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# git repo at ssh://git@git.linaro.org/people/mike.holmes/DependanceMap.git
import csv
import pandas as pd
pd.set_option('display.max_rows',None)
pd.set_option('display.max_columns',None)
import io
import requests
from collections import defaultdict
import argparse
parser = argparse.ArgumentParser(description='Pull from JIre Engineers spreadsheet data to genrate graphs')
parser.add_argument("--teams", default=False, action='store_true', help="generate teams dependance")
parser.add_argument("--dependance", default=False, action='store_true',help="generate project dependance")
parser.add_argument("--relates", default=False, action='store_true',help="generate project relates")
parser.add_argument("--company", default=False, action='store_true',help="generate company relationship")
parser.add_argument("--projects", default=False, action='store_true', help="generate projects")
parser.add_argument("--governing_group", default=False, action='store_true', help="generate governing groups")
parser.add_argument("--department_group", default=False, action='store_true', help="generate department groups")
parser.add_argument("--all_projects", default=False, action='store_true', help="list all projects")
parser.add_argument("--verbose", default=False, action='store_true', help="verbose")
parser.add_argument("--filter_list", default=[], nargs='+', help="filter out a node name, such as team, project or member")
parser.add_argument("--include_list", default=[], nargs='+', help="filter out a node name, such as team, project or member")
parser.add_argument("--center_on", help="center on a specific node which can be a company, team or project")
args = parser.parse_args()
if (args.verbose == 1):
print("// ",args)
print("")
print ("digraph G {")
print ("rankdir=RL")
print ("node [style=rounded]")
#twopi paramiters
print ("overlap=false")
if (args.center_on):
print ("root=\"", args.center_on,"\"", sep='')
def filter_node(data, filter_list):
if (args.verbose == 1):
print (data)
print("")
print ("filtering for ",filter_list)
if filter_list:
if 'Assignee Company' in data.columns:
data_filter = data['Assignee Company'].isin(filter_list)
data = data[~data_filter]
if 'Assignee Team' in data.columns:
data_filter = data['Assignee Team'].isin(filter_list)
data = data[~data_filter]
if 'Assignee Department' in data.columns:
data_filter = data['Assignee Department'].isin(filter_list)
data = data[~data_filter]
if 'Project' in data.columns:
data_filter = data['Project'].isin(filter_list)
data = data[~data_filter]
if 'project' in data.columns:
data_filter = data['project'].isin(filter_list)
data = data[~data_filter]
if 'linked' in data.columns:
data_filter = data['linked'].isin(filter_list)
data = data[~data_filter]
if (args.verbose == 1):
print (data)
print("")
return(data)
if (args.governing_group == 1):
#from URL with csv file
url = 'https://docs.google.com/spreadsheets/d/e/2PACX-1vSGKF1LA9ONNq1S3ZTb-7hk-kJ7XlXdVQKDFmFJbTpLa0u_cVqTTjHkA8TdxougbN_DvmdiVbsZJ9UY/pub?gid=1685920531&single=true&output=csv'
data = pd.read_csv(url)
mylist = defaultdict(list)
print ("//cluster governance")
data = filter_node(data, args.filter_list)
for row in data.index:
#same Governing Entity
if data['Governing Entity'][row]:
mylist[data['Governing Entity'][row]].append(data['project name'][row])
for gov in mylist:
print ( "")
print (" subgraph ", "cluster_",gov.replace(" ", "_")," {", sep='')
for x in range(len(mylist[gov])):
print (" \"", mylist[gov][x], "\";", sep='')
print (" label = \"",gov.replace(" ", "_"),"\"", sep='')
print (" }", sep='')
print("")
if (args.department_group == 1):
url ="https://docs.google.com/spreadsheets/d/e/2PACX-1vSGKF1LA9ONNq1S3ZTb-7hk-kJ7XlXdVQKDFmFJbTpLa0u_cVqTTjHkA8TdxougbN_DvmdiVbsZJ9UY/pub?gid=1268085837&single=true&output=csv"
data = pd.read_csv(url)
mylist = defaultdict(list)
print ("//cluster departments")
