Compute PageRank on large graphs with off-the-shelf hardware.
Project description
danker - Compute PageRank on large graphs with off-the-shelf hardware.
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Standalone with any input graph:
$ pip install danker $ python -m danker -h usage: python -m danker [-h] [-r RIGHT_SORTED] [-p OUTPUT_PRECISION] [-i] left_sorted damping iterations start_value danker - Compute PageRank on large graphs with off-the-shelf hardware. positional arguments: left_sorted A two-column, tab-separated file sorted by the left column. damping PageRank damping factor(between 0 and 1). iterations Number of PageRank iterations (>0). start_value PageRank starting value(>0). optional arguments: -h, --help show this help message and exit -r RIGHT_SORTED, --right_sorted RIGHT_SORTED The same file as left_sorted but sorted by the right column. -p OUTPUT_PRECISION, --output_precision OUTPUT_PRECISION Number of decimal places afterthe comma. -i, --int_only All nodes are integers(flag) $ wget https://raw.githubusercontent.com/athalhammer/danker/master/test/graphs/test.links $ python -m danker test.links 0.85 30 1 1.2.3.4.5.6.7.8.9.10.11.12.13.14.15.16.17.18.19.20.21.22.23.24.25.26.27.28.29.30. Computation of PageRank on 'test.links' with danker took 0.00 seconds. C 3.1898535044738043 B 3.5572213415705725 A 0.30410528185694391 D 0.36260066319290651 F 0.36260066319290651 E 0.75035528185694389 G 0.15000000000000002 H 0.15000000000000002 I 0.15000000000000002 K 0.15000000000000002 L 0.15000000000000002
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As Python library for computing PageRank on large graphs:
$ pip install danker $ python >>> import danker
More information on this option can be found at https://danker.rtfd.org.
More information on the project: Compute PageRank on the Wikipedia graph
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