Install SWIG for your platform (see below). Swig should be able to run from the command-line.
Checkout the snap-python repository as well as the SNAP C++ repository.
git clone git@github.com:snap-stanford/snap-python.git
git clone git@github.com:snap-stanford/snap.git
Then, run make
from the top-level of snap-python
. This will make the SNAP code into a Python module, using SWIG. Finally, it will run some Python tests in the test
directory.
cd snap-python
make
From a Python interpreter, you should be able to import snap
module:
$ python
>>> import sys
>>> sys.path.append("swig")
>>> import snap
There are some examples in the examples
directory. For example, to run benchmarks:
$ cd examples
$ python benchmark.py -h
usage: benchmark.py [-h] [-v] [-r RANGE] [-e EDGES_DEG] [-d] [-t GRAPH_TYPES]
[-n NUM_ITERATIONS] [-o OUTPUT_FILE] [-g] [-w]
optional arguments:
-h, --help show this help message and exit
-v, --verbose increase output verbosity
-r RANGE, --range RANGE
range (4-6) (10^4 to 10^6 nodes)
-e EDGES_DEG, --edges_deg EDGES_DEG
range of degrees (e.g "2-3" => (10^1 to 10^3 edges per
node)
-d, --deterministic deterministic benchmark
-t GRAPH_TYPES, --graph_types GRAPH_TYPES
Graph types, comma separated. Available: rand_ungraph,
rand_ngraph, rmat, pref, sw
-n NUM_ITERATIONS, --num_iterations NUM_ITERATIONS
number of iterations
-o OUTPUT_FILE, --output_file OUTPUT_FILE
file to output results
-g, --generate generate new graphs
-w, --write_graph save graph
$ python benchmark.py -v -g -r 4-6 # needs about 4.3GB RAM and 4 min to run
Follow the instructions from SWIG's website: download, configure and make, SWIG files. Or, use your built-in installer (a CentOS example):
sudo yum install swig
swig-1.3.12 and later support OS-X/Darwin.
If you have homebrew
, simply hit brew install swig
in terminal and ignore the rest of the instructions. Otherwise, download the Unix sources, configure, and build from the command terminal. This has been tested on 10.8.2. The following is adopted from ColourBlomb.
Download the Unix source from http://swig.org/download.html
Moving to the terminal, extract the files from the tarball and move to the root directory of the SWIG install:
cd /Developer/SWIG
tar -xf swig-2.0.4.tar.gz
cd swig-2.0.4
Run ./configure
. This will produce an error if you don't have the PCRE (Perl Compatible Regular Expressions) library package installed.
This dependency is needed for configure to complete. Either:
Tools/pcre-build.sh
script to build PCRE just for SWIG to statically
link against. Run Tools/pcre-build.sh -help
for instructions.
(quite easy and does not require privileges to install PCRE on your system)Configure using the -without-pcre
option to disable regular expressions support in SWIG
(not recommended).
See config.log
for more details.
make
sudo make install
PCRE should now have successfully installed so move to the swig install directory and try ./configure
again:
cd ../swig-2.0.4
./configure
This time no errors are thrown so try and install:
make
sudo make install
Once this has completed test that SWIG has installed correctly, type swig
into the terminal and hopefully you'll get the response:
Must specify an input file. Use -help
for available options.
Example SWIG programs using the SNAP Ringo for multi-attribute edges are in the examples
directory. The benchmark program benchmark.py
performs a series of functions on the graph data, including node/edge iteration, degree checks, clustering coefficients, largest weakly and strongest components, etc. For R-MAT graphs with 1 million nodes and 10 million edges, this takes on average:
To run a benchmark test you can run the following command:
python benchmark.py --verbose -n 5 --range 4-7 --type rmat --generate