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snutree 0.3.0

Visualize big–little brother/sister relationships in Greek-letter organizations

1   Introduction

Some Greek-letter organizations assign big brothers or big sisters (“bigs”) to new members (“littles”). This program visualizes such relationships as a family tree, using Graphviz.

2   Usage

2.1   Basic Usage

The simplest usage of snutree is:

snutree -o output.pdf input1.csv input2.csv ...

In this example, the CSV should have columns called name, big_name, and semester where semesters are strings starting with “Fall” or “Spring” and ending with a year (e.g., “Fall 2014” or “Spring 1956”). With this input, snutree will append all the input tables together, convert them into a tree, and output the tree using Graphviz. Each member will be put on a row representing the semester they joined.

2.2   Changing Schemas

The (name, big_name, semester) headers consist of the “basic” schema. There are a few other schemas available. They are:

Schema Headers
basic name, big_name, semester
keyed id, name, big_id, semester
chapter child, parent, founded
sigmanu badge, first_name, preferred_name, last_name, big_badge, status, semester, affiliations

Changing schemas can be done with the --schema option. For example, this will print the DOT source code of a family tree of chapters to the terminal:

snutree --schema chapter chapters.csv

A custom Python module may be used as a schema:

snutree --schema /home/example/custom.py input.csv

Custom schema modules should validate the tables themselves and turn them into an internal format snutree can read.

2.3   SQL Queries

Input files can also be SQL queries. This will run the query in query.sql on the database described in config.yaml and save the resulting tree to output.pdf:

snutree --config config.yaml -o output.pdf query.sql

For a SQL query, a YAML configuration file with appropriate authentication options must be provided. Here is an example of the contents of such a file:

readers:
  sql:
    host: '127.0.0.1'
    port: 3306
    user: 'root'
    passwd: 'secret'
    db: 'database_name'
    # Credentials for tunneling queries through SSH
    ssh:
      host: 'example.com'
      port: 22
      user: 'example'
      private_key: '/home/example/.ssh/id_rsa'

Note that the query must rename the column headers to match the schema used.

2.4   Command Line Summary

usage: snutree [-h] [-o <path>] [-f <filetype>] [-t <filetype>] [-m <schema>]
               [-w <writer>] [-c <path>] [-S <int>] [-l <path>] [-q] [-v] [-d]
               [-V]
               [<input> [<input> ...]]

Visualizes big-little brother/sister relationships in Greek-letter
organizations. Input file data is read from stdin and/or any provided
positional <input> arguments. Each input <filetype> has a corresponding
reader, which converts the file into a table of the given <schema> and adds it
to the rest of the input data. The <schema> module then turns the the
resulting table into a tree data structure. The tree is processed and finally
written to the output <path> using the given <writer> and output <filetype>.
Additional options can be provided in configuration files.

positional arguments:
  <input>               an input file path or '-' for stdin; default is stdin

optional arguments:
  -h, --help            show this help message and exit
  -o <path>, --output <path>
                        the output file; default is stdout
  -f <filetype>, --from <filetype>
                        expected filetype of stdin, which must be one of
                        {csv,dot,sql}; default is csv
  -t <filetype>, --to <filetype>
                        filetype of the output file, which must be supported
                        by the writer; default is the output file's extension
                        (if known) or 'dot'
  -m <schema>, --schema <schema>
                        member table schema, which must be in
                        {basic,chapter,keyed,sigmanu,*.py}; default is 'basic'
  -w <writer>, --writer <writer>
                        writer module, which must be in
                        {dot,stats,table,*.py}; default is a guess based on
                        the output file format
  -c <path>, --config <path>
                        configuration file <path(s)>; files listed earlier
                        override later ones
  -S <int>, --seed <int>
                        random number generator seed, for moving tree nodes
                        around in a repeatable way
  -l <path>, --log <path>
                        write logger output to the file at <path>
  -q, --quiet           write only errors to stderr; suppress warnings
  -v, --verbose         print more information to stderr
  -d, --debug           print debug-level information to stderr
  -V, --version         show program's version number and exit

2.5   GUI

There is also a simple GUI script called snutree-gui. It is a simple wrapper over the command-line version and implements most of the command-line features.

2.6   Note on Text Encoding

All of snutree’s built-in readers and writers use UTF-8, and all of snutree’s configuration files should be encoded in UTF-8. Use iconv or similar tools to convert to and from UTF-8 as needed.

3   Installation

3.1   With PIP

These instructions are based on Ubuntu and Debian-based installations, but they can be made to apply to any Unix-like system (including macOS) with what should be minor modifications. (These instructions are also applicable to Windows, though after less minor modifications.)

