Re: [Pytables-users] ANN: PyTables 2.3 released

[Han Genuit]

Congratulations! :-D


Whoohoo!  Congrats everyone.

On Wed, Sep 21, 2011 at 2:52 PM, Antonio Valentino 
mailto:antonio.valent...@tiscali.it>> wrote:
===
 Announcing PyTables 2.3
===

We are happy to announce PyTables 2.3.
This release comes after about 10 months of development and after that
Francesc Altet, the creator of PyTables, ceased activities with the project.

Thank you Francesc.

Also the project has been moved to GitHub:
http://github.com/PyTables/PyTables.


What's new
==

The main new features in 2.3 series are:

* PyTables now includes the codebase of PyTables Pro (now release under open
 source license) gaining a lot of performance improvements and some new
 features like:

 - the new and powerful indexing engine: OPSI
 - a fine-tuned LRU cache for both metadata (nodes) and regular data

* The entire documentation set has been converted to ReStructuredTest and
 Sphinx

As always, a large amount of bugs have been addressed and squashed too.

In case you want to know more in detail what has changed in this
version, have a look at:
http://pytables.github.com/release_notes.html

You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:
http://sourceforge.net/projects/pytables/files/pytables/2.3

For an on-line version of the manual, visit:
http://pytables.github.com/usersguide/index.html


What it is?
===

PyTables is a library for managing hierarchical datasets and
designed to efficiently cope with extremely large amounts of data with
support for full 64-bit file addressing.  PyTables runs on top of
the HDF5 library and NumPy package for achieving maximum throughput and
convenient use.  PyTables includes OPSI, a new indexing technology,
allowing to perform data lookups in tables exceeding 10 gigarows
(10**10 rows) in less than 1 tenth of a second.


Resources
=

About PyTables:

http://www.pytables.org

About the HDF5 library:

http://hdfgroup.org/HDF5/

About NumPy:

http://numpy.scipy.org/


Acknowledgments
===

Thanks to many users who provided feature improvements, patches, bug
reports, support and suggestions.  See the ``THANKS`` file in the
distribution package for a (incomplete) list of contributors.  Most
specially, a lot of kudos go to the HDF5 and NumPy (and numarray!)
makers.  Without them, PyTables simply would not exist.


Share your experience
=

Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.




 **Enjoy data!**

--
The PyTables Team

--
All the data continuously generated in your IT infrastructure contains a
definitive record of customers, application performance, security
threats, fraudulent activity and more. Splunk takes this data and makes
sense of it. Business sense. IT sense. Common sense.
http://p.sf.net/sfu/splunk-d2dcopy1
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--
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definitive record of customers, application performance, security
threats, fraudulent activity and more. Splunk takes this data and makes
sense of it. Business sense. IT sense. Common sense.
http://p.sf.net/sfu/splunk-d2dcopy1
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Re: [Pytables-users] ANN: PyTables 2.3 released

[Anthony Scopatz]

Whoohoo!  Congrats everyone.

On Wed, Sep 21, 2011 at 2:52 PM, Antonio Valentino <
antonio.valent...@tiscali.it> wrote:

> ===
>  Announcing PyTables 2.3
> ===
>
> We are happy to announce PyTables 2.3.
> This release comes after about 10 months of development and after that
> Francesc Altet, the creator of PyTables, ceased activities with the
> project.
>
> Thank you Francesc.
>
> Also the project has been moved to GitHub:
> http://github.com/PyTables/PyTables.
>
>
> What's new
> ==
>
> The main new features in 2.3 series are:
>
> * PyTables now includes the codebase of PyTables Pro (now release under
> open
>  source license) gaining a lot of performance improvements and some new
>  features like:
>
>  - the new and powerful indexing engine: OPSI
>  - a fine-tuned LRU cache for both metadata (nodes) and regular data
>
> * The entire documentation set has been converted to ReStructuredTest and
>  Sphinx
>
> As always, a large amount of bugs have been addressed and squashed too.
>
> In case you want to know more in detail what has changed in this
> version, have a look at:
> http://pytables.github.com/release_notes.html
>
> You can download a source package with generated PDF and HTML docs, as
> well as binaries for Windows, from:
> http://sourceforge.net/projects/pytables/files/pytables/2.3
>
> For an on-line version of the manual, visit:
> http://pytables.github.com/usersguide/index.html
>
>
> What it is?
> ===
>
> PyTables is a library for managing hierarchical datasets and
> designed to efficiently cope with extremely large amounts of data with
> support for full 64-bit file addressing.  PyTables runs on top of
> the HDF5 library and NumPy package for achieving maximum throughput and
> convenient use.  PyTables includes OPSI, a new indexing technology,
> allowing to perform data lookups in tables exceeding 10 gigarows
> (10**10 rows) in less than 1 tenth of a second.
>
>
> Resources
> =
>
> About PyTables:
>
> http://www.pytables.org
>
> About the HDF5 library:
>
> http://hdfgroup.org/HDF5/
>
> About NumPy:
>
> http://numpy.scipy.org/
>
>
> Acknowledgments
> ===
>
> Thanks to many users who provided feature improvements, patches, bug
> reports, support and suggestions.  See the ``THANKS`` file in the
> distribution package for a (incomplete) list of contributors.  Most
> specially, a lot of kudos go to the HDF5 and NumPy (and numarray!)
> makers.  Without them, PyTables simply would not exist.
>
>
> Share your experience
> =
>
> Let us know of any bugs, suggestions, gripes, kudos, etc. you may
> have.
>
>
> 
>
>  **Enjoy data!**
>
> --
> The PyTables Team
>
>
> --
> All the data continuously generated in your IT infrastructure contains a
> definitive record of customers, application performance, security
> threats, fraudulent activity and more. Splunk takes this data and makes
> sense of it. Business sense. IT sense. Common sense.
> http://p.sf.net/sfu/splunk-d2dcopy1
> ___
> Pytables-users mailing list
> Pytables-users@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/pytables-users
>
--
All the data continuously generated in your IT infrastructure contains a
definitive record of customers, application performance, security
threats, fraudulent activity and more. Splunk takes this data and makes
sense of it. Business sense. IT sense. Common sense.
http://p.sf.net/sfu/splunk-d2dcopy1___
Pytables-users mailing list
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https://lists.sourceforge.net/lists/listinfo/pytables-users

