap this subroutine in a Python function returning "dist": [avle@tindved test]$ cat r1.f90 subroutine r1(x,y,n,dist) real x(n),y(n) !f2py intent(out) dist xl=0.0 ; yl=0.0 ; vp=0.0 do i=1,n xl=xl + x(i)**2 ; yl=yl + y(i)**2 vp=vp + x(i)*y(i) end do if(vp>=0.0)then dist = acos(sqrt(vp/(xl*yl))) else dist = 4*atan(1.0)-acos(sqrt(-vp/(xl*yl))) end if end subroutine r1 [avle@tindved test]$ ls r1.f90 [avle@tindved test]$ f2py -c -m r1 --fcompiler=g95 r1.f90 ..lots of output... [avle@tindved test]$ ls r1.f90 r1.so* [avle@tindved test]$ python2 Python 2.2.3 (#1, Feb 15 2005, 02:41:06) [GCC 3.2.3 20030502 (Red Hat Linux 3.2.3-49)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import Numeric as nx, r1 >>> a=nx.array((2.3,2.2)) ; b=nx.array((3.2,2.1)) >>> r1.r1(a,b) 1.2827057838439941 >>>
pynetfilter_conntrack is a Python binding of libnetfilter_conntrack. The binding is the file pynetfilter_conntrack.py and you have also a clone of conntrack program: conntrack.py. See also pyctd project. What's this? ¶ This python library is based on libnetfilter_conntrack, which lets you manipulate conntrack objects. In other words, pynetfilter_conntrack lets you deal with Netfilter's stateful inspection objects from the Python world. Practically, for the administrator, this means you can now easily close connections of your choice on your Linux [2.6] firewall. You can also receive informations about all connections (how many packets have gone through, how many bytes, etc.). You will even be able to create new objects in the Connection Tracking (this means that complex protocols such as FTP, P2P, etc. can have Python dealing with them rather than complex kernel modules).
Scapy6 is an extension to Scapy that provides support for IPv6 (and much more).
The Python Packaging Index (the software formerly known as Cheeseshop) is now available at http://pypi.python.org/pypi The old addresses (www.python.org/pypi, and cheeseshop.python.org/pypi) will continue to work, either as aliases or using HTTP redirections. The software was renamed to its old name (PyPI - Python Package Index), as the Cheeseshop name was ever confusing people unfamiliar with British television comedy sketch (and puzzling even to people familiar with the sketch, as you *can* get packages from the package index). The Python Package Index is a repository of software for the Python programming language. There are currently 2609 packages here. You may:
Raisons de choisir des Logiciels Libres pour vos systèmes embarqués Cette présentation énumère les principaux atouts des Logiciels Libres pour les systèmes embarqués, ainsi que leurs points faibles. Elle peut être utile pour considérer tous les arguments pour et contre lors du choix entre un système d'exploitation libre ou un système propriétaire.