[D] PhD in RL/ML Theory or LLM
Hi guys,
I'm at a crossroads in my academic journey and would appreciate the community's insights. I'm trying to decide between pursuing a PhD focused on reinforcement learning/ML theory versus specializing in large language models with more experimental/applied research (these are the only two offers I had).
# Key considerations are the following:
# Research Impact
* RL/ML Theory: Foundational work that could advance the field's mathematical understanding
* LLMs: Direct applications in today's most transformative AI systems
# Job Prospects
* Theory: Academia, research labs, potentially more limited industry roles
* LLMs: High industry demand, active research area in both academia and industry
# Long-term Relevance
* Theory: Core principles likely to remain valuable regardless of specific technologies
* LLMs: Currently revolutionary but uncertain long-term trajectory
Personal background
* I'm an international student and about to finish my master program in US, so I no longer has enough time before making the final decision. I used to research in ml theory, but did not end up with a real top conference publication in theory. I personally doubt if I have enough mathematical background to pursue a successful PhD in this area (e.g., at least publish 2 theory papers a year on ICML/NeurIPS/ICLR/COLT/AISTATS). At the same time, I am personally doubting if theory
/r/MachineLearning
https://redd.it/1gvx8vx
Hi guys,
I'm at a crossroads in my academic journey and would appreciate the community's insights. I'm trying to decide between pursuing a PhD focused on reinforcement learning/ML theory versus specializing in large language models with more experimental/applied research (these are the only two offers I had).
# Key considerations are the following:
# Research Impact
* RL/ML Theory: Foundational work that could advance the field's mathematical understanding
* LLMs: Direct applications in today's most transformative AI systems
# Job Prospects
* Theory: Academia, research labs, potentially more limited industry roles
* LLMs: High industry demand, active research area in both academia and industry
# Long-term Relevance
* Theory: Core principles likely to remain valuable regardless of specific technologies
* LLMs: Currently revolutionary but uncertain long-term trajectory
Personal background
* I'm an international student and about to finish my master program in US, so I no longer has enough time before making the final decision. I used to research in ml theory, but did not end up with a real top conference publication in theory. I personally doubt if I have enough mathematical background to pursue a successful PhD in this area (e.g., at least publish 2 theory papers a year on ICML/NeurIPS/ICLR/COLT/AISTATS). At the same time, I am personally doubting if theory
/r/MachineLearning
https://redd.it/1gvx8vx
Thursday Daily Thread: Python Careers, Courses, and Furthering Education!
# Weekly Thread: Professional Use, Jobs, and Education 🏢
Welcome to this week's discussion on Python in the professional world! This is your spot to talk about job hunting, career growth, and educational resources in Python. Please note, this thread is not for recruitment.
---
## How it Works:
1. Career Talk: Discuss using Python in your job, or the job market for Python roles.
2. Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources.
3. Workplace Chat: Share your experiences, challenges, or success stories about using Python professionally.
---
## Guidelines:
- This thread is not for recruitment. For job postings, please see r/PythonJobs or the recruitment thread in the sidebar.
- Keep discussions relevant to Python in the professional and educational context.
---
## Example Topics:
1. Career Paths: What kinds of roles are out there for Python developers?
2. Certifications: Are Python certifications worth it?
3. Course Recommendations: Any good advanced Python courses to recommend?
4. Workplace Tools: What Python libraries are indispensable in your professional work?
5. Interview Tips: What types of Python questions are commonly asked in interviews?
---
Let's help each other grow in our careers and education. Happy discussing! 🌟
/r/Python
https://redd.it/1gw2e4u
# Weekly Thread: Professional Use, Jobs, and Education 🏢
Welcome to this week's discussion on Python in the professional world! This is your spot to talk about job hunting, career growth, and educational resources in Python. Please note, this thread is not for recruitment.
---
## How it Works:
1. Career Talk: Discuss using Python in your job, or the job market for Python roles.
2. Education Q&A: Ask or answer questions about Python courses, certifications, and educational resources.
3. Workplace Chat: Share your experiences, challenges, or success stories about using Python professionally.
---
## Guidelines:
- This thread is not for recruitment. For job postings, please see r/PythonJobs or the recruitment thread in the sidebar.
