This course will help you to expertise the usage of Python in Data Science world.
Carter your Python Knowledge so that it can be utilized to get the Insights of Data using Methodologies and Techniques of Data Science...
Objective:
Understand the concepts of Data science and Python
You will be able to use Python in Discovering Data.
You will have an idea of Statistical and Analytical methods to deal with huge data sets.
You will gain an expertise on Regular Expressions, looping functions and concepts of Object Oriented Programming.
You will be able to create business algorithms and data models using Python and it's techniques.
Work on Real-life Projects will help you to get a practical experience of real scenarios of IT Industry.
Start learning Python for Data Science from basics to advance levels here...
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I am pleased to announce release 2017.1 of SfePy.
Description
-----------
SfePy (simple finite elements in Python) is a software for solving systems of
coupled partial differential equations by the finite element method or by the
isogeometric analysis (limited support). It is distributed under the new BSD
license.
Home page: http://sfepy.org
Mailing list: http://groups.google.com/group/sfepy-devel
Git (source) repository, issue tracker: https://github.com/sfepy/sfepy
Highlights of this release
--------------------------
- spline-box parametrization of an arbitrary field
- conda-forge recipe (thanks to Daniel Wheeler)
- fixes for Python 3.6
For full release notes see http://docs.sfepy.org/doc/release_notes.html#id1
(rather long and technical).
Cheers,
Robert Cimrman
---
Contributors to this release in alphabetical order:
Siwei Chen
Robert Cimrman
Jan Heczko
Vladimir Lukes
Matyas Novak
Hi all,
I'm delighted to announce the release of Sphinx 1.5.3, now available on
the Python package index at <http://pypi.python.org/pypi/Sphinx>.
It includes about 3 new feature and 16 bug fixes for the 1.5.2 release series.
For the full changelog, go to
<http://www.sphinx-doc.org/en/stable/changes.html>.
Thanks to all collaborators and contributers!
What is it?
===========
Sphinx is a tool that makes it easy to create intelligent and beautiful
documentation for Python projects (or other documents consisting of
multiple reStructuredText source files).
Website: http://sphinx-doc.org/
IRC: #sphinx-doc on irc.freenode.net
Enjoy!
--
Takeshi KOMIYA
Hi everyone,
I'd like to announce a couple of simple packages related to Jupyter notebooks.
tex2ipy: https://github.com/prabhuramachandran/tex2ipy
This simple tool makes it relatively easy to convert a LaTeX beamer presentation
to a Jupyter/IPython notebook using RISE[1].
The second tool is:
ipyaml: https://github.com/prabhuramachandran/ipyaml
This allows Jupyter to store notebook files as easy-to-edit YAML files. It
supports both code/markdown and outputs so is entirely compatible with .ipynb
files (version 4 of the notebook format). Output dumping can be disabled if
needed. This package is similar to notedown and ipymd but offers complete
compatibility with .ipynb files.
Installation
------------
Both packages can be installed using pip.
$ pip install tex2ipy # Works only with Python3.x
$ pip install ipyaml
cheers,
Prabhu
[1] https://github.com/damianavila/RISE
(This mail announces the opening of registration for a Python-Event in
Cologne, Germany, held in German language, so what follows is in German
too.)
Liebe Python-Freunde,
die Anmeldung zum PythonCamp Cologne 2017 ist ab sofort eröffnet!
http://pythoncamp.de/
Bitte beachtet die Hinweise zur Anmeldung weiter unten.
Das PythonCamp Cologne findet am 8. - 9.04.2017 in Köln (Deutz) in den
Räumen der GFU Cyrus AG statt.
Die zweitägige Veranstaltung richtet sich an alle, die sich für die
Programmiersprache Python und deren Einsatz interessieren - sei es im
Bereich Web Development, Automatisierung, Scientific Computing oder
einfach nur zum Spaß. Die Themen des PythonCamps sind so vielfältig wie
die Einsatzmöglichkeiten von Python selbst, denn das Programm wird - wie
bei einem BarCamp üblich - von den Teilnehmern selbst gestaltet. Bitte
macht daher bereits im Vorfeld Rege von der Möglichkeit Gebrauch,
Themenvorschläge auf der Webseite einzutragen (Reiter "Sessionvorschläge")!
Wir freuen uns auf Euer zahlreiches Erscheinen und spannende Sessions!
Das PythonCamp Orga-Team
Hinweise:
Die Anmeldung zu PythonCamp Cologne 2017 ist kostenlos. Die maximale
Teilnehmerzahl ist begrenzt. Für die Anmeldung ist es notwendig, einen
Account auf der Camper-Webseite anzulegen (siehe Link "Registrieren"
oben rechts). Sobald man bei Camper angemeldet ist, geht man auf die
Seite des PythonCamp (siehe Link ganz oben) und klickt auf den Reiter
"Veranstaltungen". Dort muss man für *jede* Einzelveranstaltung, an der
man teilnehmen möchte, auf "Ich gehe" klicken. Damit landet man entweder
auf der Teilnehmerliste der Einzelveranstaltung oder auf der Warteliste,
wenn die maximale Teilnehmerzahl erreicht ist. Um zu kontrollieren, ob
man auf der richtigen Liste gelandet ist, kann man auf den Namen der
Einzelveranstaltung klicken. Außerdem erhält man eine Bestätigung der
Anmeldung an die E-Mailadresse, mit der man sich registriert hat.
