Updated repo files

CHANGELOG.md

@@ -0,0 +1,20 @@
+
+# cuGraph 0.6.0 (Date TBD)
+
+## New Features
+
+- PR #41 jaccard grmat graph bindings
+- PR #43 Louvain binings
+- PR #44 SSSP bindings
+
+## Improvements
+
+- PR #50 Reorganize directory structure to match cuDF
+
+## Bug Fixes
+
+- PR #48 ABI Fixes
+
+
+# cuGraph 0.5.0 (28 Jan 2019)
+

CONTRIBUTING.md

@@ -22,12 +22,12 @@ into three categories:
 
 ### Your first issue
 
-1. Read the project's [README.md](https://github.com/rapidsai/cudf/blob/master/README.md)
+1. Read the project's [README.md](https://github.com/rapidsai/cugraph/blob/master/README.md)
     to learn how to setup the development environment
 2. Find an issue to work on. The best way is to look for the [good first issue](https://github.com/rapidsai/cugraph/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22)
     or [help wanted](https://github.com/rapidsai/cugraph/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22) labels
 3. Comment on the issue saying you are going to work on it
-4. Code! Make sure to update unit tests!
+4. Fork the cuGraph repo and Code! Make sure to update unit tests!
 5. When done, [create your pull request](https://github.com/rapidsai/cugraph/compare)
 6. Verify that CI passes all [status checks](https://help.github.com/articles/about-status-checks/). Fix if needed
 7. Wait for other developers to review your code and update code as needed
@@ -39,7 +39,7 @@ and ask for clarifications!
 ### Seasoned developers
 
 Once you have gotten your feet wet and are more comfortable with the code, you
-can look at the prioritized issues of our next release in our [project boards](https://github.com/rapidsai/cudf/projects).
+can look at the prioritized issues of our next release in our [project boards](https://github.com/rapidsai/cugraph/projects).
 
 > **Pro Tip:** Always look at the release board with the highest number for
 issues to work on. This is where RAPIDS developers also focus their efforts.

MANIFEST.in

@@ -0,0 +1,2 @@
+include python/versioneer.py
+include python/cugraph/_version.py

README.md

@@ -2,21 +2,72 @@
 
 cuGraph is a library implementing Graph Analytics functionalities based on GPU Data Frames. For more project details, see [rapids.ai](https://rapids.ai/).
 
+
+
+## Install cuGraph
+
+### Conda
+
+It is easy to install cuGraph using conda. You can get a minimal conda installation with [Miniconda](https://conda.io/miniconda.html) or get the full installation with [Anaconda](https://www.anaconda.com/download).
+
+Install and update cuGraph using the conda command:
+
+```bash
+# NOT YET WORKING #
+
+# CUDA 9.2
+conda install -c nvidia -c rapidsai -c numba -c conda-forge -c defaults cugraph
+
+# CUDA 10.0
+conda install -c nvidia/label/cuda10.0 -c rapidsai/label/cuda10.0 -c numba -c conda-forge -c defaults cugraph
+```
+
+Note: This conda installation only applies to Linux and Python versions 3.6/3.7.
+
+### Pip
+
+It is easy to install cuDF using pip. You must specify the CUDA version to ensure you install the right package.
+
+```bash
+# NOT YET WORKING #
+
+
+# CUDA 9.2
+pip install cugraph-cuda92
+
+# CUDA 10.0.
+pip install cugraph-cuda100
+```
+
+
+
+
+
+
 ## Development Setup
 
 The following instructions are tested on Linux systems.
 
 Compiler requirement:
 
-* `g++` 4.8 or 5.4
-* `cmake` 3.12+
+* `gcc`     version 5.4+
+* `nvcc`    version 9.2
+* `cmake`   version 3.12
+
+
 
 CUDA requirement:
 
-* CUDA 9.0+
+* CUDA 9.2+
+* NVIDIA driver 396.44+
+* Pascal architecture or better
 
 You can obtain CUDA from [https://developer.nvidia.com/cuda-downloads](https://developer.nvidia.com/cuda-downloads).
 
+
+
+## Install cuGraph
+
 ### Conda
 
 You can get a minimal conda installation with [Miniconda](https://conda.io/miniconda.html) or get the full installation with [Anaconda](https://www.anaconda.com/download).
@@ -27,15 +78,15 @@ You can create and activate a development environment using the conda commands:
 
 ```bash
 # create the conda environment (assuming in base `cugraph` directory)
-conda env create --name cugraph_dev --file conda/environments/dev_py35.yml
+conda env create --name cugraph_dev --file conda/environments/cugraph_dev.yml
 # activate the environment
 source activate 
 ```
 
 The environment can be updated as development includes/changes the depedencies. To do so, run:
 
 ```bash
-conda env update --name cugraph_dev --file conda/environments/dev_py35.yml
+conda env update --name cugraph_dev --file conda/environments/cugraph_dev.yml
 source activate 
 ```
 

conda/environments/builddocs.yml

@@ -0,0 +1,19 @@
+name: builddocs
+channels:
+- rapidsai
+- pytorch
+- conda-forge
+- numba
+- defaults
+dependencies:
+- python=3.6*
+- cugraph=0.5*
+- cudatoolkit=9.2
+- cudf=0.5*
+- pyarrow=0.11.1.*
+- cython=0.29*
+- pip:
+  - numpydoc
+  - sphinx
+  - sphinx-rtd-theme
+  - sphinxcontrib-websupport

conda/environments/dev_py35.yml → conda/environments/cugraph_dev.yml

@@ -1,4 +1,4 @@
-name: cugraph_dev_py35
+name: cugraph_dev
 channels:
 - nvidia
 - numba
@@ -7,7 +7,7 @@ channels:
 - defaults
 dependencies:
 - cmake>=3.12
-- python=3.5.*
+- python=>=3.6,<3.8
 - pytest
 - numba>=0.40.0dev
 - pandas>=0.23.4

python/README.md

@@ -0,0 +1,33 @@
+# cuGraph Python Package
+
+To use cuGraph, it must be cloned and built in an environment that already has the dependencies, including [cuGraph](https://github.com/rapidsai/cugraph) and its dependencies.
+
+List of dependencies:
+
+1. zlib
+2. cmake (>= 3.8, version 3.11.4 is recommended and there are issues with version 3.12)
+3. CUDA SDK (>= 9.2)
+4. Cython (>= 0.28)
+5. gcc (>=5.4.0)
+6. nvcc
+7. [cuGraph](https://github.com/rapidsai/cugraph)
+
+### Setup steps
+
+To clone:
+
+```
+git clone --recurse-submodules [email protected]:rapidsai/cugraph.git
+```
+
+To build the python package, in the repository root folder:
+
+```
+cd python
+python setup.py install
+```
+
+### Python Tests
+
+Additional python tests can be found in the pythontests folder, along some useful scripts. Py.test based unit testing is still being worked on.
+

python/cugraph/__init__.py

@@ -0,0 +1,7 @@
+# Copyright (c) 2018, NVIDIA CORPORATION.
+# Versioneer
+import cugraph
+
+from ._version import get_versions
+__version__ = get_versions()['version']
+del get_versions