aboutsummaryrefslogtreecommitdiffstats
path: root/python/sandcrawler/pdfextract.py
blob: 3adee3a58346abddef82f7fe2108c15d8aebbb22 (plain)
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
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441

import sys
import json
import datetime
from io import BytesIO
from dataclasses import dataclass
from typing import Optional, Dict, Any

import poppler
from PIL import Image

from .workers import SandcrawlerWorker, SandcrawlerFetchWorker
from .misc import gen_file_metadata


# This is a hack to work around timeouts when processing certain PDFs with
# poppler. For some reason, the usual Kafka timeout catcher isn't working on
# these, maybe due to threading.
BAD_PDF_SHA1HEX = [
    "011478a1e63a2a31eae1a93832a74cc95f220760",
    "018dfe9824de6d2ac068ce0f7dc9961bffa1b558",
    "057c7a9dfb611bfd52f7de6c39b2d5757c5e4e53",
    "06061af0707298c12932516d1bb7c2b6dc443824",
    "0641822e68c5a07538b967489fd19a1d5dc371a5",
    "09cba9b00494d12759c50cb914f1fb7c9746f5d1",
    "09db7c9f2efb496c974427a61e84292ae27fc702",
    "0a1c13cb8783bbbf248b2345b9890e2410aa3f0a",
    "0d1c1567ea70e7b922ba88ccb868ffc7ca18e75c",
    "10c6577a658bf6203557e2998b25ea9788f8adfe",
    "15a720921ce30da983fcd1bfa7fe9aeeda503e41",
    "1659881a31edc2d0e170f6bb26d32e74cc4ca387",
    "17e679b0ec9444fff2ea4d02caec05dd2de80ec3",
    "182749ad1db1d5e999d07f010bdcfc2978dadc88",
    "1cb166f0c0b5ffe673e6bbf6a29d77278711f253",
    "1d04e46b6848e6479dd90fe26bb11627044fb664",
    "1d967c95546d31edaaf0c3ef9ffcc11113a9e11a",
    "20589d9dd0a22c8c938ad97b7f4f12648aa119fa",
    "25ab9e6169f041be05844a9b4edd6574918af769",
    "281de904c4642a9be4f17b9774fc0a2bdc8a90e3",
    "2bd5322975653536550a039eb055174b2bf241b3",
    "2fc64da736175810918fd32c94c5068b0d660bcc",
    "32318fba9b05b2756b7362bcaa4722c92ed8d449",
    "336833c6fc968cd0938250dfc93c032a30111cfc",
    "362ad00bc24d650c8f11851f9e554fc560b73e7a",
    "373f84dfab4ed47047826e604e2918a9cd6a95b2",
    "3ac0b6e17e30d141871a0a5b127536919fe5aa19",
    "3c8a6a708da0dc1802f5f3e5267a49b3c25e1ffe",
    "3e5f9fb94e7314447a22f3d009419a922136177f",
    "3fad493c940137ce703f2f570ebb504e360c6df3",
    "436c9183724f051b22c96285aa8ff1d2ba709574",
    "445968ef735b228c08c3ff4238d99fc9f4824619",
    "447fa6b5a90742a86429a932f6608d8e141688c0",
    "4785181cec8944eee00ddb631a5dfc771b89bab7",
    "47db2db2cc976429568841a0496c0ab4ed7b5977",
    "4c81129904f7976a50825595a3497ea7b52579ef",
    "4edc1402712fa6827c4501fed8042e9f4447829c",
    "50b3c5a3122272aca69855ef06b85d0b43a76eb1",
    "52fc9b3c5199ef395d410c7cee5961dc812e4d29",
    "58d9ae7dcb0a7dbbdfc58ad266030b037e9cd0ff",
    "59cfc843ebdb1c1e5db1efc76a40f46cb3bb06f0",
    "5ab98405b676ee81a6ca74fba51a9e4a6cff7311",
    "5e04779cbbae5ce88bb786064f756885dd6895fe",
    "5e6a3adde9f08c276c4efd72bfacb256f2ec35d9",
    "623ff84b616383d0a3e0dd8dbce12f0b5fe9a6ac",
