Peter Schafhalter ae17ebd032 [DataFrame] Implement to_csv (#2014)
* Add map, reduce, merge_dtypes

bug fixes

Unify dtypes on DataFrame creation

Formatting and comments

Cache dtypes

Fix bug in _merge_dtypes

Fix bug

Changed caching logic

Fix dtypes issue in read_csv

Invalidate dtypes cache when inserting column

Simplify unifying dtypes and improve caching

Fix typo

Better caching of dtypes

Fix merge conflicts

Implemented some to_csv functions

Support read_csv from buffers

Expose date_range, NaT, Timedelta from pandas

Add testing utils

Redirect imports to Pandas

Fix imports

Fix read_csv when index_col is specified

Update imports from Pandas

Fix bugs

Use util API

Fix nasty bug

Add missing import

Don't distribute reading of compressed files

Add test utilities for Pandas tests

Add test for to_csv

Add warnings

Fix rebase artifacts

* Fix rebase artifacts

* Fix bugs in read_csv indexing

* Fix bugs in read_csv

* Fix bug for IndexMetadata with _length 1

Remove testing imports

* Rebase artifacts and formatting

* Start to_csv without CSV formatter

* Fix bug in _map_partitions

* Initial implementation for improved to_csv

* Fix bug with insert

* Bugfixes

* Remove CSV Formatter

* Formatting

* Fix python2 bug

* Fix additional python2 issue
2018-05-17 11:35:17 -10:00
2018-04-23 23:18:09 -07:00
2018-04-02 00:23:56 -07:00
2018-05-16 15:04:31 -07:00
2016-11-22 17:04:24 -08:00
2018-04-30 06:31:23 -07:00
2016-07-08 12:39:11 -07:00
2016-11-22 17:04:24 -08:00

Ray
===

.. image:: https://travis-ci.org/ray-project/ray.svg?branch=master
    :target: https://travis-ci.org/ray-project/ray

.. image:: https://readthedocs.org/projects/ray/badge/?version=latest
    :target: http://ray.readthedocs.io/en/latest/?badge=latest

|

Ray is a flexible, high-performance distributed execution framework.


Ray is easy to install: ``pip install ray``

Example Use
-----------

+------------------------------------------------+----------------------------------------------------+
| **Basic Python**                               | **Distributed with Ray**                           |
+------------------------------------------------+----------------------------------------------------+
|.. code-block:: python                          |.. code-block:: python                              |
|                                                |                                                    |
|  # Execute f serially.                         |  # Execute f in parallel.                          |
|                                                |                                                    |
|                                                |  @ray.remote                                       |
|  def f():                                      |  def f():                                          |
|      time.sleep(1)                             |      time.sleep(1)                                 |
|      return 1                                  |      return 1                                      |
|                                                |                                                    |
|                                                |                                                    |
|                                                |  ray.init()                                        |
|  results = [f() for i in range(4)]             |  results = ray.get([f.remote() for i in range(4)]) |
+------------------------------------------------+----------------------------------------------------+


Ray comes with libraries that accelerate deep learning and reinforcement learning development:

- `Ray Tune`_: Hyperparameter Optimization Framework
- `Ray RLlib`_: Scalable Reinforcement Learning

.. _`Ray Tune`: http://ray.readthedocs.io/en/latest/tune.html
.. _`Ray RLlib`: http://ray.readthedocs.io/en/latest/rllib.html

Installation
------------

Ray can be installed on Linux and Mac with ``pip install ray``.

To build Ray from source or to install the nightly versions, see the `installation documentation`_.

.. _`installation documentation`: http://ray.readthedocs.io/en/latest/installation.html

More Information
----------------

- `Documentation`_
- `Tutorial`_
- `Blog`_
- `Ray paper`_
- `Ray HotOS paper`_

.. _`Documentation`: http://ray.readthedocs.io/en/latest/index.html
.. _`Tutorial`: https://github.com/ray-project/tutorial
.. _`Blog`: https://ray-project.github.io/
.. _`Ray paper`: https://arxiv.org/abs/1712.05889
.. _`Ray HotOS paper`: https://arxiv.org/abs/1703.03924

Getting Involved
----------------

- Ask questions on our mailing list `ray-dev@googlegroups.com`_.
- Please report bugs by submitting a `GitHub issue`_.
- Submit contributions using `pull requests`_.

.. _`ray-dev@googlegroups.com`: https://groups.google.com/forum/#!forum/ray-dev
.. _`GitHub issue`: https://github.com/ray-project/ray/issues
.. _`pull requests`: https://github.com/ray-project/ray/pulls
S
Description
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
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