stacked-dag for python
======================
|Build Status|
Ascii DAG for visualization of dataflow
stacked-dag can show Ascii-DAG(Directed acyclic graph) from a Dot file
of graphviz. Dataflow's direction is from top to bottom. 'o' means a
node. A label of the node is shown to the left side. Other characters
are edges of DAG.
A sample of DAG is below.
::
o o l0,l4
|/
o l1
|
o l2
|
o l3
Usage with dot
==============
Write a Dot file of graphviz.
::
$ cat > sample.dot
digraph graphname {
0 [label="l0"];
1 [label="l1"];
2 [label="l2"];
3 [label="l3"];
4 [label="l4"];
0->1;
1->2;
2->3;
4->1;
}
Show ascii DAG by following command.
::
$ python stackeddag.py sample.dot
o o l0,l4
|/
o l1
|
o l2
|
o l3
Usage with tensorflow
=====================
::
import tensorflow as tf
import stackeddag.tf as sd
def mydataflow():
a = tf.constant(1,name="a")
b = tf.constant(2,name="b")
c = tf.add(a,b,name="c")
return tf.get_default_graph()
print(sd.fromGraph(mydataflow()),end="")
The output is below.
::
o o a,b
|/
o c
Another sample
==============
::
$ python stackeddag.py sample/test.dot
o
|
o
|\
o |
| |\
o o |
|\ \ \
| | |\ \
| | | | |\
o o o o o |
|/ /_/ / /
| | / /
o o o o
|/_/_/
o
.. |Build Status| image:: https://travis-ci.org/junjihashimoto/py-stacked-dag.png?branch=master
:target: https://travis-ci.org/junjihashimoto/py-stacked-dag
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"description": "stacked-dag for python\n======================\n\n|Build Status|\n\nAscii DAG for visualization of dataflow\n\nstacked-dag can show Ascii-DAG(Directed acyclic graph) from a Dot file\nof graphviz. Dataflow's direction is from top to bottom. 'o' means a\nnode. A label of the node is shown to the left side. Other characters\nare edges of DAG.\n\nA sample of DAG is below.\n\n::\n\n o o l0,l4\n |/\n o l1\n |\n o l2\n |\n o l3\n\nUsage with dot\n==============\n\nWrite a Dot file of graphviz.\n\n::\n\n $ cat > sample.dot\n digraph graphname {\n 0 [label=\"l0\"];\n 1 [label=\"l1\"];\n 2 [label=\"l2\"];\n 3 [label=\"l3\"];\n 4 [label=\"l4\"];\n 0->1;\n 1->2;\n 2->3;\n 4->1;\n }\n\nShow ascii DAG by following command.\n\n::\n\n $ python stackeddag.py sample.dot\n o o l0,l4\n |/\n o l1\n |\n o l2\n |\n o l3\n\nUsage with tensorflow\n=====================\n\n::\n\n import tensorflow as tf\n import stackeddag.tf as sd\n\n def mydataflow():\n a = tf.constant(1,name=\"a\")\n b = tf.constant(2,name=\"b\")\n c = tf.add(a,b,name=\"c\")\n return tf.get_default_graph()\n\n print(sd.fromGraph(mydataflow()),end=\"\")\n\nThe output is below.\n\n::\n\n o o a,b\n |/\n o c\n\nAnother sample\n==============\n\n::\n\n $ python stackeddag.py sample/test.dot\n o\n |\n o\n |\\\n o |\n | |\\\n o o |\n |\\ \\ \\\n | | |\\ \\\n | | | | |\\\n o o o o o |\n |/ /_/ / /\n | | / /\n o o o o\n |/_/_/\n o\n\n.. |Build Status| image:: https://travis-ci.org/junjihashimoto/py-stacked-dag.png?branch=master\n :target: https://travis-ci.org/junjihashimoto/py-stacked-dag\n\n\n",
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