[Pytables-users] ANN: PyTables 2.3 released

[Antonio Valentino]

===
 Announcing PyTables 2.3
===

We are happy to announce PyTables 2.3.
This release comes after about 10 months of development and after that
Francesc Altet, the creator of PyTables, ceased activities with the project.

Thank you Francesc.

Also the project has been moved to GitHub:
http://github.com/PyTables/PyTables.


What's new
==

The main new features in 2.3 series are:

* PyTables now includes the codebase of PyTables Pro (now release under open
  source license) gaining a lot of performance improvements and some new
  features like:

  - the new and powerful indexing engine: OPSI
  - a fine-tuned LRU cache for both metadata (nodes) and regular data

* The entire documentation set has been converted to ReStructuredTest and
  Sphinx

As always, a large amount of bugs have been addressed and squashed too.

In case you want to know more in detail what has changed in this
version, have a look at:
http://pytables.github.com/release_notes.html

You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:
http://sourceforge.net/projects/pytables/files/pytables/2.3

For an on-line version of the manual, visit:
http://pytables.github.com/usersguide/index.html


What it is?
===

PyTables is a library for managing hierarchical datasets and
designed to efficiently cope with extremely large amounts of data with
support for full 64-bit file addressing.  PyTables runs on top of
the HDF5 library and NumPy package for achieving maximum throughput and
convenient use.  PyTables includes OPSI, a new indexing technology,
allowing to perform data lookups in tables exceeding 10 gigarows
(10**10 rows) in less than 1 tenth of a second.


Resources
=

About PyTables:

http://www.pytables.org

About the HDF5 library:

http://hdfgroup.org/HDF5/

About NumPy:

http://numpy.scipy.org/


Acknowledgments
===

Thanks to many users who provided feature improvements, patches, bug
reports, support and suggestions.  See the ``THANKS`` file in the
distribution package for a (incomplete) list of contributors.  Most
specially, a lot of kudos go to the HDF5 and NumPy (and numarray!)
makers.  Without them, PyTables simply would not exist.


Share your experience
=

Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.




  **Enjoy data!**

--
The PyTables Team

--
All the data continuously generated in your IT infrastructure contains a
definitive record of customers, application performance, security
threats, fraudulent activity and more. Splunk takes this data and makes
sense of it. Business sense. IT sense. Common sense.
http://p.sf.net/sfu/splunk-d2dcopy1
___
Pytables-users mailing list
Pytables-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/pytables-users

[Pytables-users] ANN: PyTables 2.3 released

[Antonio Valentino]

===
 Announcing PyTables 2.3
===

We are happy to announce PyTables 2.3.
This release comes after about 10 months of development and after that
Francesc Altet, the creator of PyTables, ceased activities with the project.

Thank you Francesc.

Also the project has been moved to GitHub:
http://github.com/PyTables/PyTables.


What's new
==

The main new features in 2.3 series are:

* PyTables now includes the codebase of PyTables Pro (now release under open
  source license) gaining a lot of performance improvements and some new
  features like:

  - the new and powerful indexing engine: OPSI
  - a fine-tuned LRU cache for both metadata (nodes) and regular data

* The entire documentation set has been converted to ReStructuredTest and
  Sphinx

As always, a large amount of bugs have been addressed and squashed too.

In case you want to know more in detail what has changed in this
version, have a look at:
http://pytables.github.com/release_notes.html

You can download a source package with generated PDF and HTML docs, as
well as binaries for Windows, from:
http://sourceforge.net/projects/pytables/files/pytables/2.3

For an on-line version of the manual, visit:
http://pytables.github.com/usersguide/index.html


What it is?
===

PyTables is a library for managing hierarchical datasets and
designed to efficiently cope with extremely large amounts of data with
support for full 64-bit file addressing.  PyTables runs on top of
the HDF5 library and NumPy package for achieving maximum throughput and
convenient use.  PyTables includes OPSI, a new indexing technology,
allowing to perform data lookups in tables exceeding 10 gigarows
(10**10 rows) in less than 1 tenth of a second.


Resources
=

About PyTables:

http://www.pytables.org

About the HDF5 library:

http://hdfgroup.org/HDF5/

About NumPy:

http://numpy.scipy.org/


Acknowledgments
===

Thanks to many users who provided feature improvements, patches, bug
reports, support and suggestions.  See the ``THANKS`` file in the
distribution package for a (incomplete) list of contributors.  Most
specially, a lot of kudos go to the HDF5 and NumPy (and numarray!)
makers.  Without them, PyTables simply would not exist.


Share your experience
=

Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.




  **Enjoy data!**

--
The PyTables Team

--
All the data continuously generated in your IT infrastructure contains a
definitive record of customers, application performance, security
threats, fraudulent activity and more. Splunk takes this data and makes
sense of it. Business sense. IT sense. Common sense.
http://p.sf.net/sfu/splunk-d2dcopy1
___
Pytables-users mailing list
Pytables-users@lists.sourceforge.net
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