forked from mirrors/bookwyrm
204 lines
7 KiB
Python
204 lines
7 KiB
Python
""" handle reading a csv from an external service, defaults are from Goodreads """
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import csv
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import logging
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from django.utils import timezone
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from django.utils.translation import gettext_lazy as _
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from bookwyrm import models
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from bookwyrm.models import ImportJob, ImportItem
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from bookwyrm.tasks import app, LOW
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logger = logging.getLogger(__name__)
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class Importer:
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"""Generic class for csv data import from an outside service"""
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service = "Unknown"
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delimiter = ","
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encoding = "UTF-8"
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# these are from Goodreads
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row_mappings_guesses = {
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"id": ["id", "book id"],
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"title": ["title"],
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"authors": ["author", "authors", "primary author"],
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"isbn_13": ["isbn13", "isbn"],
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"isbn_10": ["isbn10", "isbn"],
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"shelf": ["shelf", "exclusive shelf", "read status"],
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"review_name": ["review name"],
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"review_body": ["my review", "review"],
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"rating": ["my rating", "rating", "star rating"],
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"date_added": ["date added", "entry date", "added"],
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"date_started": ["date started", "started"],
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"date_finished": ["date finished", "last date read", "date read", "finished"],
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}
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date_fields = ["date_added", "date_started", "date_finished"]
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shelf_mapping_guesses = {
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"to-read": ["to-read"],
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"read": ["read"],
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"reading": ["currently-reading", "reading"],
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}
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def create_job(self, user, csv_file, include_reviews, privacy):
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"""check over a csv and creates a database entry for the job"""
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csv_reader = csv.DictReader(csv_file, delimiter=self.delimiter)
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rows = enumerate(list(csv_reader))
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job = ImportJob.objects.create(
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user=user,
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include_reviews=include_reviews,
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privacy=privacy,
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mappings=self.create_row_mappings(csv_reader.fieldnames),
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)
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for index, entry in rows:
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self.create_item(job, index, entry)
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return job
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def create_row_mappings(self, headers):
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"""guess what the headers mean"""
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mappings = {}
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for (key, guesses) in self.row_mappings_guesses.items():
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value = [h for h in headers if h.lower() in guesses]
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value = value[0] if len(value) else None
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if value:
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headers.remove(value)
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mappings[key] = value
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return mappings
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def create_item(self, job, index, data):
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"""creates and saves an import item"""
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normalized = self.normalize_row(data, job.mappings)
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normalized["shelf"] = self.get_shelf(normalized)
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ImportItem(job=job, index=index, data=data, normalized_data=normalized).save()
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def get_shelf(self, normalized_row):
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"""determine which shelf to use"""
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shelf_name = normalized_row["shelf"]
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shelf = [
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s for (s, gs) in self.shelf_mapping_guesses.items() if shelf_name in gs
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]
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return shelf[0] if shelf else None
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def normalize_row(self, entry, mappings): # pylint: disable=no-self-use
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"""use the dataclass to create the formatted row of data"""
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return {k: entry.get(v) for k, v in mappings.items()}
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def create_retry_job(self, user, original_job, items):
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"""retry items that didn't import"""
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job = ImportJob.objects.create(
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user=user,
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include_reviews=original_job.include_reviews,
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privacy=original_job.privacy,
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# TODO: allow users to adjust mappings
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mappings=original_job.mappings,
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retry=True,
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)
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for item in items:
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# this will re-normalize the raw data
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self.create_item(job, item.index, item.data)
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return job
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def start_import(self, job):
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"""initalizes a csv import job"""
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result = start_import_task.delay(self.service, job.id)
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job.task_id = result.id
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job.save()
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@app.task(queue="low_priority")
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def start_import_task(source, job_id):
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"""trigger the child tasks for each row"""
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job = ImportJob.objects.get(id=job_id)
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# these are sub-tasks so that one big task doesn't use up all the memory in celery
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for item in job.items.values_list("id", flat=True).all():
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import_item_task.delay(source, item)
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@app.task(queue="low_priority")
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def import_item_task(source, item_id):
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"""resolve a row into a book"""
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item = models.ImportItem.objects.get(id=item_id)
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try:
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item.resolve()
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except Exception as err: # pylint: disable=broad-except
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item.fail_reason = _("Error loading book")
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item.save()
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raise err
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if item.book:
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job = item.job
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# shelves book and handles reviews
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handle_imported_book(source, job.user, item, job.include_reviews, job.privacy)
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else:
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item.fail_reason = _("Could not find a match for book")
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item.save()
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def handle_imported_book(source, user, item, include_reviews, privacy):
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"""process a csv and then post about it"""
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if isinstance(item.book, models.Work):
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item.book = item.book.default_edition
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if not item.book:
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return
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existing_shelf = models.ShelfBook.objects.filter(book=item.book, user=user).exists()
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# shelve the book if it hasn't been shelved already
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if item.shelf and not existing_shelf:
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desired_shelf = models.Shelf.objects.get(identifier=item.shelf, user=user)
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shelved_date = item.date_added or timezone.now()
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models.ShelfBook(
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book=item.book, shelf=desired_shelf, user=user, shelved_date=shelved_date
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).save(priority=LOW)
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for read in item.reads:
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# check for an existing readthrough with the same dates
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if models.ReadThrough.objects.filter(
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user=user,
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book=item.book,
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start_date=read.start_date,
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finish_date=read.finish_date,
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).exists():
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continue
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read.book = item.book
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read.user = user
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read.save()
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if include_reviews and (item.rating or item.review):
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# we don't know the publication date of the review,
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# but "now" is a bad guess
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published_date_guess = item.date_read or item.date_added
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if item.review:
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# pylint: disable=consider-using-f-string
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review_title = (
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"Review of {!r} on {!r}".format(
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item.book.title,
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source,
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)
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if item.review
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else ""
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)
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review = models.Review(
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user=user,
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book=item.book,
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name=review_title,
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content=item.review,
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rating=item.rating,
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published_date=published_date_guess,
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privacy=privacy,
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)
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else:
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# just a rating
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review = models.ReviewRating(
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user=user,
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book=item.book,
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rating=item.rating,
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published_date=published_date_guess,
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privacy=privacy,
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)
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# only broadcast this review to other bookwyrm instances
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review.save(software="bookwyrm", priority=LOW)
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