1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
|
import json
import shutil
from pathlib import Path
from tempfile import TemporaryDirectory
import pytest
from sec_certs import constants
from sec_certs.configuration import config
from sec_certs.dataset.cc import CCDataset
from sec_certs.sample.cc import CCCertificate
from sec_certs.serialization.schemas import validator
from sec_certs.utils import helpers
def test_download_and_convert_pdfs(toy_dataset: CCDataset, data_dir: Path):
template_report_pdf_hashes = {
"e3dcf91ef38ddbf0": "774c41fbba980191ca40ae610b2f61484c5997417b3325b6fd68b345173bde52",
"ed7611868f0f9d97": "533a5995ef8b736cc48cfda30e8aafec77d285511471e0e5a9e8007c8750203a",
"8f08cacb49a742fb": "e277151e4b279085cd3041ce914ffb3942b43e5ace911c557ad6b8ed764a4ece",
}
template_st_pdf_hashes = {
"e3dcf91ef38ddbf0": "b9a45995d9e40b2515506bbf5945e806ef021861820426c6d0a6a074090b47a9",
"ed7611868f0f9d97": "3c8614338899d956e9e56f1aa88d90e37df86f3310b875d9d14ec0f71e4759be",
"8f08cacb49a742fb": "fcee91f09bb72a6526a1f94d0ab754a6db3fbe3ba5773cd372df19788bb25292",
}
template_cert_pdf_hashes = {
"e3dcf91ef38ddbf0": "9d38bca310c4d349cc39471e0b75d939cc275db9a75b07b8a365d719cfbedcc5",
"ed7611868f0f9d97": None,
"8f08cacb49a742fb": "4ba78f26f505819183256ca5a6b404fa90c750fe160c41791e4c400f64e2f6d5",
}
with TemporaryDirectory() as td:
toy_dataset.copy_dataset(td)
toy_dataset.download_all_artifacts()
if not (
toy_dataset["e3dcf91ef38ddbf0"].state.report.download_ok
or toy_dataset["e3dcf91ef38ddbf0"].state.st.download_ok
or toy_dataset["e3dcf91ef38ddbf0"].state.cert.download_ok
or toy_dataset["ed7611868f0f9d97"].state.report.download_ok
or toy_dataset["ed7611868f0f9d97"].state.st.download_ok
or toy_dataset["8f08cacb49a742fb"].state.report.download_ok
or toy_dataset["8f08cacb49a742fb"].state.st.download_ok
or toy_dataset["8f08cacb49a742fb"].state.cert.download_ok
):
pytest.xfail(reason="Fail due to error during download")
toy_dataset.convert_all_pdfs()
for cert in toy_dataset:
assert cert.state.report.pdf_hash == template_report_pdf_hashes[cert.dgst]
assert cert.state.st.pdf_hash == template_st_pdf_hashes[cert.dgst]
assert cert.state.cert.pdf_hash == template_cert_pdf_hashes[cert.dgst]
assert not cert.state.report.convert_garbage
assert not cert.state.st.convert_garbage
assert cert.state.report.convert_ok
assert cert.state.st.convert_ok
assert cert.state.report.txt_path.exists()
assert cert.state.st.txt_path.exists()
if cert.cert_link:
assert cert.state.cert.txt_path.exists()
template_report_txt_path = data_dir / "report_e3dcf91ef38ddbf0.txt"
template_st_txt_path = data_dir / "target_e3dcf91ef38ddbf0.txt"
assert (
abs(toy_dataset["e3dcf91ef38ddbf0"].state.st.txt_path.stat().st_size - template_st_txt_path.stat().st_size)
< 1000
)
assert (
abs(
toy_dataset["e3dcf91ef38ddbf0"].state.report.txt_path.stat().st_size
- template_report_txt_path.stat().st_size
)
< 1000
)
@pytest.mark.remote
def test_from_web():
dset = CCDataset.from_web()
assert len(dset) > 6000
@pytest.mark.remote
def test_archive_fits():
fsize = helpers.query_file_size(config.cc_latest_full_archive)
tmpdir = helpers.tempdir_for(fsize)
assert tmpdir is not None
def test_dataset_to_json(toy_dataset: CCDataset, data_dir: Path, tmp_path: Path):