    "646c4a654270606256397684204ff0f3d17be2e7",
    "64d821d728f9a3dc944b4c03be00feea0b57e314",
    "6909f0b62d8b7835de3dec7777aad7f8ef507ee3",
    "74e617dc95555e8ca3aadd19d0c85b71cd77d1d9",
    "75c2662a96ccc48891228df7c85eb7d4da9dd621",
    "771f1ca0007a6fbed5b4a434c73f524f715d33c1",
    "776859635e9dc01d97b0582f49c814ffbcb019fb",
    "781dafda896a9f5c30f3d0a011f79a3b79b574c4",
    "788672c7c2bcdecf6e2f6a2177c01e60f04d9cfb",
    "79d6cba3c6e577a0f3a3a9fe575680d38454938d",
    "7daf61526ec825151f384cc1db510ca5237d5d80",
    "7e9d846f3bf9ce15cdb991b78cc870ab8a2bed76",
    "859d7ec532a0bf3b52b17c7f2d8ecc58410c0aad",
    "88edcbab1cac2d70af5870422974afc253f4f0c6",
    "89860fc475fcb2a2d86c4544df52ec8fd5e6533f",
    "8dcaf4ef132900dd378f7be526c884b17452713b",
    "8e4f03c29ae1fe7227140ab4b625f375f6c00d31",
    "949dfb7d833da9576b2ccb9eb1ab5457469c53d3",
    "961ec451172f373f919c593737466300e42062cb",
    "976989fa6e447578d9ce16ec5b526f0e09d6df50",
    "98b02eb70066c182c705ef4d14d8b723ad7f1fab",
    "993ca31f6974f8387bb18dd7d38987d290da8781",
    "9dbd05af3442e6f42d67868054751b76973f4171",
    "a2298c137b9c8c8975bad62eea9224edb95e6952",
    "a2671738755ab8b24775e95375dc72f1ca4e5fd6",
    "a26f299fb97c646effeebd4c5e2968786bd0f781",
    "a48f9b7ad627909f76d780aa4208530304ece42c",
    "a69665d0b5d3b95f54f68406eee3ed50c67efb45",
    "a69665d0b5d3b95f54f68406eee3ed50c67efb45",
    "a8357c31837404f9ebd798999d546c9398ab3648",
    "a9162b9aef5e5da0897275fede1a6cff8cc93dfc",
    "ad038725bf6855a79f3c768ebe93c7103d14522f",
    "b2b66b9c7f817a20144456f99c0be805602e8597",
    "b2d719120306b90eb8dd3580b699a61ec70556f4",
    "b4b8e18e27f102e59b2be2d58c7b54d0a0eb457a",
    "b5be7f409a3a2601208c5ce08cf52b9ac1094aae",
    "b5bf8b7467fb095c90adf3b49aa1687291e4469c",
    "b8b427e5b3d650ba9e03197f9c3917e25b878930",
    "bad48b89b639b5b7df2c6a2d5288181fcb8b0e35",
    "be0cda7642e9247b3ee41cd2017fa709aab4f344",
    "c1b583fbd052572f08158d39ffe4d7510dadbebb",
    "c7220d1bf1e71fb755d9f26bbdd4c539dc162960",
    "c7687fa6f637c7d32a25be0e772867d87536d35c",
    "c92b9ae9eefa07504950b405625aef54b48f0e1a",
    "ccb1debcfae006a3fc984e9e91309b9706a5c375",
    "cd8a7c3b8d850ebedc1ca791ccb37b9a2689f9c3",
    "d17b1e254cce82df5c6eb4fd492cef91e7e11558",
    "d188762a7e3ab5d4ee8a897204316513e4e636ec",
    "d6b0f405bf13c23d0e90c54eea527442786d1cd3",
    "da2211ee2dbc6dda36571976d810e2366a3d2504",
    "e01bb7256d77aea258313bb410dfcfc10512f420",
    "e2bf5d0a5885359381fe8ef2cd9290171d494e9b",
    "e2c3b8a2cf33d5e8972bc9ddb78373766a75e412",
    "e9d7716b4f94bbc3d94459b5fe9bb8b15cb2e433",
    "eac7df5f799983d5a7cc55d10b4d426dc557febf",
    "eb1b39fd7a874896688855a22efddef10272427c",
    "eb5fffaa590a52bcc3705b888c6ff9c4dc4c45b2",
    "ee9530a2c5a3d1e3813ccb51a55cc8b0d9b5dfc7",
    "f0ea221d8587cede25592266486e119d277f7096",
    "f68f9a9202a75d2aee35252e104d796f9515001e",
    "f9314d3bf2eac78a7d78d18adcccdb35542054ef",
]

