diff --git a/.travis/install-dependencies.sh b/.travis/install-dependencies.sh
index 7fe258e53..73994e8ac 100755
--- a/.travis/install-dependencies.sh
+++ b/.travis/install-dependencies.sh
@@ -24,7 +24,7 @@ if [[ "$PYTHON" == "2.7" ]] && [[ "$platform" == "linux" ]]; then
   wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -O miniconda.sh -nv
   bash miniconda.sh -b -p $HOME/miniconda
   export PATH="$HOME/miniconda/bin:$PATH"
-  pip install -q numpy cython cmake funcsigs click colorama psutil redis tensorflow gym flatbuffers opencv-python pyyaml pandas
+  pip install -q numpy cython cmake funcsigs click colorama psutil redis tensorflow gym flatbuffers opencv-python pyyaml pandas requests
 elif [[ "$PYTHON" == "3.5" ]] && [[ "$platform" == "linux" ]]; then
   sudo apt-get update
   sudo apt-get install -y cmake pkg-config python-dev python-numpy build-essential autoconf curl libtool unzip
@@ -32,7 +32,7 @@ elif [[ "$PYTHON" == "3.5" ]] && [[ "$platform" == "linux" ]]; then
   wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh -nv
   bash miniconda.sh -b -p $HOME/miniconda
   export PATH="$HOME/miniconda/bin:$PATH"
-  pip install -q numpy cython cmake funcsigs click colorama psutil redis tensorflow gym flatbuffers opencv-python pyyaml pandas
+  pip install -q numpy cython cmake funcsigs click colorama psutil redis tensorflow gym flatbuffers opencv-python pyyaml pandas requests
 elif [[ "$PYTHON" == "2.7" ]] && [[ "$platform" == "macosx" ]]; then
   # check that brew is installed
   which -s brew
@@ -48,7 +48,7 @@ elif [[ "$PYTHON" == "2.7" ]] && [[ "$platform" == "macosx" ]]; then
   wget https://repo.continuum.io/miniconda/Miniconda2-latest-MacOSX-x86_64.sh -O miniconda.sh -nv
   bash miniconda.sh -b -p $HOME/miniconda
   export PATH="$HOME/miniconda/bin:$PATH"
-  pip install -q numpy cython cmake funcsigs click colorama psutil redis tensorflow gym flatbuffers opencv-python pyyaml pandas
+  pip install -q numpy cython cmake funcsigs click colorama psutil redis tensorflow gym flatbuffers opencv-python pyyaml pandas requests
 elif [[ "$PYTHON" == "3.5" ]] && [[ "$platform" == "macosx" ]]; then
   # check that brew is installed
   which -s brew
@@ -64,7 +64,7 @@ elif [[ "$PYTHON" == "3.5" ]] && [[ "$platform" == "macosx" ]]; then
   wget https://repo.continuum.io/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -O miniconda.sh -nv
   bash miniconda.sh -b -p $HOME/miniconda
   export PATH="$HOME/miniconda/bin:$PATH"
-  pip install -q numpy cython cmake funcsigs click colorama psutil redis tensorflow gym flatbuffers opencv-python pyyaml pandas
+  pip install -q numpy cython cmake funcsigs click colorama psutil redis tensorflow gym flatbuffers opencv-python pyyaml pandas requests
 elif [[ "$LINT" == "1" ]]; then
   sudo apt-get update
   sudo apt-get install -y cmake build-essential autoconf curl libtool unzip
diff --git a/doc/source/ray-tune-parcoords.png b/doc/source/ray-tune-parcoords.png
new file mode 100644
index 000000000..707287dea
Binary files /dev/null and b/doc/source/ray-tune-parcoords.png differ
diff --git a/doc/source/tune.rst b/doc/source/tune.rst
index 6380d88d6..ce85f1f67 100644
--- a/doc/source/tune.rst
+++ b/doc/source/tune.rst
@@ -67,11 +67,16 @@ Visualizing Results
 
 Ray Tune logs trial results to a unique directory per experiment, e.g. ``~/ray_results/my_experiment`` in the above example. The log records are compatible with a number of visualization tools:
 
