Release of v1.1.4

.gitignore

@@ -1,4 +1,3 @@
-*.pyc
 build/
 dist/
 *egg-info/
@@ -7,8 +6,34 @@ venv
 .output/
 sample_output/
 
+# VSCode
+.vscode
+
 # Doxygen output
 docs/html/
 
 # Testing output
 .tox/
+testing
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+.pytest_cache/
+
+
+*.py[cod]
+__pycache__/
+htmlcov/
+wheelhouse/
+
+pylint_*.txt
+Pipfile.lock
+
+#pycharm
+.idea/

.travis.yml

@@ -6,6 +6,12 @@ python:
     - "3.5"
     - "3.6"
 
+matrix:
+  include:
+    - python: 3.7
+      dist: xenial
+      sudo: true
+
 install:
     - pip install tox-travis
     - pip install flake8

Dockerfile

@@ -0,0 +1,6 @@
+FROM ubuntu
+LABEL maintainer="Francesco Di Natale dinatale3@llnl.gov"
+
+RUN apt-get update && apt-get install -y python python-pip git
+ADD . /maestrowf
+RUN pip install -U /maestrowf

Pipfile

@@ -0,0 +1,26 @@
+[[source]]
+url = "https://pypi.python.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+"enum34" = "*"
+filelock = "*"
+six = "*"
+tabulate = "*"
+Fabric = "*"
+PyYAML = ">= 4.2b1"
+maestrowf = {path = "."}
+
+[dev-packages]
+"flake8" = "*"
+pydocstyle = "*"
+pylint = "*"
+tox = "*"
+coverage = "*"
+sphinx_rtd_theme = "*"
+Sphinx = "*"
+pytest = "*"
+
+[requires]
+python_version = "3.6"

README.md

@@ -1,4 +1,5 @@
 # Maestro Workflow Conductor (MaestroWF)
+[![Build Status](https://travis-ci.org/LLNL/maestrowf.svg?branch=develop)](https://travis-ci.org/LLNL/maestrowf)
 [![PyPI](https://img.shields.io/pypi/v/maestrowf.svg)](https://pypi.python.org/pypi?name=maestrowf&version=1.0.0&:action=display)
 [![Issues](https://img.shields.io/github/issues/LLNL/maestrowf.svg)](https://github.com/LLNL/maestrowf/issues)
 [![Forks](https://img.shields.io/github/forks/LLNL/maestrowf.svg)](https://github.com/LLNL/maestrowf/network)
@@ -68,39 +69,7 @@ If you plan to develop on MaestroWF, install the repository directly using:
 
 ### Quickstart Example
 
-MaestroWF comes packed with a basic example using LULESH, a proxy application provided
-by LLNL. Information and source code for LULESH can be found [here](https://codesign.llnl.gov/lulesh.php).
-
-The example performs the following workflow locally:
-- Download LULESH from the webpage linked above and decompress it.
-- Substitute all necessary variables with their serial compilers and make LULESH.
-- Execute a small parameter sweep of varying size and iterations (a simple sensitivity study)
-
-Two copies of the workflow are in the ```samples/lulesh``` directory for unix and macosx.
-This is due to differences with ```sed```. In order to execute the sample study simply
-execute from the root directory of the repository:
-
-Unix:
-
-    $ maestro run ./samples/lulesh/lulesh_sample1_unix.yaml
-
-MacOSX:
-
-    $ maestro run ./samples/lulesh/lulesh_sample1_macosx.yaml
-
-When prompted, reply in the affirmative:
-
-    $ Would you like to launch the study?[yn] y
-
-Maestro will create a timestamped directory in ```sample_output/lulesh```.
-
-To monitor the study run:
-
-    $ maestro status sample_output/lulesh/<study_dir>
-
-To cancel the study:
-
-    $ maestro cancel sample_output/lulesh/<study_dir>
+MaestroWF comes packed with a basic example using LULESH, a proxy application provided by LLNL. You can find the Quick Start guide [here](https://maestrowf.readthedocs.io/en/latest/quick_start.html#).
 
 ----------------
 

docs/source/getting_started.rst

@@ -1,10 +1,27 @@
 Getting Started
 ================
 
+Maestro Docker Container
+************************
+
+In order to set up the Docker container execute the following from the root of the Maestro repository::
+
+    $ docker --build -t maestrowf .
+
+To launch the interactive shell of the Ubuntu image simply run::
+
+    $ docker run -it maestrowf
+
+Once inside the Docker container, the following should bring up help::
+
+    $ maestro -h
+
+For more information on using Dockerfiles, checkout Docker's `documentation <https://docs.docker.com/engine/reference/builder/>`.
+
 Installing MaestroWF
 *********************
 
-MaestroWF can be installed via pip::
+MaestroWF can be installed via pip outside of Docker with the following::
 
     $ pip install maestrowf
 
@@ -13,7 +30,7 @@ MaestroWF can be installed via pip::
 Once installed run::
 
     $ maestro -h
-    
+
     usage: maestro [-h] [-l LOGPATH] [-d DEBUG_LVL] [-c] {cancel,run,status} ...
 
     The Maestro Workflow Conductor for specifiying, launching, and managing general workflows.