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...
https://goo.gl/070wXw
After many months of work, we proudly announce the first beta release of pytypes.
(https://github.com/Stewori/pytypes)
pytypes is a toolbox for PEP-484 style typing, explicitly supporting
Python >= 3.3, Python 2.7, Jython >= 2.7.1, PyPy 3 (others not tested, but might work).
Its main features are
- decorators and profiler for runtime typechecking
- decorators for typesafe override checking of methods
- easily pull type information from stubfiles into __annotations__
- get_type_hints: workable backport to Python 2.7 (based on type comments)
- get_type_hints: variant that also takes stubfiles into account
- utility functions is_of_type(obj, tp) and is_subtype(subtype, supertype) for use with PEP 484 types
- decorator and profiler for generating stubfiles from type information observed and logged at runtime
- all these features work equally well on Python 2.7
- all these features smoothly work with OOP, i.e. methods, static methods, class methods, properties
This beta release is intended to allow testing of pytypes' approaches in real-world code.
Please check to what extend it suites your needs and help us to improve it.
Github: https://github.com/Stewori/pytypes/releases
PyPI: https://pypi.python.org/pypi/pytypes
License: Apache 2.0
Enjoy!
-Stefan
What is cx_Oracle?
cx_Oracle is a Python extension module that enables access to Oracle
Database for Python 3.x and 2.x and conforms to the Python database API 2.0
specifications with a number of enhancements.
Where do I get it?
https://oracle.github.io/python-cx_Oracle
The easiest method to install cx_Oracle is via pip as in
python -m pip install cx_Oracle --upgrade
What's new?
This release addresses issues found since the previous release. The full
release notes can be read here:
http://cx-oracle.readthedocs.io/en/latest/releasenotes.
html#version-6-0-2-august-2017
Please provide any feedback via GitHub issues (https://github.com/oracle/pyt
hon-cx_Oracle/issues).
Hello all,
I'm glad to announce the release of pyo 0.8.7, available for python
2.7, 3.5 and 3.6.
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
Bug Fixes:
- Disable Microsoft Midi devices by default. Added
Server.allowMicrosoftMidiDevices() method to enable them.
- Wrap jack api detection inside a try-except statement in case
jack2-dbus is used instead of jackd.
- Fixed bugs in Expr object's unicode handling.
- Fixed windows 10 dependencies.
- Fixed ending point of TableRec's time stream (now keep the last
value instead of switching back to 0).
- Fixed clean-up of VoiceManager object.
- Fixed encoding of file path on windows for various objects.
Enhancements:
- The server now allow up to 16 channel rms outputs for GUI drawing.
- Added getInterpolated method to PyoMatrixObject class. Returns the
interpolated value for a floating-point position in the matrix.
- OscDataSend now can send more than one message per buffer size.
- Update MacOS and Windows build routine to compile for python 2.7,
3.5 and 3.6.
Olivier Belanger
belangeo(a)gmail.com
http://olivier.ajaxsoundstudio.com/
----
P><A HREF="http://ajaxsoundstudio.com/software/pyo/">Pyo 0.8.7</A>
Python DSP library. (29-Aug-17)
On behalf of the Bokeh team, I am pleased to announce the release of version 0.12.7 of Bokeh!
OF SPECIAL NOTE: *** Network and Graph rendering is now supported! ***
Please see the announcement post at:
https://bokeh.github.io/blog/2017/8/29/release-0-12-7/
which has more information as well as live demonstrations.
If you are using Anaconda/miniconda, you can install it with conda:
conda install -c bokeh bokeh
Alternatively, you can also install it with pip:
pip install bokeh
Full information including details about how to use and obtain BokehJS are at:
http://bokeh.pydata.org/en/0.12.7/docs/installation.html
Issues, enhancement requests, and pull requests can be made on the Bokeh Github page: https://github.com/bokeh/bokeh
Documentation is available at http://bokeh.pydata.org/en/0.12.7
There are over 247 total contributors to Bokeh and their time and effort help make Bokeh such an amazing project and community. Thank you again for your contributions.
