The Lemmington Post

```python import os import re

def get_python_files(directory): python_files = [] for root, dirs, files in os.walk(directory): for file in files: if file.endswith(".py"): python_files.append(os.path.join(root, file)) return python_files

def read_file(file_path): with open(file_path, "r", encoding="utf-8") as file: contents = file.read() return contents

def write_markdown(file_paths, output_file): with open(output_file, "w", encoding="utf-8") as md_file: for file_path in file_paths: file_name = os.path.basename(file_path) md_file.write(f"{file_name}\n\n") md_file.write("python\n") md_file.write(read_file(file_path)) md_file.write("\n\n\n")

def main(): github_repo_path = input("Enter the path to the GitHub repository: ") python_files = get_python_files(github_repo_path) output_file = "merged_files.md" write_markdown(python_files, output_file) print(f"Python files merged into {output_file}")

if name == "main": main() ```

Here's how the script works:

1. The get_python_files function takes a directory path and returns a list of all Python files (files ending with .py) found in that directory and its subdirectories.
2. The read_file function reads the contents of a file and returns it as a string.
3. The write_markdown function takes a list of file paths and an output file path. It iterates over the file paths, reads the contents of each file, and writes the file name and contents to the output file in the desired markdown format.
4. The main function prompts the user to enter the path to the GitHub repository, calls the other functions, and outputs a message indicating that the Python files have been merged into the output file (merged_files.md).

To use the script, save it as a Python file (e.g., merge_python_files.py), and run it with Python. When prompted, enter the path to the GitHub repository you want to process. The script will create a merged_files.md file in the same directory containing the merged Python files in the requested format.

Note: This script assumes that the repository only contains Python files. If you want to include other file types or exclude certain files or directories, you may need to modify the get_python_files function accordingly.

Hello! I am currently on the lookout for a versatile media management platform that goes beyond the traditional boundaries of organizing just one type of media. I am in search of a platform that can handle a diverse range of media types including books, games, videos, and more.

Ideal Solution: AI-powered system that scans media files, identifies them, categorizes them, and tags them without needing manual input.

Next Best Option: Central database that supports collaborative editing of enriched metadata, including title, data, cast, genres, descriptions, etc. across diverse media types that can be exported to local management apps like Plex and Kodi.

Current Practical Option: Use specialized metadata tools by media type (Beets + MusicBrainz for music, Stash + Stash-box for adult content, Calibre for eBooks), then use an integration solution like Plex or Kodi to bring the enriched libraries together into a consolidated interface. Requires more manual effort but takes advantage of existing metadata sources.

Here are some key features I am looking for in this platform:

• Cross-media support: Ability to organize and manage various types of media including books, games, videos, and music.
• Folder scanning with "watch for changes" functionality: Automatically scan designated folders to add new media to the library whenever the folder content changes.
• Advanced search functionality: Robust search capabilities to easily locate specific media within the collection. To easily find media files based on a variety of criteria like titles, genres, people involved, dates, etc.
• Access control: Grant permissions to users for sharing and accessing specific media content.
• Federation support: Enables the integration of multiple instances of the media management platform, allowing users to access and view a consolidated library comprising content from all federated instances.
• Metadata sharing: Allow sharing metadata information across different instances of the platform for enhanced organization and categorization.
• Collaborative metadata curation: Tools for crowdsourcing and enhancing descriptions, tags, classifications. Shared libraries and collaborative editing tools allow crowdsourcing metadata improvements and corrections so the overall quality gets better over time.
• Metadata matching: Automatically associate metadata with files based on hash values for efficient curation.
• Perceptual hashes: Enhances content recognition, deduplication and metadata association by creating unique identifiers based on media content rather than exact data.
• Manual metadata matching: Enable users to manually link files with similar content but different hashes.
• Multi-instance support: Allow multiple instances of the program to be set up as endpoints.