@dataclass
class PdfExtractResult:
    sha1hex: str
    status: str
    error_msg: Optional[str] = None
    file_meta: Optional[Dict[str,Any]] = None
    text: Optional[str] = None
    page0_thumbnail: Optional[bytes] = None
    has_page0_thumbnail: bool = False
    meta_xml: Optional[str] = None
    pdf_info: Optional[Dict[str,Any]] = None
    pdf_extra: Optional[Dict[str,Any]] = None
    source: Optional[Dict[str,Any]] = None

    def to_pdftext_dict(self) -> dict:
        """
        Outputs a JSON string as would be published to Kafka text/info topic.
        """
        return {
            'key': self.sha1hex,
            'sha1hex': self.sha1hex,
            'status': self.status,
            'file_meta': self.file_meta,
            'error_msg': self.error_msg,
            'text': self.text,
            'has_page0_thumbnail': self.has_page0_thumbnail,
            'meta_xml': self.meta_xml,
            'pdf_info': self.pdf_info,
            'pdf_extra': self.pdf_extra,
            'source': self.source,
        }

    @classmethod
    def from_pdftext_dict(cls, record):
        """
        Outputs a JSON string as would be published to Kafka text/info topic.
        """
        if record['status'] != 'success':
            return PdfExtractResult(
                sha1hex=record.get('sha1hex') or record['key'],
                status=record['status'],
                error_msg=record.get('error_msg'),
            )
        else:
            return PdfExtractResult(
                sha1hex=record['sha1hex'],
                status=record['status'],
                file_meta=record.get('file_meta'),
                text=record.get('text'),
                has_page0_thumbnail=bool(record.get('has_page0_thumbnail', False)),
                meta_xml=record.get('meta_xml'),
                pdf_info=record.get('pdf_info'),
                pdf_extra=record.get('pdf_extra'),
            )

    @classmethod
    def from_pdf_meta_dict(cls, record):
        """
        Parses what would be returned from postgrest
        """
        if record['status'] != 'success':
            return PdfExtractResult(
                sha1hex=record['sha1hex'],
                status=record['status'],
                error_msg=(record.get('metadata') or {}).get('error_msg'),
            )
        else:
            pdf_extra = dict()
            for k in ('page_count', 'page0_height', 'page0_width', 'permanent_id', 'pdf_version'):
                if record.get(k):
                    pdf_extra[k] = record[k]
            return PdfExtractResult(
                sha1hex=record['sha1hex'],
                status=record['status'],
                has_page0_thumbnail=bool(record.get('has_page0_thumbnail', False)),
                pdf_info=record.get('metadata'),
                pdf_extra=pdf_extra,
            )

