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# mypy: disallow_untyped_defs=False
import unittest
import extruct
from extruct.uniform import _flatten, _uopengraph, flatten_dict, infer_context
from tests import get_testdata
class TestUniform(unittest.TestCase):
maxDiff = None
def test_uopengraph(self):
expected = [
{
"@context": {
"og": "http://ogp.me/ns#",
"fb": "http://www.facebook.com/2008/fbml",
"concerts": "http://ogp.me/ns/fb/songkick-concerts#",
},
"fb:app_id": "308540029359",
"og:site_name": "Songkick",
"@type": "songkick-concerts:artist",
"og:title": "Elysian Fields",
"og:description": "Buy tickets for an upcoming Elysian Fields concert near you. List of all Elysian Fields tickets and tour dates for 2017.",
"og:url": "http://www.songkick.com/artists/236156-elysian-fields",
"og:image": "http://images.sk-static.com/images/media/img/col4/20100330-103600-169450.jpg",
}
]
body = get_testdata("songkick", "elysianfields.html")
data = extruct.extract(body, syntaxes=["opengraph"], uniform=True)
self.assertEqual(data["opengraph"], expected)
def test_uopengraph_with_og_array(self):
expected = [
{
"@context": {
"og": "http://ogp.me/ns#",
"fb": "http://www.facebook.com/2008/fbml",
"concerts": "http://ogp.me/ns/fb/songkick-concerts#",
},
"fb:app_id": "308540029359",
"og:site_name": "Songkick",
"@type": "songkick-concerts:artist",
"og:title": "Elysian Fields",
"og:description": "Buy tickets for an upcoming Elysian Fields concert near you. List of all Elysian Fields tickets and tour dates for 2017.",
"og:url": "http://www.songkick.com/artists/236156-elysian-fields",
"og:image": [
"http://images.sk-static.com/images/media/img/col4/20100330-103600-169450.jpg",
"http://images.sk-static.com/SECONDARY_IMAGE.jpg",
],
}
]
body = get_testdata("songkick", "elysianfields.html")
data = extruct.extract(
body, syntaxes=["opengraph"], uniform=True, with_og_array=True
)
self.assertEqual(data["opengraph"], expected)
def test_uopengraph_duplicated_priorities(self):
# Ensures that first seen property is kept when flattening
data = _uopengraph(
[
{
"properties": [
("prop_{}".format(k), "value_{}".format(v))
for k in range(5)
for v in range(5)
],
"namespace": "namespace",
}
]
)
for k in range(5):
assert data[0]["prop_{}".format(k)] == "value_0"
# Ensures that empty is not returned if a property contains any
# non empty value
data = _uopengraph(
[
{
"properties": [
("prop_empty", " "),
("prop_non_empty", " "),
("prop_non_empty", "value!"),
("prop_non_empty2", "value!"),
("prop_non_empty2", " "),
("prop_non_empty3", " "),
("prop_non_empty3", "value!"),
("prop_non_empty3", "other value"),
],
"namespace": "namespace",
}
]
)
assert data[0]["prop_empty"] == " "
assert data[0]["prop_non_empty"] == "value!"
assert data[0]["prop_non_empty2"] == "value!"
assert data[0]["prop_non_empty3"] == "value!"
def test_uopengraph_duplicated_with_og_array(self):
# Ensures that first seen property is kept when flattening
data = _uopengraph(
[
{
"properties": [
("prop_{}".format(k), "value_{}".format(v))
for k in range(5)
for v in range(5)
],
"namespace": "namespace",
}
],
with_og_array=True,
)
for k in range(5):
assert data[0]["prop_{}".format(k)] == [
"value_0",
"value_1",
"value_2",
"value_3",
"value_4",
]
# Ensures that empty is not returned if a property contains any
# non empty value
data = _uopengraph(
[
{
"properties": [
("prop_empty", " "),
("prop_non_empty", " "),
("prop_non_empty", "value!"),
("prop_non_empty2", "value!"),
("prop_non_empty2", " "),
("prop_non_empty3", " "),
("prop_non_empty3", "value!"),
("prop_non_empty3", "other value"),
],
"namespace": "namespace",
}
],
with_og_array=True,
)
assert data[0]["prop_empty"] == " "
assert data[0]["prop_non_empty"] == "value!"
assert data[0]["prop_non_empty2"] == "value!"
