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rewrite data fetching into archive_item.py

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Brent Schroeter 2025-10-04 18:03:03 -07:00
parent 4d9161b043
commit d5757e3811
5 changed files with 446 additions and 106 deletions
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2
.gitignore vendored
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@ -1,4 +1,6 @@
/target
/data
*.db
*.db-journal
/archive_cache
__pycache__

307
archive_item.py Normal file
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@ -0,0 +1,307 @@
"""
Python utilities for structuring data and metadata pulled from archive.org
microfiche scans.
"""
import json
import os
import urllib
from contextlib import nullcontext
from dataclasses import dataclass
from io import BytesIO
from typing import Optional
from zipfile import ZipFile
import requests
from PIL import Image
CACHE_DIR = "./archive_cache"
@dataclass
class ArchiveLeaf:
"""
A leaf corresponds to a single image from one of the "Single Page Processed
JP2 Zip" files from an `ArchiveItem`. Not all leaves become part of the
final processed PDF displayed to the user, as some contain metadata or
superfluous information scanned off of the microfiche cards and retained for
posterity. To identify whether a leaf is pertinent or not, refer to the page
number metadata pulled as JSON from the archive.org API.
Attributes:
image PIL Image, pre-scaled using .thumbnail() to fit the long
edge to 3200 pixels.
page_number `None` if the leaf is not included in the processed PDF
presented to users, otherwise a (potentially empty)
string with the inferred page number as defined by the
document being scanned.
"""
image: Image
page_number: Optional[str]
@dataclass
class ArchiveDoc:
"""
Information pertaining to a single set of processed pages, of which there
may be multiple for any given ArchiveItem. For example, one SCOTUS case may
contain several briefs/petitions/etc., each presented as a distinct PDF but
all held within the parent `ArchiveItem`.
Note that this is a slightly different concept than the literal "files"
available via the archive.org API: an `ArchiveDoc` may combine information
from, say, both a `_page_numbers.json` file and a `_jp2.zip` file to store
image data and page number data conveniently within the same Python object.
Attributes:
identifier archive.org identifier string, for example
`"micro_IA40386007_0012"`.
name Document name, with the item identifier, leading whitespace,
and file extension stripped.
title Optional `title` metadata field assigned to the `_jp2.zip`
file, usually indicating that this file represents a subset
of the parent item's content, for example a specific brief
or opinion from a larger SCOTUS case document.
For QA intents and purposes, it's usually easiest to skip
over any documents where `title is not None`, assuming that
the item has at least one processed `_jp2.zip` file for
which `title is None`.
"""
identifier: str
name: str
title: Optional[str]
def fetch_leaves(self, numbered_only=True, use_cache=False) -> list[ArchiveLeaf]:
"""
Fetch images and page number data for this document from archive.org,
over the Internet.
Params:
numbered_only If `True`, discards any leaves with no corresponding
page number entries. Leaves for which the page
number is an empty string are retained.
use_cache If `True`, locally cached zip files under the
`./archive_cache` directory (relative to the working
directory) will be used instead of fetching over
HTTPS.
"""
if use_cache:
# Cached file names are derived from the percent-encoded verison of
# `self.name`, so that there's no need to worry about directory
# separators or other disallowed characters in the file names
# defined by archive.org.
with open(
f"{CACHE_DIR}/{_url_encode(self.name)}_page_numbers.json", "r"
) as f:
page_nums = json.load(f)["pages"]
zip_reader_ctx = open(f"{CACHE_DIR}/{_url_encode(self.name)}_jp2.zip", "rb")
else:
page_nums = _fetch_page_nums(self.identifier, self.name)["pages"]
# Wrap in a context manager so that the reader can be used in a `with`
# block in the same way as a file accessed with `open()`.
zip_reader_ctx = nullcontext(
BytesIO(_fetch_jp2_zip(self.identifier, self.name))
)
leaves = []
with zip_reader_ctx as zip_reader, ZipFile(zip_reader) as jp_zip:
for leaf_num, file_name in enumerate(sorted(jp_zip.namelist())):
for page_index, page_num_info in enumerate(page_nums):
if page_num_info["leafNum"] == leaf_num:
# Stop iterating and keep page_index set to the current
# value.
break
else:
# Indicate that leaf was not found in page_num list.
page_index = None
with jp_zip.open(file_name) as jp_file:
# Convert to single-channel greyscale ("L").
image = Image.open(jp_file).convert("L")
# Rescale long edge to no more than 3200 px.
image.thumbnail((3200, 3200))
leaves.append(ArchiveLeaf(image=image, page_number=page_index))
return leaves
@dataclass
class ArchiveItem:
"""
Information pertaining to an archive.org item. Documents, ultimately of type
`ArchiveDoc`, are referenced by name only in this class so that content
downloads for individual `ArchiveDoc`s may be skipped, staggered, or
performed in parallel if desired, rather than in one chunk per item.
