Mergemaster/cloudml (#134)

* Add gcs_copy_file() that is missing but is referenced in a couple of places. (#110)

* Add gcs_copy_file() that is missing but is referenced in a couple of places.

* Add DataFlow to pydatalab dependency list.

* Fix travis test errors by reimplementing gcs copy.

* Remove unnecessary shutil import.

* Flake8 configuration. Set max line length to 100. Ignore E111, E114 (#102)

* Add datalab user agent to CloudML trainer and predictor requests. (#112)

* Update oauth2client to 2.2.0 to satisfy cloudml in Cloud Datalab (#111)

* Update README.md (#114)

Added docs link.

* Generate reST documentation for magic commands (#113)

Auto generate docs for any added magics by searching through the source files for lines with register_line_cell_magic, capturing the names for those magics, and calling them inside an ipython kernel with the -h argument, then storing that output into a generated datalab.magics.rst file.

* Fix an issue that %%chart failed with UDF query. (#116)

* Fix an issue that %%chart failed with UDF query.

The problem is that the query is submitted to BQ without replacing variable values from user namespace.

* Fix chart tests by adding ip.user_ns mock.

* Fix charting test.

* Add missing import "mock".

* Fix chart tests.

* Fix "%%bigquery schema" issue --  the command generates nothing in output. (#119)

* Add some missing dependencies, remove some unused ones (#122)

* Remove scikit-learn and scipy as dependencies
* add more required packages
* Add psutil as dependency
* Update packages versions

* Cleanup (#123)

* Remove unnecessary semicolons

* remove unused imports

* remove unncessary defined variable

* Fix query_metadata tests (#128)

Fix query_metadata tests

* Make the library pip-installable (#125)

This PR adds tensorflow and cloudml in setup.py to make the lib pip-installable. I had to install them explicitly using pip from inside the setup.py script, even though it's not a clean way to do it, it gets around the two issues we have at the moment with these two packags:
- Pypi has Tensorflow version 0.12, while we need 0.11 for the current version of pydatalab. According to the Cloud ML docs, that version exists as a pip package for three supported platforms.
- Cloud ML SDK exists as a pip package, but also not on Pypi, and while we could add it as a dependency link, there exists another package on Pypi called cloudml, and pip ends up installing that instead (see #124). I cannot find a way to force pip to install the package from the link I included.

* Set command description so it is displayed in --help. argparser's format_help() prints description but not help. (#131)

setup.py

@@ -113,3 +113,24 @@
  ]
  }
 )
+
+# for python2 only, install tensorflow and cloudml
+if sys.version_info[0] == 2:
+ tensorflow_path = None
+ if platform.system() == 'Darwin':
+ tensorflow_path = 'https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.11.0-py2-none-any.whl'
+ elif platform.system() == 'Linux':
+ if platform.linux_distribution()[0] == 'Ubuntu':
+ tensorflow_path = 'https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0-cp27-none-linux_x86_64.whl'
+ elif platform.linux_distribution()[0] == 'Debian':
+ tensorflow_path = 'https://storage.googleapis.com/tensorflow/linux/cpu/debian/jessie/tensorflow-0.11.0-cp27-none-linux_x86_64.whl'
+
+ # install tensorflow
+ if not tensorflow_path:
+ print("""Warning: could not find tensorflow build for your OS.
+ Please go to https://www.tensorflow.org/get_started/os_setup to see install options""")
+ else:
+ pip.main(['install', tensorflow_path])
+
+ # install cloud ml sdk
+ pip.main(['install', 'https://storage.googleapis.com/cloud-ml/sdk/cloudml.latest.tar.gz'])