    def to_sql_tuple(self) -> tuple:
        # pdf_meta (sha1hex, updated, status, page0_thumbnail, page_count,
        # word_count, page0_height, page0_width, permanent_id, pdf_created,
        # pdf_version, metadata)
        word_count: Optional[int] = None
        if self.text:
            word_count = len(self.text.split())
        metadata: Optional[Dict] = None
        pdf_extra = self.pdf_extra or dict()
        pdf_created = None
        # TODO: form, encrypted
        if self.pdf_info:
            metadata = dict()
            for k in ('Title', 'Subject', 'Author', 'Creator', 'Producer', 'doi'):
                if k in self.pdf_info:
                    metadata[k.lower()] = self.pdf_info[k]
            if 'CreationDate' in self.pdf_info:
                pdf_created = self.pdf_info['CreationDate']
        metadata_json: Optional[str] = None
        if metadata:
            metadata_json = json.dumps(metadata, sort_keys=True)
        return (
            self.sha1hex,
            datetime.datetime.now(), # updated
            self.status,
            self.has_page0_thumbnail,
            pdf_extra.get('page_count'),
            word_count,
            pdf_extra.get('page0_height'),
            pdf_extra.get('page0_width'),
            pdf_extra.get('permanent_id'),
            pdf_created,
            pdf_extra.get('pdf_version'),
            metadata_json,
        )


def process_pdf(blob: bytes, thumb_size=(180,300), thumb_type="JPEG") -> PdfExtractResult:
    """
    A known issue is that output text is in "physical layout" mode, which means
    columns will be side-by-side. We would prefer a single stream of tokens!

    Tried using page.text(layout_mode=poppler.TextLayout.raw_order_layout)
    instead of the default mode (poppler.TextLayout.physical_layout), but that
    didn't seem to work at all (returned empty strings).
    """
    file_meta = gen_file_metadata(blob)
    sha1hex = file_meta['sha1hex']
    if file_meta['mimetype'] != 'application/pdf':
        return PdfExtractResult(
            sha1hex=sha1hex,
            status='not-pdf',
            error_msg=f"mimetype is '{file_meta['mimetype']}'",
            file_meta=file_meta,
        )

    if sha1hex in BAD_PDF_SHA1HEX:
        return PdfExtractResult(
            sha1hex=sha1hex,
            status='bad-pdf',
            error_msg=f"PDF known to cause processing issues",
            file_meta=file_meta,
        )

    print(f"\tpoppler processing: {sha1hex}", file=sys.stderr)
    try:
        pdf = poppler.load_from_data(blob)
        if pdf is None:
            return PdfExtractResult(
                sha1hex=sha1hex,
                status='empty-pdf',
                file_meta=file_meta,
                has_page0_thumbnail=False,
            )
        page0 = pdf.create_page(0)
        if page0 is None:
            return PdfExtractResult(
                sha1hex=sha1hex,
                status='empty-page0',
                file_meta=file_meta,
            )
        # this call sometimes fails an returns an AttributeError
        page0rect = page0.page_rect()
    except (AttributeError, poppler.document.LockedDocumentError) as e:
        # may need to expand the set of exceptions caught here over time, but
        # starting with a narrow set
        return PdfExtractResult(
            sha1hex=sha1hex,
            status='parse-error',
            error_msg=str(e),
            file_meta=file_meta,
        )

    assert page0 is not None
    page0_thumbnail: Optional[bytes] = None
    renderer = poppler.PageRenderer()
    try:
        full_img = renderer.render_page(page0)
        img = Image.frombuffer("RGBA", (full_img.width, full_img.height), full_img.data, 'raw', "BGRA", 0, 1)
        img.thumbnail(thumb_size, Image.BICUBIC)
        buf = BytesIO()
        img.save(buf, thumb_type)
        page0_thumbnail = buf.getvalue()
        # assuming that very small images mean something went wrong
        if page0_thumbnail is None or len(page0_thumbnail) < 50:
            page0_thumbnail = None
    except Exception as e:
        print(str(e), file=sys.stderr)
        page0_thumbnail = None

    try:
        full_text = page0.text()
        for n in range(1, pdf.pages):
            pageN = pdf.create_page(n)
            full_text += pageN.text()
    except AttributeError as e:
        return PdfExtractResult(
            sha1hex=sha1hex,
            status='parse-error',
            error_msg=str(e),
            file_meta=file_meta,
        )