Attributes:
identifier archive.org identifier string, for example
`"micro_IA40386007_0012"`.
docs List of `ArchiveDoc` names, with the item identifier,
leading whitespace, and file extension stripped.
"""
identifier: str
docs: list[ArchiveDoc]
def fetch_item(identifier: str, use_cache=False) -> ArchiveItem:
"""
Fetch the relevant top-level information for an `ArchiveItem` from
archive.org. This assumes a specific naming convention for the item's files:
- `<identifier>[ Title]_jp2.zip` for processed scans
- `<identifier>[ Title]_page_numbers.json` for page number metadata
- `<identifier>_micro_jp2.zip` for unprocessed scans
This function treats file names as case-insensitive, but preserves casing in
its output.
Params:
identifier archive.org identifier string, for example
`"micro_IA40386007_0012"`.
use_cache If `True`, locally cached zip files under the
`./archive_cache` directory (relative to the working
directory) will be used instead of fetching over HTTPS.
"""
if use_cache:
# File names should be treated as case-insensitive, in case the file
# system is case-insensitive. As I understand it, this applies to FAT
# and APFS in their default configurations. Both are case-preserving, so
# this shouldn't usually be an issue, but if/when it is, it can be very
# frustrating to troubleshoot user-side.
file_names = [
_url_decode(name)
for name in os.listdir(CACHE_DIR)
if name.lower().startswith(identifier.lower())
]
else:
files_resp = requests.get(
f"https://archive.org/metadata/{_url_encode(identifier)}/files"
)
files_resp.raise_for_status()
file_names = [item["name"] for item in files_resp.json()["result"]]
doc_names = [
# Strip suffix, to just leave the identifier, and title if present.
name[: -len("_jp2.zip")]
for name in file_names
if name.lower().endswith("_jp2.zip")
# Exclude unprocessed scans, which are also named `..._jp2.zip`.
and name.lower() != f"{identifier.lower()}_micro_jp2.zip"
]
# Assert that all files we expect to find are actually present.
for doc_name in doc_names:
if f"{_url_encode(doc_name.lower())}_page_numbers.json" not in [
name.lower() for name in file_names
]:
raise Exception(
f"expected file not found: {_url_encode(doc_name.lower())}_page_numbers.zip"
)
return ArchiveItem(
identifier=identifier,
docs=[
ArchiveDoc(
identifier=identifier,
name=name,
title=name[len(identifier) :].strip() or None,
)
for name in doc_names
],
)
def cache_item(identifier: str, overwrite=True):
"""
Load the relevant files for an `ArchiveItem` and its component `ArchiveDoc`s
and store them within the `archive_cache` directory (relative to the working
directory). The `archive_cache` directory will be created if it does not
exist.
Params:
identifier archive.org identifier string, for example
`"micro_IA40386007_0012"`.
overwrite If set to `False` and any file names in the cache already
match the item, fetching the item is skipped.
"""
os.makedirs(CACHE_DIR, exist_ok=True)
for name in os.listdir(CACHE_DIR):
if _url_decode(name.lower()).startswith(identifier.lower()):
return
item = fetch_item(identifier)
for doc in item.docs:
page_nums = _fetch_page_nums(identifier, doc.name)
zip_file = _fetch_jp2_zip(identifier, doc.name)
with open(f"{CACHE_DIR}/{_url_encode(doc.name)}_page_numbers.json", "w") as f:
json.dump(page_nums, f)
with open(f"{CACHE_DIR}/{_url_encode(doc.name)}_jp2.zip", "wb") as f:
f.write(zip_file)
def _url_encode(string: str) -> str:
"""
Helper to encode to a URL-encoded (in other words, percent-encoded) string.
"""
return urllib.parse.quote(string, safe=" ._")
def _url_decode(string: str) -> str:
"""
Helper to decode from a URL-encoded (in other words, percent-encoded)
string.
"""
return urllib.parse.unquote(string)
def _fetch_page_nums(identifier: str, doc_name: str) -> dict:
"""
Fetch JSON file with page number metadata for an `ArchiveDoc`.