Klickt man auf "vielleicht", landet man auf der Interessentenliste. Von
dort erfolgt *keine* automatische Übertragung in die Teilnehmerliste.
Sofern man sich später entschließt, tatsächlich am BarCamp teilnehmen zu
wollen, muss man die Teilnahmeoption an der selben Stelle ändern.
Falls Ihr euch anmeldet und später feststellt, dass Ihr doch nicht
kommen könnt, meldet euch bitte wieder ab, so dass ggf. weitere
Teilnehmer von der Warteliste nachrücken können. Dies gilt auch, wenn
Ihr nur an einem Tag nicht könnt.
Bitte beachtet weiterhin, dass die Teilnahme am Frühankommer-Treffen und
der Abendveranstaltung auf eigene Kosten erfolgt. Die Verpflegung auf
dem PythonCamp (Mittagessen Samstag/Sonntag, Frühstück Sonntag, Getränke
tagsüber) ist für die Teilnehmer kostenlos und wird durch unsere
großzügigen Sponsoren ermöglicht.
Für die Anreise und Unterkunft ist jeder Teilnehmer selbst verantwortlich.
--
Christopher Arndt
PythonCamp Orga-Team
info(a)pythoncamp.de
http://pythoncamp.de
PISI is an efficient, compact, feature-rich package manager written in Python.
You may find the sources of the revived original development branch of PISI on github:
https://github.com/examachine/pisi
The current revision is 1.1_beta12. I uploaded this revision from my local subversion working copies, it belongs to the last development branch that I maintained in Pardus Linux project. You may see the details about this branch for yourself:
$ svn info .
Path: .
Working Copy Root Path: /Volumes/Centauri/Users/malfunct/Code/projects/pisi-svn
URL: https://svn.uludag.org.tr/uludag/trunk/pisi
Repository Root: https://svn.uludag.org.tr/uludag
Repository UUID: 26e1f6f6-46e4-0310-a0b7-a8a415fd4c45
Revision: 8647
Node Kind: directory
Schedule: normal
Last Changed Author: caglar
Last Changed Rev: 8644
Last Changed Date: 2006-07-07 16:45:27 +0400 (Fri, 07 Jul 2006)
Since the PISI based Pardus project has officially ended, the development branch will likely remove Pardus dependencies (at least not make them mandatory), and continue as a next-generation portable package manager. That is, I will make it work on systems without other Pardus tools. I might use this to maintain an OS distribution for my AI startup. There are interesting platforms considered that might be useful.
Another objective is to fork one of the existing PISI based distributions, and make a brand new distribution. I just forked the latest official Pardus Linux repo on github.
My vision for PISI was way beyond Pardus, I thought I would have a reason to write more code if I worked towards that direction. Since I'm a parallel computing researcher, I might wish to make a distro to ease cluster installation for instance. Pardus did not go much beyond a basic KDE desktop distro and a server distro. There might be many variations as is the case with debian, and its derivative ubuntu. A PISI/debconf hybrid, or a configuration tool that is good enough to replace debconf would also be useful.
Eray Özkural, PhD
Hello all,
I'm glad to announce the release of pyo 0.8.3, available for python 2.7 and 3.5.
Pyo is a Python module written in C to help real-time digital signal processing
script creation. It is available for Windows, macOS and linux. It is released
under the LGPL 3 license.
For more info, downloads and other links, see the official web site:
http://ajaxsoundstudio.com/software/pyo/
The documentation:
http://ajaxsoundstudio.com/pyodoc/
For the latest sources and bug tracker:
https://github.com/belangeo/pyo
What's new:
New objects:
- SharedTable, an inter-process shared memory table (unix only).
- Particle2, An even more full control granular synthesis generator.
- TableFill, continuously fills a table with incoming samples.
- TableScan, Reads the content of a table in loop, without interpolation.
- MidiDispatcher, self-contained midi dispatcher thread.
Changes & bug fixes:
- Jack ports activation and auto-connection now happen in the boot process.
- Added "onlyonce" argument to Seq and Beat objects.
- Seq now accepts floating-point values as time units.
- Added "maxwindow" argument to TableWrite. This is the maximum number
of samples over which the object is allowed to interpolate. Useful to
avoid interpolation over the entire table when using a circular
writing pointer.
- Added "shape" argument to PVAmpMod and PVFreqMod objects. This
allows to change the modulation oscillator's waveform.
- Added setGlobalDur, setGlobalDel, getGlobalDur and getGlobalDel
methods to the Server object. These methods allow the user to manage
the start time and duration of audio objects globally.
- Fader and Adsr now start a new envelope from the current amplitude
value if the previous ramp has not finished yet.
