"""
NetworKit -- an interactive tool suite for high-performance network analysis.

NetworKit is an open-source software package for high-performance
analysis of large complex networks. Complex networks are equally
attractive and challenging targets for data mining, and novel
algorithmic solutions, including parallelization, are required to handle
data sets containing billions of connections. Our goal for NetworKit is
to package results of our algorithm engineering efforts and put them
into the hands of domain experts. NetworKit is a hybrid combining the
performance of kernels written in C++ with a convenient Python
frontend. The package targets shared-memory platforms with OpenMP support.
The current feature set includes various analytics kernels such as connected components, diameter, clustering
coefficients, community detection, k-core decomposition, degree assortativity
and multiple centrality indices, as well as a
collection of graph generators. Scaling to massive networks is enabled by techniques such as parallel and sampling-based approximation algorithms.
NetworKit is geared towards large networks and satisfies three important
criteria: High performance, interactive workflows
and integration into the Python ecosystem of tools for data analysis and
scientific computation.


Usage examples can be found on http://nbviewer.ipython.org/urls/networkit.iti.kit.edu/data/uploads/docs/NetworKit_UserGuide.ipynb
"""

__author__ = "Christian Staudt"
__copyright__ = "Copyright (c) 2014 Christan Staudt"
__credits__ = ["Lukas Barth", "Miriam Beddig", "Elisabetta Bergamini", "Stefan Bertsch", "Pratistha Bhattarai", "Andreas Bilke", "Simon Bischof", \
	"Guido Brückner", "Mark Erb", "Patrick Flick", "Michael Hamann", "Lukas Hartmann", "Daniel Hoske", "Gerd Lindner", "Moritz v. Looz", "Yassine Marrakchi", "Henning Meyerhenke", \
	"Marcel Radermacher", "Klara Reichard", "Marvin Ritter", "Aleksejs Sazonovs", "Florian Weber", "Michael Wegner", "Jörg Weisbarth"]
__license__ = "MIT"
__version__ = "4.0.1"


# standard library modules
import csv
import os
import logging
import sys

# local imports
from . import stopwatch
from . import graph
from . import graphio
from . import community
from . import centrality
from . import generators
from . import structures
from . import engineering
from . import distance
from . import components
from . import dynamic
from . import gephi
from . import partitioning
from . import coloring
from . import workflows
from . import flow
from . import plot
from . import sparsification
from . import scd
from . import clique
from . import globals
from . import linkprediction
from . import correlation
from .profiling import profiling

try:
	from . import viztasks
except ImportError as importError:
	print("""WARNING: some dependencies are not satisfied which are needed to use the
		'viztasks' submodule""")
	print(importError)




#--------- Top Level Classes and Functions ----------------#
#

# Some functions and classes should be directly available from the top module

# TODO: introduce settings module

# extension imports
from _NetworKit import getLogLevel, setLogLevel, setPrintLocation, enableNestedParallelism, setNumberOfThreads, getCurrentNumberOfThreads, getMaxNumberOfThreads, none, setSeed

# local imports into the top namespace
from .graph import Graph
from .structures import Partition, Cover
from .graphio import readGraph, writeGraph, Format


#-------- Setup ---------- #

def setup():
	""" This function is run once on module import to configure initial settings """
	setLogLevel("ERROR")    # set default loglevel for C++ code
	setPrintLocation(True)
	enableNestedParallelism()	# enable nested parallelism
	logging.basicConfig(level=logging.INFO)	# set default loglevel for Python code



setup() # here the setup function is called once on import


# in general, no implementations here