import pytest
import nlp
from nlp import loadPageHTML, stripRawHTML, findOutlinks, onlyWikipediaURLS
from nlp import expand_pages, relevant_pages, normalize, ConvergenceDetector, getInlinks
from nlp import getOutlinks, Page
from nlp import Rules, Lexicon
# Clumsy imports because we want to access certain nlp.py globals explicitly, because
# they are accessed by function's within nlp.py


def test_rules():
    assert Rules(A="B C | D E") == {'A': [['B', 'C'], ['D', 'E']]}


def test_lexicon():
    assert Lexicon(Art="the | a | an") == {'Art': ['the', 'a', 'an']}


# ______________________________________________________________________________
# Data Setup

testHTML = """Keyword String 1: A man is a male human.
            Keyword String 2: Like most other male mammals, a man inherits an
            X from his mom and a Y from his dad.
            Links:
            href="https://google.com.au"
            < href="/wiki/TestThing" > href="/wiki/TestBoy"
            href="/wiki/TestLiving" href="/wiki/TestMan" >"""
testHTML2 = "Nothing"

pA = Page("A", 1, 6, ["B", "C", "E"], ["D"])
pB = Page("B", 2, 5, ["E"], ["A", "C", "D"])
pC = Page("C", 3, 4, ["B", "E"], ["A", "D"])
pD = Page("D", 4, 3, ["A", "B", "C", "E"], [])
pE = Page("E", 5, 2, [], ["A", "B", "C", "D", "F"])
pF = Page("F", 6, 1, ["E"], [])
pageDict = {pA.address: pA, pB.address: pB, pC.address: pC,
            pD.address: pD, pE.address: pE, pF.address: pF}
nlp.pagesIndex = pageDict
nlp.pagesContent ={pA.address: testHTML, pB.address: testHTML2,
                   pC.address: testHTML, pD.address: testHTML2,
                   pE.address: testHTML, pF.address: testHTML2}

# This test takes a long time (> 60 secs)
# def test_loadPageHTML():
#     # first format all the relative URLs with the base URL
#     addresses = [examplePagesSet[0] + x for x in examplePagesSet[1:]]
#     loadedPages = loadPageHTML(addresses)
#     relURLs = ['Ancient_Greek','Ethics','Plato','Theology']
#     fullURLs = ["https://en.wikipedia.org/wiki/"+x for x in relURLs]
#     assert all(x in loadedPages for x in fullURLs)
#     assert all(loadedPages.get(key,"") != "" for key in addresses)


def test_stripRawHTML():
    addr = "https://en.wikipedia.org/wiki/Ethics"
    aPage = loadPageHTML([addr])
    someHTML = aPage[addr]
    strippedHTML = stripRawHTML(someHTML)
    assert "<head>" not in strippedHTML and "</head>" not in strippedHTML


def test_determineInlinks():
    # TODO
    assert True


def test_findOutlinks_wiki():
    testPage = pageDict[pA.address]
    outlinks = findOutlinks(testPage, handleURLs=onlyWikipediaURLS)
    assert "https://en.wikipedia.org/wiki/TestThing" in outlinks
    assert "https://en.wikipedia.org/wiki/TestThing" in outlinks
    assert "https://google.com.au" not in outlinks
# ______________________________________________________________________________
# HITS Helper Functions


def test_expand_pages():
    pages = {k: pageDict[k] for k in ('F')}
    pagesTwo = {k: pageDict[k] for k in ('A', 'E')}
    expanded_pages = expand_pages(pages)
    assert all(x in expanded_pages for x in ['F', 'E'])
    assert all(x not in expanded_pages for x in ['A', 'B', 'C', 'D'])
    expanded_pages = expand_pages(pagesTwo)
    print(expanded_pages)
    assert all(x in expanded_pages for x in ['A', 'B', 'C', 'D', 'E', 'F'])


def test_relevant_pages():
    pages = relevant_pages("male")
    assert all((x in pages.keys()) for x in ['A', 'C', 'E'])
    assert all((x not in pages) for x in ['B', 'D', 'F'])


def test_normalize():
    normalize(pageDict)
    print(page.hub for addr, page in nlp.pagesIndex.items())
    expected_hub = [1/91**0.5, 2/91**0.5, 3/91**0.5, 4/91**0.5, 5/91**0.5, 6/91**0.5]  # Works only for sample data above
    expected_auth = list(reversed(expected_hub))
    assert len(expected_hub) == len(expected_auth) == len(nlp.pagesIndex)
    assert expected_hub == [page.hub for addr, page in sorted(nlp.pagesIndex.items())]
    assert expected_auth == [page.authority for addr, page in sorted(nlp.pagesIndex.items())]


def test_detectConvergence():
    # run detectConvergence once to initialise history
    convergence = ConvergenceDetector()
    convergence()
    assert convergence()  # values haven't changed so should return True
    # make tiny increase/decrease to all values
    for _, page in nlp.pagesIndex.items():
        page.hub += 0.0003
        page.authority += 0.0004
    # retest function with values. Should still return True
    assert convergence()
    for _, page in nlp.pagesIndex.items():
        page.hub += 3000000
        page.authority += 3000000
    # retest function with values. Should now return false
    assert not convergence()


def test_getInlinks():
    inlnks = getInlinks(pageDict['A'])
    assert sorted([page.address for page in inlnks]) == pageDict['A'].inlinks


def test_getOutlinks():
    outlnks = getOutlinks(pageDict['A'])
    assert sorted([page.address for page in outlnks]) == pageDict['A'].outlinks


def test_HITS():
    # TODO
    assert True  # leave for now


if __name__ == '__main__':
    pytest.main()