- Keep discussions relevant to Python in the professional and educational context.
---
## Example Topics:
1. Career Paths: What kinds of roles are out there for Python developers?
2. Certifications: Are Python certifications worth it?
3. Course Recommendations: Any good advanced Python courses to recommend?
4. Workplace Tools: What Python libraries are indispensable in your professional work?
5. Interview Tips: What types of Python questions are commonly asked in interviews?
---
Let's help each other grow in our careers and education. Happy discussing! 🌟
/r/Python
https://redd.it/1gw2e4u
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Just published part 2 of my articles on Python Project Management and Packaging, illustrated with uv
Hey everyone,
Just finished the second part of my comprehensive guide on Python project management. This part covers both building packages and publishing.
It's like the first article, the goal is to dig in the PEPs and specifications to understand what the standard is, why it came to be and how. This is was mostly covered in the build system section of the article.
The article: https://reinforcedknowledge.com/a-comprehensive-guide-to-python-project-management-and-packaging-concepts-illustrated-with-uv-part-2/
I have tried to implement some of your feedback. I worked a lot on the typos (I believe there aren't any but I may be wrong), and I tried to divide the article into three smaller articles:
- Just the high level overview: https://reinforcedknowledge.com/a-comprehensive-guide-to-python-project-management-and-packaging-part-2-high-level-overview/
- The deeper dive into the PEPs and specs for build systems: https://reinforcedknowledge.com/a-comprehensive-guide-to-python-project-management-and-packaging-part-2-source-trees-and-build-systems-interface/
- The deeper dive into PEPs and specs for package formats: https://reinforcedknowledge.com/a-comprehensive-guide-to-python-project-management-and-packaging-part-2-sdists-and-wheels/
In the parent article there are also two smalls sections about
/r/Python
https://redd.it/1gw1fe6
Hey everyone,
Just finished the second part of my comprehensive guide on Python project management. This part covers both building packages and publishing.
It's like the first article, the goal is to dig in the PEPs and specifications to understand what the standard is, why it came to be and how. This is was mostly covered in the build system section of the article.
The article: https://reinforcedknowledge.com/a-comprehensive-guide-to-python-project-management-and-packaging-concepts-illustrated-with-uv-part-2/
I have tried to implement some of your feedback. I worked a lot on the typos (I believe there aren't any but I may be wrong), and I tried to divide the article into three smaller articles:
- Just the high level overview: https://reinforcedknowledge.com/a-comprehensive-guide-to-python-project-management-and-packaging-part-2-high-level-overview/
- The deeper dive into the PEPs and specs for build systems: https://reinforcedknowledge.com/a-comprehensive-guide-to-python-project-management-and-packaging-part-2-source-trees-and-build-systems-interface/
- The deeper dive into PEPs and specs for package formats: https://reinforcedknowledge.com/a-comprehensive-guide-to-python-project-management-and-packaging-part-2-sdists-and-wheels/
In the parent article there are also two smalls sections about
uv build and uv publish. I don't think they deserve to be in a separate smaller article and I included them for completeness but anyone can just go uv help <command> and read about the command and it'd be much better. I did explain some small details that I believe that not everyone knows but I don't think it replaces your/r/Python
https://redd.it/1gw1fe6
Should I Learn a New Tech or Start Applying?
Hello folks,
I've been working with Django for the past 3 months and have hands-on experience in Machine Learning, Computer Vision, and other AI-related projects. I'm pretty confident in Python and have completed two remote internships, each lasting 2 months.
I'm aiming for a decent package of around 5-6 LPA, but I'm at a crossroads:
1)Should I learn a different technology (like Node.js, since many job postings mention it), or is Django enough?
2)Should I start applying for jobs now or focus on adding more skills to match industry demands?
Also, can you suggest platforms or places where I can find Django-related job opportunities? Most openings I come across seem to require JavaScript or Node.js expertise.
Thank you in advance for your advice!
/r/django
https://redd.it/1gw81a7
Hello folks,
I've been working with Django for the past 3 months and have hands-on experience in Machine Learning, Computer Vision, and other AI-related projects. I'm pretty confident in Python and have completed two remote internships, each lasting 2 months.
I'm aiming for a decent package of around 5-6 LPA, but I'm at a crossroads:
1)Should I learn a different technology (like Node.js, since many job postings mention it), or is Django enough?
