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build_draft_stats, total_original_post_notes_by_qtr_and_year, other minor improvements

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Amber McCloughan
2026-04-04 02:02:24 -04:00
parent d4e6df7721
commit a2d49785be
4 changed files with 102 additions and 28 deletions
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4
.gitignore vendored
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@@ -4,3 +4,7 @@ __pycache__/
.pytest_cache/
.ruff_cache/
.pdm-python
# Data files
*.json
*.csv

12
build_draft_stats_model.py Normal file
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@@ -0,0 +1,12 @@
from dataclasses import dataclass
from stats_model import StatsModel
@dataclass(kw_only=True)
class BuildDraftStatsModel(StatsModel):
"""Stats model built around calculating stats from your currently drafted posts"""
operation: str = 'build_draft_stats'
def __post_init__(self):
super().__post_init__()
self.most_popular_tags = self.determine_most_popular_tags('post_count')

36
stats_model.py
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@@ -33,7 +33,11 @@ class StatsModel:
total_original_post_notes: int = field(init=False)
# Total notes for original posts within each month and year.
total_original_post_notes_by_month_and_year: Dict[str, int] = field(
total_original_post_notes_by_month_and_year: Dict[str, Any] = field(
init=False)
# Total notes for original posts within each quarter and year.
total_original_post_notes_by_qtr_and_year: Dict[str, Any] = field(
init=False)
# Tags ranked from most popular to least popular by notes.
@@ -44,6 +48,7 @@ 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.total_original_post_notes_by_qtr_and_year = self.calculate_total_original_post_notes_by_qtr_and_year()
self.most_popular_tags = self.determine_most_popular_tags('note_count')
def calculate_total_posts(self) -> int:
@@ -58,7 +63,7 @@ class StatsModel:
total += self.original_post_map[post_key]['note_count']
return total
def calculate_total_original_post_notes_by_month_and_year(self) -> Dict[str, int]:
def calculate_total_original_post_notes_by_month_and_year(self) -> Dict[str, Any]:
# https://docs.python.org/3/library/collections.html#defaultdict-objects
date_map: Dict[str, Any] = {}
date_map = defaultdict(lambda: {'note_count': 0,
@@ -113,3 +118,30 @@ class StatsModel:
# https://stackoverflow.com/a/73050
return sorted(list(tag_dict.values()), key=itemgetter(sort_key),
reverse=True)
def calculate_total_original_post_notes_by_qtr_and_year(self) -> Dict[str, Any]:
total_original_post_notes_by_month_and_year: Dict[str, int] = self.total_original_post_notes_by_month_and_year
if not total_original_post_notes_by_month_and_year:
total_original_post_notes_by_month_and_year = self.calculate_total_original_post_notes_by_month_and_year()
self.total_original_post_notes_by_month_and_year = total_original_post_notes_by_month_and_year.copy()
quarter_map: Dict[str, Any] = {}
quarter_map = defaultdict(lambda: {'note_count': 0,
'post_count': 0},
quarter_map)
for key in total_original_post_notes_by_month_and_year:
month_ent = total_original_post_notes_by_month_and_year[key]
month_year: datetime = datetime.strptime(key, '%Y-%m')
qtr = (month_year.month + 2) // 3
new_key = f"{month_year.year}q{qtr}"
quarter_map[new_key]['note_count'] += month_ent['note_count']
quarter_map[new_key]['post_count'] += month_ent['post_count']
# Results postprocessing.
for quarter in quarter_map:
sts = quarter_map[quarter]
post_count = sts['post_count']
note_count = sts['note_count']
sts['notes_to_posts_ratio'] = note_count / post_count
return quarter_map

