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#!/usr/bin/env python3
"""
Reads a sqlite3 manifest database (IA 2017 style) and outputs a stream of
"match" JSON objects which can be imported into fatcat with matched_import.py
This was used to convert this manifest:
https://archive.org/details/ia_papers_manifest_2018-01-25/
to JSON format for fast fatcat importing.
"""
import sys
import json
import sqlite3
# iterate over rows in files metadata...
# 1. select all identified DOIs
# => filter based on count
# 2. select all file metadata
# 3. output object
def or_none(s):
if s is None:
return None
elif type(s) == str and ((not s) or s == "\\N" or s == "-"):
return None
return s
def process_db(db_path):
db = sqlite3.connect(db_path)
for row in db.execute("SELECT sha1, mimetype, size_bytes, md5 FROM files_metadata"):
sha1 = row[0]
dois = db.execute("SELECT doi FROM files_id_doi WHERE sha1=?", [sha1]).fetchall()
dois = [d[0] for d in dois]
if not dois:
continue
urls = db.execute("SELECT url, datetime FROM urls WHERE sha1=?", [sha1]).fetchall()
if not urls:
continue
cdx = [dict(url=row[0], dt=row[1]) for row in urls]
obj = dict(
sha1=sha1,
mimetype=or_none(row[1]),
size=(or_none(row[2]) and int(row[2])),
md5=or_none(row[3]),
dois=dois,
cdx=cdx,
)
dois = db.execute("SELECT doi FROM files_id_doi WHERE sha1=?", [sha1])
print(json.dumps(obj))
if __name__=="__main__":
process_db(sys.argv[1])
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