Olivier Belanger
belangeo(a)gmail.com
http://olivier.ajaxsoundstudio.com/
----
P><A HREF="http://ajaxsoundstudio.com/software/pyo/">Pyo 0.8.3</A>
Python DSP library. (13-Feb-17)
Hi all,
I am very pleased to announce poliastro 0.6.0, a MIT licensed, pure
Python library for studying Orbital Mechanics and Astrodynamics problems!
This is a new major release, focused on refactoring some internal core
parts and improving the propagation functionality. Among the new
features are:
* Support for Python 3.6.
* Allow propagation functions to receive a callback
* New Orbit objects that supersede the State API.
See the changelog for a more complete list of changes:
http://poliastro.readthedocs.io/en/v0.6.0/changelog.html#new-in-poliastro-0…
You can install poliastro using either pip or conda:
$ pip install poliastro
$ conda install poliastro --channel conda-forge
And cite it using this DOI:
https://doi.org/10.5281/zenodo.290596
If you want to see an overview of poliastro capabilities, check out the
gallery of Jupyter notebooks where we list some specific applications
and interesting problems analyzed with this library:
http://nbviewer.jupyter.org/github/poliastro/poliastro/blob/v0.6.0/index.ip…
And if you prefer video format, don't miss the recording of my talk on
EuroPython 2016:
https://youtu.be/VCpTgU1pb5k
This release is probably the last one I'm going to make as an "almost
aerospace engineer", so wish me luck for my MSc final project :) You can
check its progress here:
https://github.com/Juanlu001/pfc-uc3m
poliastro is an open source collection of Python subroutines for solving
problems in Astrodynamics and Orbital Mechanics. It combines cutting
edge technologies like Python JIT compiling (using numba) with young,
well developed astronomy packages (like astropy and jplephem) to provide
a user friendly API for solving Astrodynamics problems. It is therefore
an experiment to mix the best Python open source practices with my love
for Orbital Mechanics.
The project is still a work in progress and the API is subject to
change. Contributions, bug reports, suggestions and advice are more than
welcome! If you are willing to help, please join our mailing list on
groups.io:
https://groups.io/g/poliastro-dev
/Per Python ad Astra!
/Juan Luis Cano Rodríguez
What’s new
=========
* SNMPv3 Reeder AES192/256 key localization algorithm implemented
* Broken 3DES encryption fixed
* Switched from PyCrypto to PyCryptodome for SNMPv3 crypto operations
* TEXTUAL-CONVENTION implementation improved to emit/consume human-friendlier values
More changes noted in the CHANGELOG [1].
What is pysnmp
============
The pysnmp library is a complete implementation of SNMPv1/v2c/v3 network management protocol
all in pure-Python. MIBs are automatically supported out-of-the-box, bindings to popular asynchronous
frameworks such as asyncio or Twisted are shipped along with the package.
More information on library features and API documentation can be found on project’s GitHub page [2].
1. https://github.com/etingof/pysnmp/blob/master/CHANGES.txt
2. https://github.com/etingof/pysnmp
On behalf of Twisted Matrix Laboratories, I am honoured to announce the release of Twisted 17.1!
The highlights of this release are:
- twisted.web.client.Agent now supports IPv6! It's also now the primary web client in Twisted, with twisted.web.client.getPage being deprecated in favour of it and Treq.
- twisted.web.server has had many cleanups revolving around timing out inactive clients.
- twisted.internet.ssl.CertificateOptions has had its `method` argument deprecated, in favour of the new raiseMinimumTo, lowerMaximumSecurityTo, and insecurelyLowerMinimumTo arguments, which take TLSVersion arguments. This allows you to better give a range of versions of TLS you wish to negotiate, rather than forcing yourself to any one version.
- twisted.internet.ssl.CertificateOptions will use OpenSSL's MODE_RELEASE_BUFFERS, which will let it free unused memory that was held by idle TLS connections.
- You can now call the new twist runner with `python -m twisted`.
- twisted.conch.ssh now has some ECDH key exchange support and supports `hmac-sha2-384`.
- Better Unicode support in twisted.internet.reactor.spawnProcess, especially on Windows on Python 3.6.
- More Python 3 porting in Conch, and more under-the-hood changes to facilitate a Twisted-wide jump to new-style classes only on Python 2 in 2018/2019. This release has also been tested on Python 3.6 on Linux.
- Lots of deprecated code removals, to make a sleeker, less confusing Twisted.
- 60+ closed tickets.
For more information, check the NEWS file (link provided below).
You can find the downloads at <https://pypi.python.org/pypi/Twisted <https://pypi.python.org/pypi/Twisted>> (or alternatively <http://twistedmatrix.com/trac/wiki/Downloads <http://twistedmatrix.com/trac/wiki/Downloads>>). The NEWS file is also available at <https://github.com/twisted/twisted/blob/twisted-17.1.0/NEWS <https://github.com/twisted/twisted/blob/twisted-17.1.0/NEWS>>.
Many thanks to everyone who had a part in this release - the supporters of the Twisted Software Foundation, the developers who contributed code as well as documentation, and all the people building great things with Twisted!
Twisted Regards,
Amber Brown (HawkOwl)
