Python compat.u函数代码示例

def test_phrase_andmaybe():
    qp = default.QueryParser("f", None)

    q = qp.parse(u('Dahmen ANDMAYBE "Besov Spaces"'))
    assert isinstance(q, query.AndMaybe)
    assert q[0] == query.Term("f", u("Dahmen"))
    assert q[1] == query.Phrase("f", [u("Besov"), u("Spaces")])

def test_deleteall():
    schema = fields.Schema(text=fields.TEXT)
    with TempIndex(schema, "deleteall") as ix:
        w = ix.writer()
        domain = u("alfa bravo charlie delta echo").split()
        for i, ls in enumerate(permutations(domain)):
            w.add_document(text=u(" ").join(ls))
            if not i % 10:
                w.commit()
                w = ix.writer()
        w.commit()

        # This is just a test, don't use this method to delete all docs IRL!
        doccount = ix.doc_count_all()
        w = ix.writer()
        for docnum in xrange(doccount):
            w.delete_document(docnum)
        w.commit()

        with ix.searcher() as s:
            r = s.search(query.Or([query.Term("text", u("alfa")),
                                   query.Term("text", u("bravo"))]))
            assert len(r) == 0

        ix.optimize()
        assert ix.doc_count_all() == 0

        with ix.reader() as r:
            assert list(r) == []

 def __unicode__(self):
     r = u("(")
     r += (self.JOINT).join([text_type(s) for s in self.subqueries])
     r += u(")")
     if self.minmatch:
         r += u(">%s") % self.minmatch
     return r

def test_boolean():
    schema = fields.Schema(id=fields.ID(stored=True),
                           done=fields.BOOLEAN(stored=True))
    ix = RamStorage().create_index(schema)

    w = ix.writer()
    w.add_document(id=u("a"), done=True)
    w.add_document(id=u("b"), done=False)
    w.add_document(id=u("c"), done=True)
    w.add_document(id=u("d"), done=False)
    w.add_document(id=u("e"), done=True)
    w.commit()

    with ix.searcher() as s:
        qp = qparser.QueryParser("id", schema)

        r = s.search(qp.parse("done:true"))
        assert sorted([d["id"] for d in r]) == ["a", "c", "e"]
        assert all(d["done"] for d in r)

        r = s.search(qp.parse("done:yes"))
        assert sorted([d["id"] for d in r]) == ["a", "c", "e"]
        assert all(d["done"] for d in r)

        q = qp.parse("done:false")
        assert q.__class__ == query.Term
        assert q.text is False
        assert schema["done"].to_bytes(False) == b("f")
        r = s.search(q)
        assert sorted([d["id"] for d in r]) == ["b", "d"]
        assert not any(d["done"] for d in r)

        r = s.search(qp.parse("done:no"))
        assert sorted([d["id"] for d in r]) == ["b", "d"]
        assert not any(d["done"] for d in r)

def test_colonspace():
    s = fields.Schema(content=fields.TEXT, url=fields.ID)
    qp = default.QueryParser("content", s)
    q = qp.parse(u("url:test"))
    assert_equal(q.__class__, query.Term)
    assert_equal(q.fieldname, "url")
    assert_equal(q.text, "test")

    q = qp.parse(u("url: test"))
    assert_equal(q.__class__, query.And)
    assert_equal(q[0].__class__, query.Term)
    assert_equal(q[1].__class__, query.Term)
    assert_equal(q[0].fieldname, "content")
    assert_equal(q[1].fieldname, "content")
    assert_equal(q[0].text, "url")
    assert_equal(q[1].text, "test")

    q = qp.parse(u("url:"))
    assert_equal(q.__class__, query.Term)
    assert_equal(q.fieldname, "content")
    assert_equal(q.text, "url")