2)Should I start applying for jobs now or focus on adding more skills to match industry demands?
Also, can you suggest platforms or places where I can find Django-related job opportunities? Most openings I come across seem to require JavaScript or Node.js expertise.
Thank you in advance for your advice!
/r/django
https://redd.it/1gw81a7
Reddit
From the django community on Reddit
Explore this post and more from the django community
Offering 50 free places on my Python Udemy course
Thank you to everyone who beta tested my new Udemy course "The 10-Day Python Bootcamp for Engineers and Scientists".
Things are going well and I'm making some income! Given there are literally millions of people out there interested in Python, I figured it wouldn't do any harm to hand out some more vouchers to this community.
As such, here is a link to 50 free vouchers for the course: https://www.udemy.com/course/python-for-engineers-scientists-and-analysts/?couponCode=THANKYOUREDDIT
As always, I'm grateful for your feedback. Enjoy the course if you do take a voucher.
/r/Python
https://redd.it/1gw30h9
Thank you to everyone who beta tested my new Udemy course "The 10-Day Python Bootcamp for Engineers and Scientists".
Things are going well and I'm making some income! Given there are literally millions of people out there interested in Python, I figured it wouldn't do any harm to hand out some more vouchers to this community.
As such, here is a link to 50 free vouchers for the course: https://www.udemy.com/course/python-for-engineers-scientists-and-analysts/?couponCode=THANKYOUREDDIT
As always, I'm grateful for your feedback. Enjoy the course if you do take a voucher.
/r/Python
https://redd.it/1gw30h9
Udemy
The 10-Day Python Bootcamp for Engineers and Scientists 2024
Learn practical coding for data science, visualization, modeling and simulation - including numpy, pandas and seaborn.
Tips to morph Internal DRF App into Multi Tenant SaaS Setup
Dear community,
I learned A TON over the last months from all the posts and great answers here.
My team and I are transforming our Django-React application (utilizing DRF, PostgreSQL, Redis, Celery, and MinIO) into a multi-tenant SaaS platform. Currently, the app relies heavily on manual admin management. Our goal is to streamline client onboarding and empower tenant admins to manage their settings, data, and users independently.
Points where we catch strays :
1. Multi-Tenancy Design: We're debating between using separate schemas or databases. We aim for robust data isolation but are concerned about the complexities of schema migrations and managing multiple databases.
2. Customization: Tenants wish to define custom fields (likely using JSON) and workflows. How can we efficiently handle queries and searches across these fields without overloading PostgreSQL?
3. Global Search: Tenants require robust search functionality, including full-text and nested searches. While Elasticsearch seems suitable, syncing tenant data dynamically poses challenges. In the interim, could PostgreSQL Views facilitate searches across models and relationships?
4. Throttling & Performance: How can we prevent resource hogging (e.g., database queries, Celery tasks) by "noisy neighbors" without complicating resource allocation?
5. Auth/Compliance: Supporting SSO and maintaining tenant-specific audit logs is becoming complex. Any advice on keeping this
/r/django
https://redd.it/1gwaw56
Dear community,
I learned A TON over the last months from all the posts and great answers here.
My team and I are transforming our Django-React application (utilizing DRF, PostgreSQL, Redis, Celery, and MinIO) into a multi-tenant SaaS platform. Currently, the app relies heavily on manual admin management. Our goal is to streamline client onboarding and empower tenant admins to manage their settings, data, and users independently.
Points where we catch strays :
1. Multi-Tenancy Design: We're debating between using separate schemas or databases. We aim for robust data isolation but are concerned about the complexities of schema migrations and managing multiple databases.
2. Customization: Tenants wish to define custom fields (likely using JSON) and workflows. How can we efficiently handle queries and searches across these fields without overloading PostgreSQL?
3. Global Search: Tenants require robust search functionality, including full-text and nested searches. While Elasticsearch seems suitable, syncing tenant data dynamically poses challenges. In the interim, could PostgreSQL Views facilitate searches across models and relationships?
4. Throttling & Performance: How can we prevent resource hogging (e.g., database queries, Celery tasks) by "noisy neighbors" without complicating resource allocation?
