"""
**generate_textcorpus** is a custom manage command to generate a plain
text corpus from Solr. It should be run *after* content has been indexed
into Solr via the **index** manage command.
The full text corpus is generated from Solr; it does not include content
for suppressed works or their pages (note that this depends on Solr
content being current).
Examples:
- Expected use:
python manage.py generate_textcorpus
- Specify a path:
python manage.py generate_textcorpus --path ~/ppa_solr_corpus
- Dry run (do not create any files or folders):
python manage.py generate_textcorpus --dry-run
- Partial run (save only N rows, for testing):
python manage.py generate_textcorpus --doc-limit 100
- Cron-style run (no progress bar, but logs)
python manage.py generate_textcorpus --no-progress --verbosity 2
Notes:
- Default path is `ppa_corpus_{timestamp}` in the current working directory
- Default batch size is 10,000, meaning 10,000 records are pulled
from solr at a time. Usage testing revealed that this default
iterates over the collection the quickest.
"""
import argparse
import os
from datetime import datetime
import json
import csv
from django.core.management.base import BaseCommand, CommandError
from parasolr.django import SolrQuerySet
from progressbar import progressbar
import orjsonl
DEFAULT_BATCH_SIZE = 10000
TIMESTAMP_FMT = "%Y-%m-%d_%H%M"
[docs]
class Command(BaseCommand):
"""
Custom manage command to generate a text corpus from text indexed in Solr.
"""
#: normal verbosity level
v_normal = 1
verbosity = v_normal
# fields to return from Solr; output_name: solr_field_name
FIELDLIST = {
"page": {
"id": "id",
"work_id": "group_id_s",
"order": "order",
"label": "label",
"tags": "tags",
"text": "content",
},
"work": {
"work_id": "group_id_s",
"source_id": "source_id",
"cluster_id": "cluster_id_s",
"title": "title",
"author": "author_exact",
"pub_year": "pub_date",
"publisher": "publisher",
"pub_place": "pub_place",
"collections": "collections_exact",
"work_type": "work_type_s",
"source": "source_t",
"source_url": "source_url",
"sort_title": "sort_title",
"subtitle": "subtitle",
},
}
# Argument parsing
[docs]
def add_arguments(self, parser):
"""
Configure additional CLI arguments
"""
# add --path argument for output
parser.add_argument(
"--path",
help="Directory path to save corpus file(s). "
"Defaults to ./ppa_corpus_{timestamp}",
default=None,
)
# add --doc-limit argument (determines how many results to retrieve from solr)
parser.add_argument(
"--doc-limit",
type=int,
default=None,
help="Limit the number of documents for corpus generation. "
"By default, includes ALL documents.",
)
# add --batch-size argument (for solr querying)
parser.add_argument(
"--batch-size",
type=int,
default=DEFAULT_BATCH_SIZE,
help="Number of docs to query from solr at one time",
)
# control compression of pages jsonl output (enabled by default)
parser.add_argument(
"--gzip",
help="Save pages as compressed or uncompressed "
"(ppa_pages.jsonl or ppa_pages.jsonl.gz) [default: %(default)s]",
action=argparse.BooleanOptionalAction,
default=True,
)
# add --dry-run argument (don't save anything, just iterate)
parser.add_argument(
"--dry-run",
action="store_true",
help="Do not save anything, just iterate over solr",
)
# control progress bar display (on by default)
parser.add_argument(
"--progress",
help="Show progress",
action=argparse.BooleanOptionalAction,
default=True,
)
#### SOLR ####
[docs]
def iter_solr(self, item_type="page"):
"""
Returns a generator Solr documents for the requested `item_type`
(page or work).
"""
# filter to the requested item type, order by id,
# and return the configured set of fields
qset = (
self.query_set.filter(item_type=item_type)
.order_by("id")
.only(**self.FIELDLIST[item_type])
)
# get the total count for this query
total = qset.count()
if not total:
raise CommandError(f"No {item_type} records found in Solr.")
# if a doc limit is requested, decrease the total to pull from Solr
if self.doclimit:
total = min(total, self.doclimit)
# define a generator to iterate solr with
batch_iterator = (
result
for step in range(0, total, self.batch_size)
for result in qset[
step : (step + self.batch_size)
if (step + self.batch_size) < total
else total
]
)
# if progress bar is enabled, wrap the generator
if self.progress:
batch_iterator = progressbar(
batch_iterator, max_value=total, prefix=f"Exporting {item_type}s: "
)
# yield from this generator
yield from batch_iterator
[docs]
def iter_works(self):
"""
Yield results from :meth:`iter_solr` with `item_type=work`
"""
yield from self.iter_solr(item_type="work")
# save pages
[docs]
def iter_pages(self):
"""
Yield results from :meth:`iter_solr` with `item_type=page`
"""
yield from self.iter_solr(item_type="page")
### saving to file
[docs]
def save_pages(self):
"""
Save the page-level data as a jsonl file
"""
### save pages
if self.is_dry_run:
# consume the generator
list(self.iter_pages())
else:
# save to jsonl or jsonl.gz
orjsonl.save(self.path_pages_json, self.iter_pages())
### running script
[docs]
def set_params(self, *args, **options):
"""
Run the command, generating metadata.jsonl and pages.jsonl
"""
# options
self.path = options.get("path")
if not self.path:
self.path = os.path.join(f"ppa_corpus_{nowstr()}")
self.path_works_json = os.path.join(self.path, "ppa_metadata.json")
self.path_works_csv = os.path.join(self.path, "ppa_metadata.csv")
jsonl_ext = "jsonl.gz" if options.get("gzip") else "jsonl"
self.path_pages_json = os.path.join(self.path, f"ppa_pages.{jsonl_ext}")
self.is_dry_run = options.get("dry_run")
self.doclimit = options.get("doc_limit")
self.verbosity = options.get("verbosity", self.verbosity)
self.progress = options.get("progress")
self.batch_size = options.get("batch_size", DEFAULT_BATCH_SIZE)
self.query_set = SolrQuerySet()
[docs]
def handle(self, *args, **options):
self.set_params(*args, **options)
# ensure output path exists
if not self.is_dry_run:
if self.verbosity >= self.v_normal:
print(f"Saving files in {self.path}")
os.makedirs(self.path, exist_ok=True)
# save metadata
self.save_metadata()
# save pages
self.save_pages()
# helper func
[docs]
def nowstr():
"""helper method to generate timestamp for use in output filename"""
return datetime.now().strftime(TIMESTAMP_FMT)