    s = fields.Schema(foo=fields.KEYWORD)
    qp = default.QueryParser("foo", s)
    q = qp.parse(u("blah:"))
    assert_equal(q.__class__, query.Term)
    assert_equal(q.fieldname, "foo")
    assert_equal(q.text, "blah:")

def test_suggest_prefix():
    domain = ("Shoot To Kill",
              "Bloom, Split and Deviate",
              "Rankle the Seas and the Skies",
              "Lightning Flash Flame Shell",
              "Flower Wind Rage and Flower God Roar, Heavenly Wind Rage and "
              "Heavenly Demon Sneer",
              "All Waves, Rise now and Become my Shield, Lightning, Strike "
              "now and Become my Blade",
              "Cry, Raise Your Head, Rain Without end",
              "Sting All Enemies To Death",
              "Reduce All Creation to Ash",
              "Sit Upon the Frozen Heavens",
              "Call forth the Twilight")

    schema = fields.Schema(content=fields.TEXT(stored=True, spelling=True),
                           quick=fields.NGRAM(maxsize=10, stored=True))

    with TempIndex(schema, "sugprefix") as ix:
        with ix.writer() as w:
            for item in domain:
                content = u(item)
                w.add_document(content=content, quick=content)

        with ix.searcher() as s:
            sugs = s.suggest("content", u("ra"), maxdist=2, prefix=2)
            assert sugs == ['rage', 'rain']

            sugs = s.suggest("content", "ra", maxdist=2, prefix=1)
            assert sugs == ["rage", "rain", "roar"]

def test_requires():
    a = Term("f", u("a"))
    b = Term("f", u("b"))
    assert_equal(And([a, b]).requires(), set([a, b]))
    assert_equal(Or([a, b]).requires(), set())
    assert_equal(AndMaybe(a, b).requires(), set([a]))
    assert_equal(a.requires(), set([a]))

def test_sorting_function():
    schema = fields.Schema(id=fields.STORED, text=fields.TEXT(stored=True, vector=True))
    ix = RamStorage().create_index(schema)
    w = ix.writer()
    domain = ("alfa", "bravo", "charlie")
    count = 1
    for w1 in domain:
        for w2 in domain:
            for w3 in domain:
                for w4 in domain:
                    w.add_document(id=count, text=u(" ").join((w1, w2, w3, w4)))
                    count += 1
    w.commit()

    def fn(searcher, docnum):
        v = dict(searcher.vector_as("frequency", docnum, "text"))
        # Sort documents that have equal number of "alfa"
        # and "bravo" first
        return 0 - 1.0 / (abs(v.get("alfa", 0) - v.get("bravo", 0)) + 1.0)

    fnfacet = sorting.FunctionFacet(fn)

    with ix.searcher() as s:
        q = query.And([query.Term("text", u("alfa")), query.Term("text", u("bravo"))])
        results = s.search(q, sortedby=fnfacet)
        r = [hit["text"] for hit in results]
        for t in r[:10]:
            tks = t.split()
            assert tks.count("alfa") == tks.count("bravo")

def test_compound_sort():
    fspec = fields.KEYWORD(stored=True, sortable=True)
    schema = fields.Schema(a=fspec, b=fspec, c=fspec)
    ix = RamStorage().create_index(schema)

    alist = u("alfa bravo alfa bravo alfa bravo alfa bravo alfa bravo").split()
    blist = u("alfa bravo charlie alfa bravo charlie alfa bravo charlie alfa").split()
    clist = u("alfa bravo charlie delta echo foxtrot golf hotel india juliet").split()
    assert all(len(ls) == 10 for ls in (alist, blist, clist))

    with ix.writer() as w:
        for i in xrange(10):
            w.add_document(a=alist[i], b=blist[i], c=clist[i])

    with ix.searcher() as s:
        q = query.Every()
        sortedby = [sorting.FieldFacet("a"), sorting.FieldFacet("b", reverse=True), sorting.FieldFacet("c")]