First, install Python (>=3.5), Python’s pip package manager, and Graphviz:

# apt install python3 python3-pip graphviz

At this point, python3, pip3, and dot should be in your PATH:

$ python3 --version
Python 3.X.X
$ pip3 --version
pip X.X.X from /path/to/python3/packages (python 3.5)
$ dot -V
dot - graphviz version X.XX.X (20XXXXXX.XXXX)

Now install snutree with:

$ pip3 install --user snutree

This will install snutree and its required Python dependencies to your home directory. Make sure that ~/.local/bin is in your PATH. You might run pip without the --user flag to install it system-wide, but this will require root.

3.2   Windows

Since installation on Windows is less straightforward, Windows executables have been compiled and are available here. After downloading the executable, you must install Graphviz and add C:\Program Files (x86)\GraphvizX.XX\bin (or equivalent) to your Windows PATH. You can now run the command-line or GUI executables.

3.3   Optional Dependencies

Use pip to install these packages for optional features:

  • gooey: Use the GUI version
  • mysqlclient: Allow reading from MySQL databases
  • sshtunnel: Allow tunneling SQL queries through ssh
  • pydotplus: Allow reading data from DOT files (experimental)

4   Configuration

All configuration is done in YAML (or JSON) files. In the terminal, these files can be included with --config flags. Configuration files listed later override those that came earlier and command line options override all configuration files.

Below are all of the available options along with descriptions in the comments and default values where applicable.

4.1   General

readers: # reader module configuration
  stdin: # standard input reader configuration
    filetype: csv # type of files coming from stdin
  <reader1>:
  <reader2>: ...
schema: # members schema module configuration
  name: basic # member schema module name
seed: 71 # random number generator seed
writer: # writer module configuration
  file: None # output file name
  filetype: # output filetype
  name: None # writer module name

4.2   Readers

SQL Reader

db: # SQL database name
host: 127.0.0.1 # SQL server hostname
passwd: # SQL user password
port: 3306 # SQL server port
ssh: # credentials to encrypt SQL connection with SSH
  host: # SSH server hostname
  port: 22 # SSH server port
  private_key: # SSH private keyfile path
  user: # SSH username
user: root # SQL username

4.3   Schemas

Sigma Nu Schema

chapter: # the chapter whose family tree will be generated
name: sigmanu

4.4   Writers

DOT Writer

See Graphviz’s documentation for available DOT attributes.

colors: True # add color to member nodes
custom_edges: True # enable custom edges
custom_nodes: True # enable custom nodes
defaults: # default Graphviz attributes
  edge: # defaults for Graphviz edges
    all: # all edges
      <name1>: <value1>
      <name2>: ...
    rank: # edges between rank nodes
      <name1>: <value1>
      <name2>: ...
    unknown: # edges coming from unknown parents
      <name1>: <value1>
      <name2>: ...
  graph: # defaults for Graphviz graphs
    all:
      <name1>: <value1>
      <name2>: ...
  node: # defaults for Graphviz nodes
    all: # all nodes
      <name1>: <value1>
      <name2>: ...
    member: # member nodes
      <name1>: <value1>
      <name2>: ...
    rank: # rank nodes
      <name1>: <value1>
      <name2>: ...
    unknown: # nodes of unknown parents
      <name1>: <value1>
      <name2>: ...
edges: # a list of custom Graphviz edges
  - # edge1
    attributes: # Graphviz edge attributes
      <name1>: <value1>
      <name2>: ...
    nodes: # keys of nodes connected by this edge
      - # key1
      - ...
  - ...
family_colors: # map of member keys to Graphviz colors
  <key1>: <color1>
  <key2>: ...
file: # output file name
filetype: # output filetype
name: dot # writer name
no_singletons: True # delete member nodes with neither parent nor child nodes
nodes: # custom Graphviz nodes
  <key1>:
    attributes: # Graphviz node attributes
      <name1>: <value1>
      <name2>: ...
    rank: # the rank (i.e., year, semester, etc.) the node is in
  <key2>: ...
ranks: True # enable ranks
unknowns: True # add parent nodes to members without any
warn_rank: None # if no_singletons=True, singletons with rank>=warn_rank trigger warnings when dropped

5   Versioning

This project loosely uses Semantic Versioning.

6   License

This project is licensed under GPLv3.

 
File Type Py Version Uploaded on Size
snutree-0.3.0-py3-none-any.whl (md5) Python Wheel py3 2017-11-15 49KB
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