"""
# `self.name` does not get percent-encoded, because it is derived from the
# file path itself as defined by archive.org. Percent- encoding it further
# may result in a 404 error.
page_nums_resp = requests.get(
f"https://archive.org/download/{_url_encode(identifier)}/{doc_name}_page_numbers.json"
)
page_nums_resp.raise_for_status()
return page_nums_resp.json()
def _fetch_jp2_zip(identifier: str, doc_name: str) -> bytes:
"""
Fetch zip file with processed page scans for an `ArchiveDoc`.
"""
# `self.name` does not get percent-encoded, because it is derived
# from the file path itself as defined by archive.org. Percent-
# encoding it further may result in a 404 error.
zip_resp = requests.get(
f"https://archive.org/download/{_url_encode(identifier)}/{doc_name}_jp2.zip"
)
zip_resp.raise_for_status()
return zip_resp.content

65
diagnostics.py Normal file
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@ -0,0 +1,65 @@
import json
from argparse import ArgumentParser
from time import time
import numpy as np
from archive_item import cache_item, fetch_item
from engine import analyze_doc
def main():
parser = ArgumentParser()
parser.add_argument("--item-id")
parser.add_argument("--cpus", type=int, default=4)
args = parser.parse_args()
cache_item(
args.item_id,
# Will not refetch if value is already cached.
overwrite=False,
)
item = fetch_item(args.item_id, use_cache=True)
t_start = time()
minimal_docs = (
[doc for doc in item.docs if doc.name != ""]
if len(item.docs) > 1
else item.docs
)
analyses = [
analyze_doc(doc, parallel=args.cpus, use_cache=True) for doc in minimal_docs
]
t_end = time()
print(
json.dumps(
{
"analyses": analyses,
"duration_secs": t_end - t_start,
"disoriented_pages": [
[
i
for i, page in enumerate(doc["pages"])
if not page["ocr_orientation_match"]
]
for doc in analyses
],
"sharpness_max": max(
*[page["sharpness"] for doc in analyses for page in doc["pages"]]
),
"sharpness_median": np.median(
[page["sharpness"] for doc in analyses for page in doc["pages"]]
).tolist(),
"sharpness_min": min(
*[page["sharpness"] for doc in analyses for page in doc["pages"]]
),
}
)
)
if __name__ == "__main__":
main()

64
engine.py
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@ -1,62 +1,30 @@
import urllib.parse
import re
from dataclasses import dataclass
from io import BytesIO
from multiprocessing import Pool
from sys import stderr
from zipfile import ZipFile
from sys import stdout
import numpy as np
import pytesseract
import requests
from PIL import Image, ImageFilter
from archive_item import ArchiveDoc
def analyze_item(item_id, ocr_langs="eng+fra", parallel=1, verbose=False):
escaped_item_id = urllib.parse.quote(item_id, safe="")
def analyze_doc(
doc: ArchiveDoc, ocr_langs="eng+fra", parallel=1, use_cache=False, verbose=False
):
if verbose:
print(f"Loading {doc.name}...")
stdout.flush()
tasks: PageAnalysisTask = [
PageAnalysisTask(im=leaf.image, ocr_langs=ocr_langs)
for leaf in doc.fetch_leaves(use_cache=use_cache)
]
if verbose:
print("Downloading...", file=stderr)
stderr.flush()
page_nums_resp = requests.get(
f"https://archive.org/metadata/{escaped_item_id}/page_numbers/pages"
)
page_nums_resp.raise_for_status()
page_nums = page_nums_resp.json()["result"]
zip_resp = requests.get(
f"https://archive.org/download/{escaped_item_id}/{escaped_item_id}_jp2.zip"
)
zip_resp.raise_for_status()
if verbose:
print("Decompressing...", file=stderr)
stderr.flush()
tasks = []
with ZipFile(BytesIO(zip_resp.content)) as jp_zip:
for leaf_num, file_name in enumerate(sorted(jp_zip.namelist())):
for page_index, page_num_info in enumerate(page_nums):
if page_num_info["leafNum"] == leaf_num:
# Stop iterating and keep page_index set to the current item.
break
else:
# Set to -1 to indicate that leaf was not found in page_num list.
page_index = -1
if page_index != -1:
with jp_zip.open(file_name) as jp_file:
im = Image.open(jp_file).convert("L")
im.thumbnail((3200, 3200))
tasks.append(
PageAnalysisTask(
im=im,
ocr_langs=ocr_langs,
)
)
if verbose:
print(f"Processing {len(page_nums)} pages...", file=stderr)
stderr.flush()
print(f"Processing {len(tasks)} pages...", file=stdout)
stdout.flush()
if parallel > 1:
# Parallelize image processing and OCR of pages across up to n cores.

94
main.py
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@ -8,14 +8,28 @@ from time import sleep
import requests
from engine import analyze_item
from archive_item import fetch_item
from engine import analyze_doc
def main():
parser = ArgumentParser()
parser.add_argument("--database", default="./microqa.db")
parser.add_argument("--cpus", type=int, default=2)
parser.add_argument("--earliest-review-date", default="20250701")
parser.add_argument(
"--database",
help="path to sqlite database for analysis output",
default="./microqa.db",
)
parser.add_argument(
"--cpus",
type=int,
help="number of concurrent subprocesses to use; higher is generally faster but consumes more resources",
default=2,
)
parser.add_argument(
"--earliest-review-date",
help="script will attempt to analyze all items with a review date greater than or equal to this value (YYYYMMDD)",
default="20250701",
)
args = parser.parse_args()
with sqlite3.connect(args.database) as conn:
@ -28,9 +42,14 @@ create table if not exists items (
analyzed_date text
)""")
cur.execute("""
create table if not exists docs (
name text primary key not null,
item text not null
)""")
cur.execute("""
create table if not exists pages (
id int primary key,
item text not null,
doc text not null,
page int not null,
orientation_match boolean not null,
sharpness real not null,
@ -41,9 +60,10 @@ create table if not exists pages (
cur.execute(
"create index if not exists analyzed_date_idx on items (analyzed_date)"
)
cur.execute("create index if not exists item_idx on pages (item)")
cur.execute("create index if not exists item_idx on docs (item)")
cur.execute("create index if not exists doc_idx on pages (doc)")
cur.execute(
"create unique index if not exists item_page_idx on pages (item, page)"
"create unique index if not exists doc_page_idx on pages (doc, page)"
)
conn.commit()
@ -63,29 +83,33 @@ order by review_date
for _ in range(N_ATTEMPTS):
try:
print(f"Processing {item_id}")
analysis = analyze_item(
item_id, parallel=args.cpus, verbose=True
item = fetch_item(item_id)
minimal_docs = (
[doc for doc in item.docs if doc.name != ""]
if len(item.docs) > 1
else item.docs
)
for doc in minimal_docs:
cur.execute(
"insert into docs (name, item) values (?, ?) on conflict do nothing",
[doc.name, item_id],
)
analysis = analyze_doc(
doc, parallel=args.cpus, verbose=True
)
for i, page in enumerate(analysis["pages"]):
cur.execute(
"""
insert into pages (
item,
doc,
page,
orientation_match,
sharpness,
is_blank,
text_margin_px
) values (
?,
?,
?,
?,
?,
?
)""",
) values (?, ?, ?, ?, ?, ?)""",
[
item_id,
doc.name,
i + 1,
page["ocr_orientation_match"],
page["sharpness"],
@ -126,35 +150,9 @@ def pull_new_item_ids(conn, earliest_review_date):
query = re.sub(r"\s+", "+", query.strip())
sort = re.sub(r"\s+", "+", sort.strip())
# params = {
# "q": query,
# "count": 100,
# "fields": "identifier,review_date",
# "sorts": sort,
# }
# for i in range(1, 999):
# resp = requests.get(
# "https://archive.org/services/search/v1/scrape",
# params=params,
# )
# resp.raise_for_status()
# print(resp.text)
# try:
# body = resp.json()
# except Exception as err:
# print("Body:", resp.text, file=stderr)
# raise err
# for doc in body["items"]:
# cur.execute(
# "insert into items (id, review_date, skip_analysis) values (?, ?, false) on conflict do nothing",
# (doc["identifier"], doc["review_date"]),
# )
# conn.commit()
# cursor = body.get("cursor", None)
# if cursor is None:
# break
# params = params.copy()
# params["cursor"] = cursor
# Archive.org has a paginated scraping API, but the query feature seems to
# be broken in mysterious ways and more or less impossible to use for our
# purposes.
resp = requests.get(
f"https://archive.org/advancedsearch.php?q={query}&sort[]={sort}&fl[]=identifier&fl[]=review_date&rows=250000&output=json",
)