assert data[0]["prop_non_empty3"] == ["value!", "other value"]
def test_umicroformat(self):
expected = [
{
"@context": "http://microformats.org/wiki/",
"@type": ["h-hidden-phone", "h-hidden-tablet"],
"name": [""],
},
{
"@context": "http://microformats.org/wiki/",
"@type": ["h-hidden-phone"],
"children": [
{"@type": ["h-hidden-phone", "h-hidden-tablet"], "name": [""]},
{
"@type": ["h-hidden-phone"],
"name": [
"aJ Styles FastLane 2018 15 x "
"17 Framed Plaque w/ Ring "
"Canvas"
],
"photo": [
{
"alt": "aJ Styles FastLane 2018 15 x 17 Framed Plaque w/ Ring Canvas",
"value": "/on/demandware.static/-/Sites-main/default/dwa3227ee6/images/small/CN1148.jpg",
}
],
},
],
},
{
"@context": "http://microformats.org/wiki/",
"@type": ["h-entry"],
"author": [
{
"@type": ["h-card"],
"name": ["W. Developer"],
"url": ["http://example.com"],
"value": "W. Developer",
}
],
"content": [
{"html": "<p>Blah blah blah</p>", "value": "Blah blah blah"}
],
"name": ["Microformats are amazing"],
"published": ["2013-06-13 12:00:00"],
"summary": ["In which I extoll the virtues of using " "microformats."],
},
]
body = get_testdata("misc", "microformat_test.html")
data = extruct.extract(body, syntaxes=["microformat"], uniform=True)
self.assertEqual(data["microformat"], expected)
def test_umicrodata(self):
expected = [
{
"@context": "http://schema.org",
"@type": "Product",
"brand": "ACME",
"name": "Executive Anvil",
"image": "anvil_executive.jpg",
"description": "Sleeker than ACME's Classic Anvil, the Executive Anvil is perfect for the business traveler looking for something to drop from a height.",
"mpn": "925872",
"aggregateRating": {
"@type": "AggregateRating",
"ratingValue": "4.4",
"reviewCount": "89",
},
"offers": {
"@type": "Offer",
"priceCurrency": "USD",
"price": "119.99",
"priceValidUntil": "2020-11-05",
"seller": {"@type": "Organization", "name": "Executive Objects"},
"itemCondition": "http://schema.org/UsedCondition",
"availability": "http://schema.org/InStock",
},
}
]
body = get_testdata("misc", "product_microdata.html")
data = extruct.extract(body, syntaxes=["microdata"], uniform=True)
self.assertEqual(data["microdata"], expected)
def test_udublincore(self):
expected = [
{
"elements": [
{
"name": "DC.title",
"lang": "en",
"content": "Expressing Dublin Core\nin HTML/XHTML meta and link elements",
"URI": "http://purl.org/dc/elements/1.1/title",
},
{
"name": "DC.creator",
"content": "Andy Powell, UKOLN, University of Bath",
"URI": "http://purl.org/dc/elements/1.1/creator",
},
{
"name": "DC.identifier",
"scheme": "DCTERMS.URI",
"content": "http://dublincore.org/documents/dcq-html/",
"URI": "http://purl.org/dc/elements/1.1/identifier",
},
{
"name": "DC.format",
"scheme": "DCTERMS.IMT",
"content": "text/html",
"URI": "http://purl.org/dc/elements/1.1/format",
},
],
"terms": [
{
"name": "DCTERMS.issued",
"scheme": "DCTERMS.W3CDTF",
"content": "2003-11-01",
"URI": "http://purl.org/dc/terms/issued",
},
{
"name": "DCTERMS.abstract",
"content": "This document describes how\nqualified Dublin Core metadata can be encoded\nin HTML/XHTML <meta> elements",
"URI": "http://purl.org/dc/terms/abstract",
},
{
"name": "DC.Date.modified",
"content": "2001-07-18",
"URI": "http://purl.org/dc/terms/modified",
},
{
"name": "DCTERMS.modified",
"content": "2001-07-18",
"URI": "http://purl.org/dc/terms/modified",
},
{
"rel": "DCTERMS.replaces",
"hreflang": "en",
"href": "http://dublincore.org/documents/2000/08/15/dcq-html/",
"URI": "http://purl.org/dc/terms/replaces",
},
],
"@context": {
"DC": "http://purl.org/dc/elements/1.1/",
"DCTERMS": "http://purl.org/dc/terms/",
},
"@type": "Text",
}
]
body = get_testdata("misc", "dublincore_test.html")
data = extruct.extract(body, syntaxes=["dublincore"], uniform=True)
self.assertEqual(data["dublincore"], expected)
def test_infer_context(self):
context = "http://schema.org/UsedCondition"
self.assertEqual(infer_context(context), ("http://schema.org", "UsedCondition"))
context = "http://ogp.me/ns#description"
self.assertEqual(infer_context(context), ("http://ogp.me/ns", "description"))
context = "http://ogp.me/ns/fb#app_id"
self.assertEqual(infer_context(context), ("http://ogp.me/ns/fb", "app_id"))
def test_flatten_dict(self):
d = {
"type": "SPANISH INQUISITION",
"properties": {
"chief_weapon": "surprise",
"extra_weapon": "fear",
"another_one": "ruthless efficiency",
},
}
expected = {
"@type": "SPANISH INQUISITION",
"@context": "http://schema.org",
"chief_weapon": "surprise",
"extra_weapon": "fear",
"another_one": "ruthless efficiency",
}
self.assertEqual(
flatten_dict(d, schema_context="http://schema.org", add_context=True),
expected,
)
def test_flatten(self):
d = {
"children": [
{
"properties": {"name": [""]},
"type": ["h-hidden-tablet", "h-hidden-phone"],
},
{
"properties": {
"name": [
"aJ Styles "
"FastLane 2018 "
"15 x 17 Framed "
"Plaque w/ Ring "
"Canvas"
],
"photo": ["path.jpg"],
},
"type": ["h-hidden-phone"],
},
],
"properties": {"name": [""]},
"type": ["h-hidden-phone"],
}
expected = {
"children": [
{"name": [""], "@type": ["h-hidden-tablet", "h-hidden-phone"]},
{
"name": [
"aJ Styles "
"FastLane 2018 "
"15 x 17 Framed "
"Plaque w/ Ring "
"Canvas"
],
"photo": ["path.jpg"],
"@type": ["h-hidden-phone"],
},
],
"name": [""],
"@type": ["h-hidden-phone"],
}
self.assertEqual(_flatten(d, schema_context="http://schema.org"), expected)
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