In summary, I’m looking for the most automated cross-media metadata management platform available to eliminate manual effort. Failing an AI-powered solution, a centralized database with rich collaborative tools would be helpful, before falling back on specialized tools by media type coupled with a consolidated viewing interface via something like Plex.

If anyone is aware of a platform that encompasses some of these features or comes close to meeting these requirements, I would greatly appreciate any recommendations or insights you may have. Thank you in advance for your help!

If you're developing an application or script that interacts with Lemmy's API, particularly for posting content, it's crucial to understand and respect the platform's rate limits to avoid encountering rate_limit_errors. Lemmy, like many other online platforms, implements rate limiting to prevent abuse and ensure fair usage among all users. This guide will help you navigate Lemmy's rate limits for posting content, ensuring your application runs smoothly without hitting any snags.

Understanding Lemmy's Rate Limits

Lemmy's API provides specific rate limits for different types of requests. These limits are crucial for maintaining the platform's integrity and performance. For posts, as well as other actions like messaging, registering, uploading images, commenting, and searching, Lemmy sets distinct limits.

To find the current rate limits, you can make a GET request to /api/v3/site, which returns various parameters, including local_site_rate_limit. This parameter outlines the limits for different actions. Here's a breakdown of what these numbers mean, using the example provided:

json "local_site_rate_limit": { "post": 6, "post_per_second": 600, ... }

In this context, you're allowed to make 6 post requests every 600 seconds (which is equivalent to 10 minutes). It's important to note that this limit is not per second as the variable name might suggest, but rather for a fixed duration (600 seconds in this case).

Calculating the Delay Between Posts

Given the rate limit of 6 posts every 600 seconds, to evenly distribute your posts and avoid hitting the rate limit, you should calculate the delay between each post. The formula for this calculation is:

$$ \text{Delay between posts (in seconds)} = \frac{\text{Total period (in seconds)}}{\text{Number of allowed posts}} $$

For the given example:

$$ \text{Delay} = \frac{600}{6} = 100 \text{ seconds} $$

This means you should wait for 100 seconds after making a post before making the next one to stay within the rate limit.

Implementing the Delay in Your Program

To implement this in your program, you can use various timing functions depending on your programming language. For example, in Python, you can use time.sleep(100) to wait for 100 seconds between posts.

Best Practices

• Monitor Your Requests: Keep track of your requests to ensure you're not nearing the limit.
• Handle Errors Gracefully: Implement error handling in your code to catch rate_limit_errors and respond appropriately, possibly by waiting longer before retrying.
• Stay Updated: Rate limits can change, so it's a good idea to periodically check the limits by making a GET request to /api/v3/site.

Conclusion

Understanding and respecting rate limits is essential when interacting with Lemmy's API. By calculating the appropriate delay between your posts based on the current rate limits and implementing this delay in your program, you can avoid rate limit errors and ensure your application interacts with Lemmy smoothly. Remember, these practices not only help you avoid errors but also contribute to the fair and efficient operation of the platform for all users.

