Added a more structured model, some basic stats, ranked post list for a tag
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620f3d2975
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94
app.py
94
app.py
@ -1,11 +1,15 @@
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from dataclasses import asdict
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import json
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from operator import itemgetter
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import os
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import sys
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from typing import Any, Dict
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from typing import Any, Dict, List, Tuple
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import pytumblr
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from model import StatsModel
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def init_client() -> pytumblr.TumblrRestClient:
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consumer_key = os.getenv('TUMBLR_CONSUMER_KEY')
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@ -18,33 +22,44 @@ def init_client() -> pytumblr.TumblrRestClient:
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('$TUMBLR_CONSUMER_SECRET', consumer_secret),
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('$TUMBLR_OAUTH_TOKEN', oauth_token),
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('$TUMBLR_OAUTH_SECRET', oauth_secret)] if val is None]
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if missing_vars:
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print("Missing important environment variables:", missing_vars)
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sys.exit(1)
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return pytumblr.TumblrRestClient(
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consumer_key=consumer_key, # type: ignore
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consumer_secret=consumer_secret, # type: ignore
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oauth_token=oauth_token, # type: ignore
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oauth_secret=oauth_secret, # type: ignore
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consumer_key=consumer_key, # type: ignore
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consumer_secret=consumer_secret, # type: ignore
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oauth_token=oauth_token, # type: ignore
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oauth_secret=oauth_secret, # type: ignore
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)
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def main() -> None:
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client = init_client()
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def calculate_total_notes(post_map: Dict[str, Any]) -> int:
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total = 0
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for post_key in post_map:
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total += post_map[post_key]['note_count']
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return total
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def determine_top_post_urls(post_map: Dict[str, Any]) -> List[str]:
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post_list = sorted(list(post_map.values()), key=itemgetter('note_count'), reverse=True)
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return [post['post_url'] for post in post_list]
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def build_post_map_and_dumpster(client: pytumblr.TumblrRestClient, blog_name: str, tag: str) -> Tuple[Dict[str, Any], Dict[str, Any]]:
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post_map: Dict[str, Any] = {}
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dumpster: Dict[str, Any] = {}
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total = 0
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offset = 0
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limit = 20
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while offset <= total:
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# Begin LOOP
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### Begin LOOP
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# Get me some posts! 😈🍪🍪🍪
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data = client.posts('panda-pal.tumblr.com', **{'tag': 'inuyasha'}, \
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offset = offset, \
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limit = limit)
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data = client.posts(f"{blog_name}.tumblr.com", **{'tag': tag},
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offset=offset,
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limit=limit)
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# Total check for the first iteration, but always checked for sanity.
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if total == 0:
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# Let's see what's in there,
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@ -54,11 +69,11 @@ def main() -> None:
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if not total_posts:
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print("Couldn't get total posts. We're outta here!")
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sys.exit(1)
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# Something was there, so we're good.
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print(f"I'm working with {total_posts} total posts...")
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total = total_posts
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curr_posts = data['posts']
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local_post_map: Dict[str, Any] = {}
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for curr_post in curr_posts:
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@ -78,28 +93,43 @@ def main() -> None:
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if any(post not in post_map for post in filtered_local_post_map):
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post_map.update(filtered_local_post_map)
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# The increment. Should always end the loop!
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# The increment and status printing. Should always end the loop!
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offset += limit
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if offset <= total:
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print(f"Processed batch {(offset // limit) - 1} of {total // 20}...")
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if offset < total:
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print(f"Processed batch {offset // limit} of {total // 20}...")
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else:
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print(f"Processed final batch of {total} posts")
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# End LOOP
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if not post_map and not dumpster:
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print('We found nothing, so we end with nothing. 🤷')
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sys.exit(1)
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else:
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with open("./tumblr_data.json", "w") as f:
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json.dump(post_map, f, indent=2, sort_keys=True)
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with open("./tumblr_dumpster.json", "w") as f:
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json.dump(dumpster, f, indent=2, sort_keys=True)
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return
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print(f"Processed all {total} posts")
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### End LOOP
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return (post_map, dumpster)
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def retrieve_all_posts(tag: str):
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def build_tag_stats_model(client: pytumblr.TumblrRestClient, blog_name: str, tag: str) -> StatsModel:
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post_map, dumpster = build_post_map_and_dumpster(client, blog_name, tag)
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stats_model: StatsModel = StatsModel()
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stats_model.operation = 'build_tag_stats'
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stats_model.blog_name = blog_name
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stats_model.post_map = post_map
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stats_model.dumpster = dumpster
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stats_model.total_posts = len(post_map) + len(dumpster)
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stats_model.total_original_posts = len(post_map)
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stats_model.total_original_post_notes = calculate_total_notes(post_map)
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stats_model.ranked_post_urls = determine_top_post_urls(post_map)
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return stats_model
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def main() -> None:
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client = init_client()
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stats_model = build_tag_stats_model(client, 'panda-pal', 'inuyasha')
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with open("./tumblr_data.json", "w") as f:
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json.dump(asdict(stats_model), f, indent=2, sort_keys=True)
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return
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if __name__ == '__main__':
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main()
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sys.exit(0)
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sys.exit(0)
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33
model.py
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33
model.py
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@ -0,0 +1,33 @@
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from dataclasses import dataclass, field
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from typing import Any, Dict, List
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@dataclass
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class StatsModel:
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"""Class that models the output of the Tumblr stats script."""
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# Operation used to output stats.
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operation: str = field(default_factory=str)
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# Blog in question.
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blog_name: str = field(default_factory=str)
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# Tags used.
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tags: List[str] = field(default_factory=list)
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# Original posts.
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post_map: Dict[str, Any] = field(default_factory=dict)
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# Posts that are not original.
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dumpster: Dict[str, Any] = field(default_factory=dict)
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# Total posts handled.
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total_posts: int = field(default_factory=int)
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# Total original posts (per blog_name) handled.
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total_original_posts: int = field(default_factory=int)
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# Total original post (per blog_name) notes handled
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total_original_post_notes: int = field(default_factory=int)
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# Posts ranked from most popular to least popular.
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ranked_post_urls: List[str] = field(default_factory=list)
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