| Name | asciigraf JSON |
| Version |
1.1.0
JSON |
| download |
| home_page | |
| Summary | A python library for making ascii-art into network graphs. |
| upload_time | 2023-11-02 14:30:04 |
| maintainer | |
| docs_url | None |
| author | Opus One Solutions |
| requires_python | |
| license | copyright 2017 Anton Lodder Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
graph
network
testing
parser
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
asciigraf
=========
.. image:: https://img.shields.io/badge/License-MIT-yellow.svg
:target: https://opensource.org/licenses/MIT
.. image:: https://badge.fury.io/py/asciigraf.svg
:target: https://pypi.python.org/pypi/asciigraf
.. image:: https://img.shields.io/pypi/pyversions/asciigraf.svg
:target: https://pypi.python.org/pypi/asciigraf
.. image:: https://api.codeclimate.com/v1/badges/e7e872f6832da6cf6ab6/maintainability
:target: https://codeclimate.com/github/opusonesolutions/asciigraf/maintainability
:alt: Maintainability
Asciigraf is a python library that turns ascii diagrams of networks into
network objects. It returns a `networkx <https://networkx.github.io/>`__
graph of nodes for each alpha-numeric element in the input text; nodes
are connected in the graph to match the edges represented in the diagram
by ``-``, ``/``, ``\`` and ``|``.
Installation
------------
Asciigraf can be installed from pypi using pip:
.. code::
~/$ pip install asciigraf
Usage
-----
Asciigraf expects a string containg a 2-d ascii diagram. Nodes can be an
alphanumeric string composed of words, sentences and punctuation (for a look at
what is all tested to work, see the `node recognition tests`_). Edges can be
composed of ``-``, ``/``, ``\`` and ``|``.
.. _node recognition tests: https://github.com/opusonesolutions/asciigraf/blob/master/tests/test_node_match.py
.. code:: python
import asciigraf
network = asciigraf.graph_from_ascii("""
NodeA-----
|
|---NodeB
""")
print(network)
>>> <networkx.classes.graph.Graph at 0x7f24c3a8b470>
print(network.edges())
>>> [('NodeA', 'NodeB')]
print(network.nodes())
>>> ['NodeA', 'NodeB']
Networkx provides tools to attach data to graphs, nodes and edges, and asciigraf
leverages these in a number of ways; in the example below you can see that
asciigraf uses this to attach a ``x, y`` position tuple to each node
indicating the line/col position of each node ( *0,0* is at the top-left).
It also attaches a ``length`` attribute
to each edge which matches the number of characters in that edge, as well
as a list of positions for each character an edge. In addition, the input data
is attached as a graph attribute ``ascii_string`` for reference.
.. code:: python
print(network.nodes(data=True))
>>> [('NodeA', {'position': (10, 1)}), ('NodeB', {'position': (23, 3)})]
print(network.edges(data=True))
>>> [('NodeA', 'NodeB', OrderedDict([('length', 10), 'points', [...]))]
print(network.edge['NodeA']['NodeB']['points'])
>>> [(15, 1), (16, 1), (17, 1), (18, 1),
(19, 1), (19, 2), (19, 3), (20, 3), (21, 3), (22, 3)]
print(network.graph["ascii_string"])
>>>
NodeA-----
|
|---NodeB
Asciigraf also lets you annotate the edges of graphs using in-line labels ---
denoted by parentheses. The contents of the label will be attached to the edge
on which it is drawn with the attribute name ``label``.
.. code:: python
network = asciigraf.graph_from_ascii("""
A---(nuts)----B----(string)---C
|
|
|
D---(pebbles)----E
""")
print(network.get_edge_data("A", "B")["label"])
>>> nuts
print(network.get_edge_data("B", "C")["label"])
>>> string
print(network.get_edge_data("D", "E")["label"])
>>> pebbles
print(hasattr(network.get_edge_data("B", "D"), "label"))
>>> False
Have fun!