5. Auth/Compliance: Supporting SSO and maintaining tenant-specific audit logs is becoming complex. Any advice on keeping this
/r/django
https://redd.it/1gwaw56
Reddit
From the django community on Reddit
Explore this post and more from the django community
Django REST Framework (DRF) ?
I have a strong foundation in Django and have completed several full-stack projects using Django templates. Now that I’m confident with the basics, I’m looking to expand my skills by diving into Django REST Framework (DRF) and building APIs.
I already understand the core concepts of APIs and how they work, but I’m looking for high-quality resources to help me get started with DRF whether it’s books, video tutorials, or other learning materials.
If you have any recommendations, I’d greatly appreciate your guidance. Thank you!
/r/djangolearning
https://redd.it/1gvx77f
I have a strong foundation in Django and have completed several full-stack projects using Django templates. Now that I’m confident with the basics, I’m looking to expand my skills by diving into Django REST Framework (DRF) and building APIs.
I already understand the core concepts of APIs and how they work, but I’m looking for high-quality resources to help me get started with DRF whether it’s books, video tutorials, or other learning materials.
If you have any recommendations, I’d greatly appreciate your guidance. Thank you!
/r/djangolearning
https://redd.it/1gvx77f
Reddit
From the djangolearning community on Reddit
Explore this post and more from the djangolearning community
SQLAlchemy Foreign Key Error: "Could not find table 'user' for assignment_reminder.teacher_id"
# Body:
# Problem Denoscription:
I'm encountering an error when running my Flask application. The error occurs when I try to log in, and it seems related to the `AssignmentReminder` model's foreign key referencing the `User` model. Here's the error traceback:
sqlalchemy.exc.NoReferencedTableError: Foreign key associated with column 'assignment_reminder.teacher_id' could not find table 'user' with which to generate a foreign key to target column 'id'
# Relevant Code:
Here are the models involved:
**User Model**:
class User(db.Model, UserMixin):
__tablename__ = 'user'
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String(150), nullable=False, unique=True)
email = db.Column(db.String(120), unique=True, nullable=False)
password_hash = db.Column(db.String(128), nullable=False)
role = db.Column(db.String(20), nullable=False) # e.g., 'student', 'teacher', etc.
def __repr__(self):
return f"User('{self.username}', '{self.email}', '{self.role}')"
**AssignmentReminder Model**:
class AssignmentReminder(db.Model):
__tablename__ = 'assignment_reminder'
/r/flask
https://redd.it/1gwed4y
# Body:
# Problem Denoscription:
I'm encountering an error when running my Flask application. The error occurs when I try to log in, and it seems related to the `AssignmentReminder` model's foreign key referencing the `User` model. Here's the error traceback:
sqlalchemy.exc.NoReferencedTableError: Foreign key associated with column 'assignment_reminder.teacher_id' could not find table 'user' with which to generate a foreign key to target column 'id'
# Relevant Code:
Here are the models involved:
**User Model**:
class User(db.Model, UserMixin):
__tablename__ = 'user'
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String(150), nullable=False, unique=True)
email = db.Column(db.String(120), unique=True, nullable=False)
password_hash = db.Column(db.String(128), nullable=False)
role = db.Column(db.String(20), nullable=False) # e.g., 'student', 'teacher', etc.
def __repr__(self):
return f"User('{self.username}', '{self.email}', '{self.role}')"
**AssignmentReminder Model**:
class AssignmentReminder(db.Model):
__tablename__ = 'assignment_reminder'
/r/flask
https://redd.it/1gwed4y
Reddit
From the flask community on Reddit
Explore this post and more from the flask community
Generate Realistic Podcast Sessions Programmatically
Hey everyone! 👋
I just released `podcast_tts`, a Python library that generates **realistic podcasts and dialogues** with multi-speaker audio, background music, and professional-quality mixing—all running **100% locally**.
# What My Project Does
`podcast_tts` allows you to programmatically create high-quality audio sessions with multiple speakers, dynamic or premade voice profiles, and customizable background music. You can save the output as MP3 or WAV files and even assign playback to specific audio channels for spatial separation.
It’s designed to be flexible, whether you’re building an API with FastAPI or experimenting with personal projects.
# Target Audience
This library is perfect for:
* Developers needing a **local TTS solution** for privacy or offline use.
