Added operation for calculating stats on queued posts, improved loop handling

This commit is contained in:
Amber McCloughan 2026-01-03 23:08:01 -05:00
parent 590277d7ee
commit d4e6df7721
3 changed files with 86 additions and 16 deletions

View File

@ -0,0 +1,47 @@
from dataclasses import dataclass, field
from datetime import datetime
from operator import itemgetter
from typing import Any, Dict, List
from stats_model import StatsModel
@dataclass(kw_only=True)
class BuildQueueStatsModel(StatsModel):
"""Stats model built around calculating stats from your currently queued posts"""
operation: str = 'build_queue_stats'
# Queued posts (both original and not original), sorted in publish order.
ordered_queue: List[Dict[str, Any]] = field(init=False)
def __post_init__(self):
super().__post_init__()
self.most_popular_tags = self.determine_most_popular_tags('post_count')
self.ordered_queue = self.determine_ordered_queue()
def determine_ordered_queue(self) -> List[Dict[str, Any]]:
full_post_map = self.original_post_map | self.unoriginal_post_map
post_list: List[Dict[str, Any]] = []
for post_key in full_post_map:
post = full_post_map[post_key]
if 'scheduled_publish_time' not in post or not post['scheduled_publish_time']:
print('WARNING: Queued post found without publish time. Huh?')
queued_date_time: datetime = datetime.fromtimestamp(
post['scheduled_publish_time'])
post_list.append({
'post_url': post['post_url'],
'tags': post['tags'],
'publish_date_time': queued_date_time
})
# https://stackoverflow.com/a/73050
sorted_list = sorted(post_list, key=itemgetter('publish_date_time'))
# https://stackoverflow.com/a/522578
for i, post in enumerate(sorted_list):
post['queue_order'] = i + 1
return sorted_list

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@ -44,7 +44,7 @@ class StatsModel:
self.total_original_posts = self.calculate_total_original_posts()
self.total_original_post_notes = self.calculate_total_original_post_notes()
self.total_original_post_notes_by_month_and_year = self.calculate_total_original_post_notes_by_month_and_year()
self.most_popular_tags = self.determine_most_popular_tags()
self.most_popular_tags = self.determine_most_popular_tags('note_count')
def calculate_total_posts(self) -> int:
return len(self.original_post_map) + len(self.unoriginal_post_map)
@ -86,7 +86,7 @@ class StatsModel:
return date_map
def determine_most_popular_tags(self) -> List[Dict[str, Any]]:
def determine_most_popular_tags(self, sort_key: str) -> List[Dict[str, Any]]:
# https://docs.python.org/3/library/collections.html#defaultdict-objects
tag_dict: Dict[str, Any] = {}
tag_dict = defaultdict(lambda: {'note_count': 0,
@ -111,5 +111,5 @@ class StatsModel:
sts['notes_to_posts_ratio'] = note_count / post_count
# https://stackoverflow.com/a/73050
return sorted(list(tag_dict.values()), key=itemgetter('note_count'),
return sorted(list(tag_dict.values()), key=itemgetter(sort_key),
reverse=True)

View File

@ -13,6 +13,7 @@ import pytumblr
from build_tag_stats_model import BuildTagStatsModel
from build_total_stats_model import BuildTotalStatsModel
from build_queue_stats_model import BuildQueueStatsModel
from stats_model import StatsModel
@ -23,8 +24,8 @@ def get_args() -> Dict[str, Any]:
description='Use pytumblr to calculate stats after setting these enviroment variables: '
+ '$TUMBLR_CONSUMER_KEY, $TUMBLR_CONSUMER_SECRET, $TUMBLR_OAUTH_TOKEN, and $TUMBLR_OAUTH_SECRET',
epilog='— Be gay and do crime')
parser.add_argument('operation', type=str, nargs='+',
metavar='OPERATION', choices=['build_tag_stats'],
parser.add_argument('operation', type=str, nargs='+', metavar='OPERATION',
choices=['build_tag_stats', 'build_queue_stats'],
help="operation used to calculate stats")
parser.add_argument('-b', '--blog', type=str, required=True,
help='blog name for which to calculate stats')
@ -96,23 +97,35 @@ def build_post_maps(client: pytumblr.TumblrRestClient,
limit: int = 20
# The request loop that pulls all data from the APIs.
while offset <= total:
while True:
# Begin LOOP
# Get me some posts via REST! 😈🍪🍪🍪
data = client.posts(f"{blog_name}.tumblr.com",
offset=offset,
limit=limit,
**params)
data: Dict[str, Any]
if 'build_queue_stats' in args['operation'] and len(args['operation']) == 1:
data = client.queue(f"{blog_name}.tumblr.com",
offset=offset,
limit=limit,
**params)
else: # Above is for queued posts, below is for published posts.
data = client.posts(f"{blog_name}.tumblr.com",
offset=offset,
limit=limit,
**params)
# Stop the presses if we found no posts.
curr_posts: List[Dict[str, Any]] = data['posts']
if not curr_posts or len(curr_posts) < 1:
print('Stopping, as no posts were found.')
print('Stopping, as no more posts were found.')
break
next_off: int = 0
if '_links' in data:
links = data['_links']
if 'next' in links and 'query_params' in links['next']:
next_off = int(links['next']['query_params']['offset'])
# Total init check for the first iteration, but always checked for sanity.
if not total:
# Let's see what's in there,
if not total and 'total_posts' in data:
total_posts = data['total_posts']
print(f"I'm working with {total_posts} total posts...")
total = total_posts
@ -137,9 +150,12 @@ def build_post_maps(client: pytumblr.TumblrRestClient,
og_post_map.update(local_og_post_map)
un_og_post_map.update(local_un_og_post_map)
# The increment and status printing. Should always end the loop!
offset += limit
if not args['after']:
# The increment and status printing.
if next_off != 0 and next_off != offset:
offset = next_off
else:
offset += limit
if not args['after'] and total:
print(
f"Processed batch {offset // limit} of {(total // 20) + 1}...")
# End LOOP
@ -177,6 +193,13 @@ def main() -> None:
# Pick a stats model, which will determine output.
stats_model: StatsModel
if 'build_queue_stats' in args['operation']:
if len(args['operation']) != 1:
print('You can\'t mix build_queue_stats with other operations. Sorry.')
sys.exit(1)
stats_model = BuildQueueStatsModel(blog_name=args['blog'],
original_post_map=og_post_map,
unoriginal_post_map=un_og_post_map)
if 'build_tag_stats' in args['operation']:
stats_model = BuildTagStatsModel(blog_name=args['blog'],
original_post_map=og_post_map,