filter_node(data, args.filter_list)
for row in data.index:
#same Governing Entity
if data['Assignee Department'][row]:
mylist[data['Assignee Department'][row]].append(data['Assignee Team'][row])
print("")
for gov in mylist:
print ( "")
print (" subgraph ", "cluster_",gov.replace(" ", "_")," {", sep='')
for x in range(len(mylist[gov])):
print (" \"", mylist[gov][x], "\";", sep='')
print (" label = \"",gov.replace(" ", "_"),"\"", sep='')
print (" }", sep='')
url="https://docs.google.com/spreadsheets/d/e/2PACX-1vSGKF1LA9ONNq1S3ZTb-7hk-kJ7XlXdVQKDFmFJbTpLa0u_cVqTTjHkA8TdxougbN_DvmdiVbsZJ9UY/pub?gid=954864288&single=true&output=csv"
data = pd.read_csv(url)
data = filter_node(data, args.filter_list)
print("")
if (args.teams == 1):
print ("//generate Teams with a with a unique shape and colour")
for row in data.index:
print (" \"", data['Assignee Team'][row],"\"", " [", "fillcolor=yellow, style=\"rounded,filled\", shape=diamond","]", sep='')
if (args.all_projects== 1):
print("")
print ("//generate projects with a unique shape and colour")
for row in data.index:
print (" \"", data['Project'][row],"\"", " [", "shape=box","]", sep='')
print("")
if (args.teams == 1):
print("")
print ("//generate team members in a project")
url="https://docs.google.com/spreadsheets/d/e/2PACX-1vSGKF1LA9ONNq1S3ZTb-7hk-kJ7XlXdVQKDFmFJbTpLa0u_cVqTTjHkA8TdxougbN_DvmdiVbsZJ9UY/pub?gid=954864288&single=true&output=csv"
data = pd.read_csv(url)
data = filter_node(data, args.filter_list)
for row in data.index:
#generate the graph for assignee team
print (" \"", data['Assignee Team'][row],"\"", " -> ", "\"", data['Project'][row],"\"", " [", "taillabel=\"E", int(data['COUNTUNIQUE of Assignee'][row]),"\"", " weight=",
data['COUNTUNIQUE of Assignee'][row]," style=dashed"," color=red","]", sep='')
print("")
url = "https://docs.google.com/spreadsheets/d/e/2PACX-1vSGKF1LA9ONNq1S3ZTb-7hk-kJ7XlXdVQKDFmFJbTpLa0u_cVqTTjHkA8TdxougbN_DvmdiVbsZJ9UY/pub?gid=1744118841&single=true&output=csv"
data = pd.read_csv(url,names=["project", "linked", "depends_on", "relates_to"],skiprows=2)
data = filter_node(data, args.filter_list)
data.fillna(0, inplace=True)
#generate the graph for relates to and depends on
if (args.relates == 1):
print("")
print ("//generate relates to links")
for row in data.index:
if data['relates_to'][row]:
print (" \"", data['project'][row],"\"", " -> ", "\"", data['linked'][row],"\"", " [", "label=\"R",
int(data['relates_to'][row]),"\"", " weight=", data['relates_to'][row]," color=blue", " style=dotted ","]", sep='')
if (args.dependance == 1):
print("")
print ("//generate depends on links")
for row in data.index:
if data['depends_on'][row]:
print (" \"",data['project'][row],"\"", " -> ", "\"",data['linked'][row],"\""," [", " taillabel=\"D",
int(data['depends_on'][row]),"\"", " weight=",data['depends_on'][row], "]", sep='' )
print("")
url = "https://docs.google.com/spreadsheets/d/e/2PACX-1vSGKF1LA9ONNq1S3ZTb-7hk-kJ7XlXdVQKDFmFJbTpLa0u_cVqTTjHkA8TdxougbN_DvmdiVbsZJ9UY/pub?gid=1310895524&single=true&output=csv"
data = pd.read_csv(url)
data = filter_node(data, args.filter_list)
if (args.company == 1):
print("")
print ("// generate the graph for assignee teams to projects")
for row in data.index:
print (" \"", data['Assignee Company'][row],"\"", " -> ", "\"", data['Project'][row],"\"", " [", "taillabel=\"",
int(data['COUNTUNIQUE of Assignee'][row]),"\"", " weight=",
data['COUNTUNIQUE of Assignee'][row]," style=dashed"," color=azure3","]", sep='')
if (args.company == 1):
print("")
print ("// generate company shape and colour")
#remove duplicates
data.drop_duplicates(subset="Assignee Company", keep = 'first', inplace = True)
for row in data.index:
#generate the graph for assignee team
print (" \"", data['Assignee Company'][row],"\"", " [", "fillcolor=azure, style=\"rounded,filled\", shape=diamond","]", sep='')
print ("}")
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