toy_dataset.to_json(tmp_path / "dset.json")
with (tmp_path / "dset.json").open("r") as handle:
data = json.load(handle)
with (data_dir / "toy_dataset.json").open("r") as handle:
template_data = json.load(handle)
del data["timestamp"]
del template_data["timestamp"]
del data["state"]["sec_certs_version"]
del template_data["state"]["sec_certs_version"]
assert data == template_data
def test_dataset_from_json(toy_dataset: CCDataset, data_dir: Path, tmp_path):
assert toy_dataset == CCDataset.from_json(data_dir / "toy_dataset.json")
compressed_path = tmp_path / "dset.json.gz"
toy_dataset.to_json(compressed_path, compress=True)
decompressed_dataset = CCDataset.from_json(compressed_path, is_compressed=True)
assert toy_dataset == decompressed_dataset
def test_build_empty_dataset():
with TemporaryDirectory() as tmp_dir:
dset = CCDataset({}, Path(tmp_dir), "sample_dataset", "sample dataset description")
dset.get_certs_from_web(to_download=False, get_archived=False, get_active=False)
assert len(dset) == 0
assert dset.state.meta_sources_parsed
assert not dset.state.auxiliary_datasets_processed
assert not dset.state.artifacts_downloaded
assert not dset.state.pdfs_converted
assert not dset.state.certs_analyzed
def test_build_dataset(data_dir: Path, cert_one: CCCertificate, toy_dataset: CCDataset):
with TemporaryDirectory() as tmp_dir:
dataset_path = Path(tmp_dir)
(dataset_path / "web").mkdir()
shutil.copyfile(data_dir / "cc_products_active.csv", dataset_path / "web" / "cc_products_active.csv")
shutil.copyfile(data_dir / "cc_products_active.html", dataset_path / "web" / "cc_products_active.html")
dset = CCDataset({}, dataset_path, "sample_dataset", "sample dataset description")
dset.get_certs_from_web(
keep_metadata=False, to_download=False, get_archived=False, get_active=True, update_json=False
)
assert len(list(dataset_path.iterdir())) == 0
assert len(dset) == 3
assert cert_one in dset
assert dset == toy_dataset
@pytest.mark.xfail(reason="May fail due to error on CC server")
def test_download_csv_html_files():
with TemporaryDirectory() as tmp_dir:
min_html_size = constants.MIN_CC_HTML_SIZE
dset = CCDataset(root_dir=Path(tmp_dir))
dset._download_csv_html_resources(get_active=True, get_archived=False)
for x in dset.active_html_tuples:
assert x[1].exists()
assert x[1].stat().st_size >= min_html_size
for x in dset.active_csv_tuples:
assert x[1].exists()
assert x[1].stat().st_size >= constants.MIN_CC_CSV_SIZE
def test_to_pandas(toy_dataset: CCDataset):
df = toy_dataset.to_pandas()
assert df.shape == (len(toy_dataset), len(CCCertificate.pandas_columns))
assert df.index.name == "dgst"
assert set(df.columns) == (set(CCCertificate.pandas_columns).union({"year_from"})) - {"dgst"}
def test_schema_validate(toy_dataset: CCDataset):
with TemporaryDirectory() as tmp_dir:
single_v = validator("http://sec-certs.org/schemas/cc_certificate.json")
for cert in toy_dataset:
fname = Path(tmp_dir) / (cert.dgst + ".json")
cert.to_json(fname)
with fname.open("r") as handle:
single_v.validate(json.load(handle))
dset_v = validator("http://sec-certs.org/schemas/cc_dataset.json")
fname = Path(tmp_dir) / "dset.json"
toy_dataset.to_json(fname)
with fname.open("r") as handle:
dset_v.validate(json.load(handle))
|