78
tumblr_stats.py
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@@ -11,6 +11,7 @@ from typing import Any, Callable, Dict, List, Tuple
import pytumblr
from build_draft_stats_model import BuildDraftStatsModel
from build_tag_stats_model import BuildTagStatsModel
from build_total_stats_model import BuildTotalStatsModel
from build_queue_stats_model import BuildQueueStatsModel
@@ -25,7 +26,7 @@ def get_args() -> Dict[str, Any]:
+ '$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', 'build_queue_stats'],
choices=['build_tag_stats', 'build_queue_stats', 'build_draft_stats'],
help="operation used to calculate stats")
parser.add_argument('-b', '--blog', type=str, required=True,
help='blog name for which to calculate stats')
@@ -76,7 +77,6 @@ def filter_posts_for_after(post_list: List[Dict[str, Any]],
x['date'], '%Y-%m-%d %H:%M:%S %Z') > after
return [post for post in post_list if after_check(post)]
def build_post_maps(client: pytumblr.TumblrRestClient,
args: Dict[str, Any]) -> Tuple[Dict[str, Any], Dict[str, Any]]:
og_post_map: Dict[str, Any] = {}
@@ -92,6 +92,9 @@ def build_post_maps(client: pytumblr.TumblrRestClient,
# before: datetime = args['before']
# params.update({'before': int(before.timestamp())})
draft_url = f"/v2/blog/{blog_name}/posts/draft"
is_draft_stats: bool = 'build_draft_stats' in args['operation']
total: int = 0
offset: int = 0
limit: int = 20
@@ -101,12 +104,14 @@ def build_post_maps(client: pytumblr.TumblrRestClient,
# Begin LOOP
# Get me some posts via REST! 😈🍪🍪🍪
data: Dict[str, Any]
if 'build_queue_stats' in args['operation'] and len(args['operation']) == 1:
if 'build_queue_stats' in args['operation']:
data = client.queue(f"{blog_name}.tumblr.com",
offset=offset,
limit=limit,
**params)
else: # Above is for queued posts, below is for published posts.
elif is_draft_stats:
data = client.send_api_request("get", draft_url)
else: # Above is for queued + draft posts, below is for published posts.
data = client.posts(f"{blog_name}.tumblr.com",
offset=offset,
limit=limit,
@@ -119,7 +124,7 @@ def build_post_maps(client: pytumblr.TumblrRestClient,
break
next_off: int = 0
if '_links' in data:
if '_links' in data and not is_draft_stats:
links = data['_links']
if 'next' in links and 'query_params' in links['next']:
next_off = int(links['next']['query_params']['offset'])
@@ -135,7 +140,7 @@ def build_post_maps(client: pytumblr.TumblrRestClient,
after: datetime = args['after']
curr_posts = filter_posts_for_after(curr_posts, after)
if not curr_posts:
print(f"All posts after {after.year}-{after.month} processed.")
print(f"All posts after {after.year}-{after.month}-{after.day} processed.")
return (og_post_map, un_og_post_map)
# This block populates the local post_maps from the raw response data.
@@ -150,6 +155,15 @@ 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)
# For build_draft_stats.
if is_draft_stats:
if '_links' in data:
draft_url = data['_links']['next']['href']
continue
else:
print('All draft posts processed.')
break
# The increment and status printing.
if next_off != 0 and next_off != offset:
offset = next_off
@@ -167,6 +181,13 @@ def build_post_maps(client: pytumblr.TumblrRestClient,
def main() -> None:
args: Dict[str, Any] = get_args()
client: pytumblr.TumblrRestClient = init_client()
operation: List[str] = args['operation']
# Quick bail for bad use of build_queue_stats and build_draft_stats.
if (set(operation) & set(['build_queue_stats', 'build_draft_stats'])) and len(operation) > 1:
print(f"You can't mix operations {operation} together. Sorry.")
sys.exit(1)
pass
# Handle JSON input (if you don't want to make API calls.)
if 'input' in args and args['input']:
@@ -193,28 +214,33 @@ 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.')
match args:
case {'operation': ['build_queue_stats']}:
stats_model = BuildQueueStatsModel(blog_name=args['blog'],
original_post_map=og_post_map,
unoriginal_post_map=un_og_post_map)
case {'operation': ['build_draft_stats']}:
stats_model = BuildDraftStatsModel(blog_name=args['blog'],
original_post_map=og_post_map,
unoriginal_post_map=un_og_post_map)
case {'operation': op} if 'build_tag_stats' in operation:
stats_model = BuildTagStatsModel(blog_name=args['blog'],
original_post_map=og_post_map,
unoriginal_post_map=un_og_post_map)
stats_model.tags = args['tags']
case {'operation': op} if 'build_total_stats' in operation:
if 'before' not in args: # or 'after' not in args:
print(f"You must specify a time range for {op}. " +
'You\'ll otherwise request TOO MUCH DATA!')
sys.exit(1)
stats_model = BuildTotalStatsModel(blog_name=args['blog'],
original_post_map=og_post_map,
unoriginal_post_map=un_og_post_map)
case _:
print('Unsupported command. How did you even make it this far?!')
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,
unoriginal_post_map=un_og_post_map)
stats_model.tags = args['tags']
if 'build_total_stats' in args['operation']:
if 'before' not in args: # or 'after' not in args:
print('You must specify a time range for build_total stats. ' +
'You\'ll otherwise request TOO MUCH DATA!')
sys.exit(1)
stats_model = BuildTotalStatsModel(blog_name=args['blog'],
original_post_map=og_post_map,
unoriginal_post_map=un_og_post_map)
# Write the chosen model as JSON output.
# Write the selected model as JSON output.
with open('./tumblr_stats.json', 'w') as f:
json.dump(asdict(stats_model), f, indent=1, default=str)