-To visualize learning in tensorboard, run:
+To visualize learning in tensorboard, install TensorFlow:
+
+.. code-block:: bash
+
+    $ pip install tensorflow
+
+Then, after you run a experiment, you can visualize your experiment with TensorBoard by specifying the output directory of your results:
 
 .. code-block:: bash
 
-    $ pip install tensorboard
     $ tensorboard --logdir=~/ray_results/my_experiment
 
 .. image:: ray-tune-tensorboard.png
@@ -92,6 +97,8 @@ Finally, to view the results with a `parallel coordinates visualization <https:/
     $ cd $RAY_HOME/python/ray/tune
     $ jupyter-notebook ParallelCoordinatesVisualization.ipynb
 
+.. image:: ray-tune-parcoords.png
+
 Trial Variant Generation
 ------------------------
 
@@ -182,7 +189,13 @@ If your trainable function / class creates further Ray actors or tasks that also
 Client API
 ----------
 
-You can modify an ongoing experiment by adding or deleting trials using the Tune Client API. To do this, start your experiment with ``with_server=True``:
+You can modify an ongoing experiment by adding or deleting trials using the Tune Client API. To do this, verify that you have the ``requests`` library installed:
+
+.. code-block:: bash
+
+    $ pip install requests
+
+To use the Client API, you can start your experiment with ``with_server=True``:
 
 .. code-block:: python
 
diff --git a/python/ray/tune/logger.py b/python/ray/tune/logger.py
index d08f67470..fab8934f1 100644
--- a/python/ray/tune/logger.py
+++ b/python/ray/tune/logger.py
@@ -7,7 +7,6 @@ import json
 import numpy as np
 import os
 import sys
-import tensorflow as tf
 
 from ray.tune.result import TrainingResult
 
@@ -16,6 +15,12 @@ if sys.version_info[0] == 2:
 elif sys.version_info[0] == 3:
     import io as StringIO
 
+try:
+    import tensorflow as tf
+except ImportError:
+    tf = None
+    print("Couldn't import TensorFlow - this disables TensorBoard logging.")
+
 
 class Logger(object):
     """Logging interface for ray.tune; specialized implementations follow.
@@ -54,6 +59,9 @@ class UnifiedLogger(Logger):
     def _init(self):
         self._loggers = []
         for cls in [_JsonLogger, _TFLogger, _VisKitLogger]:
+            if cls is _TFLogger and tf is None:
+                print("TF not installed - cannot log with {}...".format(cls))
+                continue
             self._loggers.append(cls(self.config, self.logdir, self.uri))
         print("Unified logger created with logdir '{}'".format(self.logdir))
 
diff --git a/python/ray/tune/web_server.py b/python/ray/tune/web_server.py
index c4d3a4a7f..d1e161e87 100644
--- a/python/ray/tune/web_server.py
+++ b/python/ray/tune/web_server.py
@@ -2,14 +2,26 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import requests
 import json
+import sys
 import threading
-from http.server import HTTPServer, BaseHTTPRequestHandler
 
 from ray.tune.error import TuneError, TuneManagerError
 from ray.tune.variant_generator import generate_trials
 
+if sys.version_info[0] == 2:
+    from SimpleHTTPServer import SimpleHTTPRequestHandler
+    from SocketServer import TCPServer as HTTPServer
+elif sys.version_info[0] == 3:
+    from http.server import SimpleHTTPRequestHandler, HTTPServer
+
+try:
+    import requests  # `requests` is not part of stdlib.
+except ImportError:
+    requests = None
+    print("Couldn't import `requests` library. Be sure to install it on"
+          " the client side.")
+
 
 class TuneClient(object):
     """Client to interact with ongoing Tune experiment.
@@ -58,7 +70,7 @@ class TuneClient(object):
 
 
 def RunnerHandler(runner):
-    class Handler(BaseHTTPRequestHandler):
+    class Handler(SimpleHTTPRequestHandler):
 
         def do_GET(self):
             content_len = int(self.headers.get('Content-Length'), 0)