cross-posted from: https://discuss.online/post/5772572

> The current state of moderation across various online communities, especially on platforms like Reddit, has been a topic of much debate and dissatisfaction. Users have voiced concerns over issues such as moderator rudeness, abuse, bias, and a failure to adhere to their own guidelines. Moreover, many communities suffer from a lack of active moderation, as moderators often disengage due to the overwhelming demands of what essentially amounts to an unpaid, full-time job. This has led to a reliance on automated moderation tools and restrictions on user actions, which can stifle community engagement and growth. > > In light of these challenges, it's time to explore alternative models of community moderation that can distribute responsibilities more equitably among users, reduce moderator burnout, and improve overall community health. One promising approach is the implementation of a trust level system, similar to that used by Discourse. Such a system rewards users for positive contributions and active participation by gradually increasing their privileges and responsibilities within the community. This not only incentivizes constructive behavior but also allows for a more organic and scalable form of moderation. > > Key features of a trust level system include: > > - Sandboxing New Users: Initially limiting the actions new users can take to prevent accidental harm to themselves or the community. > - Gradual Privilege Escalation: Allowing users to earn more rights over time, such as the ability to post pictures, edit wikis, or moderate discussions, based on their contributions and behavior. > - Federated Reputation: Considering the integration of federated reputation systems, where users can carry over their trust levels from one community to another, encouraging cross-community engagement and trust. > > Implementing a trust level system could significantly alleviate the current strains on moderators and create a more welcoming and self-sustaining community environment. It encourages users to be more active and responsible members of their communities, knowing that their efforts will be recognized and rewarded. Moreover, it reduces the reliance on a small group of moderators, distributing moderation tasks across a wider base of engaged and trusted users. > > For communities within the Fediverse, adopting a trust level system could mark a significant step forward in how we think about and manage online interactions. It offers a path toward more democratic and self-regulating communities, where moderation is not a burden shouldered by the few but a shared responsibility of the many. > > As we continue to navigate the complexities of online community management, it's clear that innovative approaches like trust level systems could hold the key to creating more inclusive, respectful, and engaging spaces for everyone. > > #### Related > > - Grant users privileges based on activity level > - Understanding Discourse Trust Levels > - Federated Reputation

If Stack Overflow taught us anything, it's that

> "people will do anything for fake internet points" > > Source: Five years ago, Stack Overflow launched. Then, a miracle occurred.

Ever noticed how people online will jump through hoops, climb mountains, and even summon the powers of ancient memes just to earn some fake digital points? It's a wild world out there in the realm of social media, where karma reigns supreme and gamification is the name of the game.

But what if we could harness this insatiable thirst for validation and turn it into something truly magnificent? Imagine a social media platform where an army of monkeys tirelessly tags every post with precision and dedication, all in the pursuit of those elusive internet points. A digital utopia where every meme is neatly categorized, every cat video is meticulously labeled, and every shitpost is lovingly sorted into its own little corner of the internet.

Reddit tried this strategy to increase their content quantity, but alas, the monkeys got a little too excited and flooded the place with reposts and low-effort bananas. Stack Overflow, on the other hand, employed their chimp overlords for moderation and quality control, but the little guys got a bit too overzealous and started scaring away all the newbies with their stern glares and downvote-happy paws.

But fear not, my friends! For we shall learn from the mistakes of our primate predecessors and strike the perfect balance between order and chaos, between curation and creativity. With a leaderboard showcasing the top users per day, week, month, and year, the competition would be fierce, but not too fierce. Who wouldn't want to be crowned the Tagging Champion of the Month or the Sultan of Sorting? The drive for recognition combined with the power of gamification could revolutionize content curation as we know it, without sacrificing the essence of what makes social media so delightfully weird and wonderful.

And the benefits? Oh, they're endless! Imagine a social media landscape where every piece of content is perfectly tagged, allowing users to navigate without fear of stumbling upon triggering or phobia-inducing material. This proactive approach can help users avoid inadvertently coming across content that triggers phobias, traumatic events, or other sensitive topics. It's like a digital safe haven where you can frolic through memes and cat videos without a care in the world, all while basking in the glory of a well-organized and properly tagged online paradise.

So next time you see someone going to great lengths for those fake internet points, just remember - they might just be part of the Great Monkey Tagging Army, working tirelessly to make your online experience safer, more enjoyable, and infinitely more entertaining. Embrace the madness, my friends, for in the chaos lies true innovation! But not too much chaos, mind you – just the right amount to keep things interesting.

Related

• Post Tags
• Advanced Search and Tag Filtering
• Filter for Hiding Unwanted Content
• Comprehensive Tagging System
• Post tags
• Request for Comments: Flexible Tag System
• Booru-Style Image View, Search and Tagging by Users
• Grant users privileges based on activity level