    # Kafka message size limit; cap at about 1 MByte
    if len(full_text)> 1000000:
        return PdfExtractResult(
            sha1hex=sha1hex,
            status='text-too-large',
            error_msg="full_text chars: {}".format(len(full_text)),
            file_meta=file_meta,
        )
    if len(pdf.metadata)> 1000000:
        return PdfExtractResult(
            sha1hex=sha1hex,
            status='text-too-large',
            error_msg="meta_xml chars: {}".format(len(full_text)),
            file_meta=file_meta,
        )

    try:
        pdf_info = pdf.infos()
    except UnicodeDecodeError:
        return PdfExtractResult(
            sha1hex=sha1hex,
            status='bad-unicode',
            error_msg="in infos()",
            file_meta=file_meta,
        )

    # TODO: is this actually needed? or does json marshalling work automatically?
    for k in pdf_info.keys():
        if isinstance(pdf_info[k], datetime.datetime):
            pdf_info[k] = datetime.datetime.isoformat(pdf_info[k])

    permanent_id: Optional[str] = None
    update_id: Optional[str] = None
    try:
        permanent_id = pdf.pdf_id.permanent_id
        update_id = pdf.pdf_id.update_id
    except TypeError:
        pass

    return PdfExtractResult(
        sha1hex=sha1hex,
        file_meta=file_meta,
        status='success',
        error_msg=None,
        text=full_text or None,
        has_page0_thumbnail=page0_thumbnail is not None,
        page0_thumbnail=page0_thumbnail,
        meta_xml=pdf.metadata or None,
        pdf_info=pdf_info,
        pdf_extra=dict(
            page0_height=page0rect.height,
            page0_width=page0rect.width,
            page_count=pdf.pages,
            permanent_id=permanent_id,
            update_id=update_id,
            pdf_version=f"{pdf.pdf_version[0]}.{pdf.pdf_version[1]}",
        ),
    )

class PdfExtractWorker(SandcrawlerFetchWorker):

    def __init__(self, wayback_client=None, sink=None, **kwargs):
        super().__init__(wayback_client=wayback_client)
        self.wayback_client = wayback_client
        self.sink = sink
        self.thumbnail_sink = kwargs.get('thumbnail_sink')

    def timeout_response(self, task) -> Dict:
        default_key = task['sha1hex']
        return dict(
            status="error-timeout",
            error_msg="internal pdf-extract worker timeout",
            source=task,
            sha1hex=default_key,
        )

    def process(self, record, key: Optional[str] = None):
        default_key = record['sha1hex']

        fetch_result = self.fetch_blob(record)
        if fetch_result['status'] != 'success':
            return fetch_result
        blob = fetch_result['blob']

        result = process_pdf(blob)
        result.source = record
        if self.thumbnail_sink and result.page0_thumbnail is not None:
            self.thumbnail_sink.push_record(result.page0_thumbnail, key=result.sha1hex)
        return result.to_pdftext_dict()

class PdfExtractBlobWorker(SandcrawlerWorker):
    """
    This is sort of like PdfExtractWorker, except it receives blobs directly,
    instead of fetching blobs from some remote store.
    """

    def __init__(self, sink=None, **kwargs):
        super().__init__()
        self.sink = sink
        self.thumbnail_sink = kwargs.get('thumbnail_sink')

    def process(self, blob, key: Optional[str] = None):
        if not blob:
            return None
        assert isinstance(blob, bytes)

        result = process_pdf(blob)
        if self.thumbnail_sink and result.page0_thumbnail is not None:
            self.thumbnail_sink.push_record(result.page0_thumbnail, key=result.sha1hex)

        return result.to_pdftext_dict()