.. code:: python
import asciigraf
network = asciigraf.graph_from_ascii("""
s---p----1---nx
/ | |
/ | 0---f
6l-a c--
/ | \--k
/ ua | 9e
q \ | /
\-r7z jud
\ |
m y
\ |
v-ow
""")
Raw data
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"description": "asciigraf\n=========\n\n.. image:: https://img.shields.io/badge/License-MIT-yellow.svg\n :target: https://opensource.org/licenses/MIT\n\n.. image:: https://badge.fury.io/py/asciigraf.svg\n :target: https://pypi.python.org/pypi/asciigraf\n\n.. image:: https://img.shields.io/pypi/pyversions/asciigraf.svg\n :target: https://pypi.python.org/pypi/asciigraf\n\n.. image:: https://api.codeclimate.com/v1/badges/e7e872f6832da6cf6ab6/maintainability\n :target: https://codeclimate.com/github/opusonesolutions/asciigraf/maintainability\n :alt: Maintainability\n\nAsciigraf is a python library that turns ascii diagrams of networks into\nnetwork objects. It returns a `networkx <https://networkx.github.io/>`__\ngraph of nodes for each alpha-numeric element in the input text; nodes\nare connected in the graph to match the edges represented in the diagram\nby ``-``, ``/``, ``\\`` and ``|``.\n\nInstallation\n------------\n\nAsciigraf can be installed from pypi using pip:\n\n.. code::\n\n ~/$ pip install asciigraf\n\nUsage\n-----\n\nAsciigraf expects a string containg a 2-d ascii diagram. Nodes can be an\nalphanumeric string composed of words, sentences and punctuation (for a look at\nwhat is all tested to work, see the `node recognition tests`_). Edges can be\ncomposed of ``-``, ``/``, ``\\`` and ``|``.\n\n.. _node recognition tests: https://github.com/opusonesolutions/asciigraf/blob/master/tests/test_node_match.py\n\n.. code:: python\n\n\n import asciigraf\n\n network = asciigraf.graph_from_ascii(\"\"\"\n NodeA-----\n |\n |---NodeB\n \"\"\")\n\n print(network)\n >>> <networkx.classes.graph.Graph at 0x7f24c3a8b470>\n\n print(network.edges())\n >>> [('NodeA', 'NodeB')]\n\n print(network.nodes())\n >>> ['NodeA', 'NodeB']\n\n\nNetworkx provides tools to attach data to graphs, nodes and edges, and asciigraf\nleverages these in a number of ways; in the example below you can see that\nasciigraf uses this to attach a ``x, y`` position tuple to each node\nindicating the line/col position of each node ( *0,0* is at the top-left).\nIt also attaches a ``length`` attribute\nto each edge which matches the number of characters in that edge, as well\nas a list of positions for each character an edge. In addition, the input data\nis attached as a graph attribute ``ascii_string`` for reference.\n\n.. code:: python\n\n print(network.nodes(data=True))\n >>> [('NodeA', {'position': (10, 1)}), ('NodeB', {'position': (23, 3)})]\n\n print(network.edges(data=True))\n >>> [('NodeA', 'NodeB', OrderedDict([('length', 10), 'points', [...]))]\n \n print(network.edge['NodeA']['NodeB']['points'])\n >>> [(15, 1), (16, 1), (17, 1), (18, 1),\n (19, 1), (19, 2), (19, 3), (20, 3), (21, 3), (22, 3)]\n\n print(network.graph[\"ascii_string\"])\n >>>\n NodeA-----\n |\n |---NodeB\n\n\nAsciigraf also lets you annotate the edges of graphs using in-line labels ---\ndenoted by parentheses. The contents of the label will be attached to the edge\non which it is drawn with the attribute name ``label``.\n\n.. code:: python\n\n network = asciigraf.graph_from_ascii(\"\"\"\n\n A---(nuts)----B----(string)---C\n |\n |\n |\n D---(pebbles)----E\n\n \"\"\")\n\n print(network.get_edge_data(\"A\", \"B\")[\"label\"])\n >>> nuts\n\n print(network.get_edge_data(\"B\", \"C\")[\"label\"])\n >>> string\n\n print(network.get_edge_data(\"D\", \"E\")[\"label\"])\n >>> pebbles\n\n print(hasattr(network.get_edge_data(\"B\", \"D\"), \"label\"))\n >>> False\n\n\nHave fun!\n\n.. code:: python\n\n import asciigraf\n\n\n network = asciigraf.graph_from_ascii(\"\"\"\n s---p----1---nx\n / | |\n / | 0---f\n 6l-a c--\n / | \\--k\n / ua | 9e\n q \\ | /\n \\-r7z jud\n \\ |\n m y\n \\ |\n v-ow\n \"\"\")\n",
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