Finally (as always), for questions, technical assistance or if you're interested in contributing, questions can be directed to the Bokeh mailing list: bokeh(a)continuum.io or the Gitter Chat room: https://gitter.im/bokeh/bokeh
Thanks,
Bryan Van de Ven
Vulture - Find dead code
========================
Vulture finds unused code in Python programs. This is useful for
cleaning up and finding errors in large code bases. If you run Vulture
on both your library and test suite you can find untested code.
Due to Python's dynamic nature, static code analyzers like Vulture are
likely to miss some dead code. Also, code that is only called
implicitly may be reported as unused. Nonetheless, Vulture can be a
very helpful tool for higher code quality.
Download
========
https://github.com/jendrikseipp/vulturehttp://pypi.python.org/pypi/vulture
Features
========
* fast: static code analysis
* lightweight: only one module
* tested: tests itself and has complete test coverage
* complements pyflakes and has the same output syntax
* supports Python 2.6, 2.7 and 3.x
News
====
* Detect ``async`` function definitions (thanks @RJ722).
* Add ``Item.get_report()`` method (thanks @RJ722).
* Move method for finding Python modules out of Vulture class.
Cheers,
Jendrik
I'm happy to announce the immediate availability of Python 2.7.14
release candidate 1, a testing release for the latest bugfix release in
the Python 2.7 series.
Downloads of source code and binaries are at
https://www.python.org/downloads/release/python-2714rc1/
Please consider testing the release with your libraries and applications
and reporting any bugs to
https://bugs.python.org
A final release is expected in 3 weeks.
Regards,
Benjamin
2.7 release manager
(on behalf of 2.7's contributors)
An initial release of new Python library for Deep Learning: conx (pronounced
"connects"). Built on Keras, but with enhancements, and designed for
researchers, teaching, and learning.
Documentation: http://conx.readthedocs.io/
Installation: https://github.com/Calysto/conx
What niche does conx fill?
* designed for students and researchers that don't want to work with (or
don't know) numpy, matplotlib, or Keras functional-api
* tight integration with Jupyter notebooks
* widget-based app for easy exploration of ANN models
* error messages designed for humans
* standard input and target dataset API (separate from internal Keras
numpy-based format)
* supports all Keras layers via thin wrappers
* creates standard Keras models
* extended propagate functions: propagate_to, propagate_from
* designed for use with an online robot simulator (optional)
* built-in plotting and webcam interfaces
* creates updatable network images (SVG) with activations, like this one:
https://raw.githubusercontent.com/Calysto/conx/master/notebooks/network.png
We're just getting started, so if you would like to collaborate, or have
ideas, please let us know!
Discussion group here: https://groups.google.com/forum/#!forum/conx-users
What is cx_Oracle?
cx_Oracle is a Python extension module that enables access to Oracle
Database for Python 3.x and 2.x and conforms to the Python database API 2.0
specifications with a number of enhancements.
Where do I get it?
https://oracle.github.io/python-cx_Oracle
The easiest method to install cx_Oracle is via pip as in
python -m pip install cx_Oracle --upgrade
What's new?
This release addresses issues found since the production release was made.
The full release notes can be read here:
http://cx-oracle.readthedocs.io/en/latest/releasenotes.html#version-6-0-1-a…
Please provide any feedback via GitHub issues (https://github.com/oracle/pyt
hon-cx_Oracle/issues).
hi,
I'm happy to announce the first (public) release of aiounittest.
PyPi: https://pypi.python.org/pypi/aiounittest
Github: https://github.com/kwarunek/aiounittest
This is a helper library to ease of your pain (and boilerplate) when writing tests of the asynchronous code (asyncio). It supports to test:
- synchronous code (same as the unittest.TestCase)
- asynchronous code, syntax with async/await (Python 3.5+) and asyncio.coroutine/yield from (Python 3.4)
Package provides:
- AsyncTestCase,
- futurized (mock helper),
- async_test (sync run decorator)
More info and examples on github or pypi.
--
Best regards,
Krzysztof Warunek
<krzysztof(a)warunek.net>