        r = s.search(q, sortedby=sortedby)
        output = []
        for hit in r:
            output.append(" ".join((hit["a"], hit["b"], hit["c"])))

        assert output == [
            "alfa charlie charlie",
            "alfa charlie india",
            "alfa bravo echo",
            "alfa alfa alfa",
            "alfa alfa golf",
            "bravo charlie foxtrot",
            "bravo bravo bravo",
            "bravo bravo hotel",
            "bravo alfa delta",
            "bravo alfa juliet",
        ]

def test_overlapping_lists():
    schema = fields.Schema(id=fields.STORED, tags=fields.KEYWORD)
    ix = RamStorage().create_index(schema)
    with ix.writer() as w:
        w.add_document(id=0, tags=u("alfa bravo charlie"))
        w.add_document(id=1, tags=u("bravo charlie delta"))
        w.add_document(id=2, tags=u("charlie delta echo"))
        w.add_document(id=3, tags=u("delta echo alfa"))
        w.add_document(id=4, tags=u("echo alfa bravo"))

    with ix.searcher() as s:
        of = sorting.FieldFacet("tags", allow_overlap=True)
        cat = of.categorizer(s)
        assert not cat._use_vectors

        r = s.search(query.Every(), groupedby={"tags": of})
        assert r.groups("tags") == {
            "alfa": [0, 3, 4],
            "bravo": [0, 1, 4],
            "charlie": [0, 1, 2],
            "delta": [1, 2, 3],
            "echo": [2, 3, 4],
        }

        fcts = sorting.Facets()
        fcts.add_field("tags", allow_overlap=True)
        r = s.search(query.Every(), groupedby=fcts)
        assert r.groups("tags") == {
            "alfa": [0, 3, 4],
            "bravo": [0, 1, 4],
            "charlie": [0, 1, 2],
            "delta": [1, 2, 3],
            "echo": [2, 3, 4],
        }

 def check(method):
     with TempIndex(get_schema()) as ix:
         method(ix)
         with ix.searcher() as s:
             results = s.search(query.Every(), groupedby="tag")
             groups = results.groups()
             assert sorted(groups.items()) == [(u("one"), [0, 6]), (u("three"), [1, 3, 7, 8]), (u("two"), [2, 4, 5])]

 def __unicode__(self):
     r = self.text + u("~")
     if self.maxdist > 1:
         r += u("%d") % self.maxdist
     if self.boost != 1.0:
         r += u("^%f") % self.boost
     return r

def test_requires():
    a = Term("f", u("a"))
    b = Term("f", u("b"))
    assert And([a, b]).requires() == set([a, b])
    assert Or([a, b]).requires() == set()
    assert AndMaybe(a, b).requires() == set([a])
    assert a.requires() == set([a])

def test_keyterms():
    ix = create_index()
    with ix.searcher() as s:
        docnum = s.document_number(path="/a")
        keys = list(s.key_terms([docnum], "content", numterms=3))
        assert ([t[0] for t in keys]
                == [u("collision"), u("calculations"), u("damped")])

def test_boost_phrase():
    schema = fields.Schema(title=fields.TEXT(field_boost=5.0, stored=True), text=fields.TEXT)
    ix = RamStorage().create_index(schema)
    domain = u("alfa bravo charlie delta").split()
    w = ix.writer()
    for ls in permutations(domain):
        t = u(" ").join(ls)
        w.add_document(title=t, text=t)
    w.commit()

    q = Or([Term("title", u("alfa")), Term("title", u("bravo")), Phrase("text", [u("bravo"), u("charlie"), u("delta")])])

    def boost_phrases(q):
        if isinstance(q, Phrase):
            q.boost *= 1000.0
            return q
        else:
            return q.apply(boost_phrases)
    q = boost_phrases(q)

    with ix.searcher() as s:
        r = s.search(q, limit=None)
        for hit in r:
            if "bravo charlie delta" in hit["title"]:
                assert hit.score > 100.0