* Engineers building backend systems for **audio generation** (e.g., podcasts or virtual assistants).
* Anyone looking for an all-in-one tool for **dialogue generation** with professional audio quality.
# Comparison to Alternatives
Unlike many TTS libraries that rely on cloud services, `podcast_tts` is fully offline, ensuring privacy and reducing latency. It also integrates features like **multi-speaker support**, **background music mixing**, and **text normalization**, which are often missing or require multiple tools to achieve.
The project is **open source**, and you can find it on GitHub here: [GitHub Repo](https://github.com/puntorigen/podcast_tts).
It’s also available on **PyPI** for easy installation: `pip install podcast_tts`.
I’ve shared more
/r/Python
https://redd.it/1gw5j21
Hey everyone! 👋
I just released `podcast_tts`, a Python library that generates **realistic podcasts and dialogues** with multi-speaker audio, background music, and professional-quality mixing—all running **100% locally**.
# What My Project Does
`podcast_tts` allows you to programmatically create high-quality audio sessions with multiple speakers, dynamic or premade voice profiles, and customizable background music. You can save the output as MP3 or WAV files and even assign playback to specific audio channels for spatial separation.
It’s designed to be flexible, whether you’re building an API with FastAPI or experimenting with personal projects.
# Target Audience
This library is perfect for:
* Developers needing a **local TTS solution** for privacy or offline use.
* Engineers building backend systems for **audio generation** (e.g., podcasts or virtual assistants).
* Anyone looking for an all-in-one tool for **dialogue generation** with professional audio quality.
# Comparison to Alternatives
Unlike many TTS libraries that rely on cloud services, `podcast_tts` is fully offline, ensuring privacy and reducing latency. It also integrates features like **multi-speaker support**, **background music mixing**, and **text normalization**, which are often missing or require multiple tools to achieve.
The project is **open source**, and you can find it on GitHub here: [GitHub Repo](https://github.com/puntorigen/podcast_tts).
It’s also available on **PyPI** for easy installation: `pip install podcast_tts`.
I’ve shared more
/r/Python
https://redd.it/1gw5j21
GitHub
GitHub - puntorigen/podcast_tts: A class for generating realistic audio (TTS) for podcasts and dialogues.
A class for generating realistic audio (TTS) for podcasts and dialogues. - puntorigen/podcast_tts
Creating a Python System to Turn All PostgreSQL Servers into Masters with Auto-Recovery and Sync – N
Hello Python community!I’m currently working on developing a distributed PostgreSQL system using Python, where all servers act as masters. Additionally, I’m adopting a clear separation between servers and clients to create a flexible and efficient architecture.The primary goals of this project are as follows:
1. Master-Master architecture
All servers operate equally, eliminating single points of failure (SPOF).
2. Server-Client separation
Clients can seamlessly access the system while the internal operations are optimized for distributed workloads.
3. Automatic recovery
In case of server failures, other nodes automatically handle recovery to maintain uninterrupted service.
4. Automatic data synchronization
Efficiently synchronizing data across nodes while ensuring consistency.
5. Leveraging Python and PostgreSQL
Combining Python's flexibility with PostgreSQL's robust features.
# Current Tools
For this project, I’m focusing on the following two key modules:
psycopg3: To enable efficient communication with PostgreSQL, especially with its asynchronous capabilities.
aioquic: For leveraging the QUIC protocol to achieve fast and reliable data synchronization, particularly for server-client communications in a distributed setup.
# Challenges and Feedback Needed
Here are some specific points where I’d love to get your insights:
1. Server-Client Design Approach
What’s the best way to dynamically determine which server the client should
/r/Python
https://redd.it/1gwghji
Hello Python community!I’m currently working on developing a distributed PostgreSQL system using Python, where all servers act as masters. Additionally, I’m adopting a clear separation between servers and clients to create a flexible and efficient architecture.The primary goals of this project are as follows:
1. Master-Master architecture
All servers operate equally, eliminating single points of failure (SPOF).
2. Server-Client separation
Clients can seamlessly access the system while the internal operations are optimized for distributed workloads.
3. Automatic recovery
In case of server failures, other nodes automatically handle recovery to maintain uninterrupted service.
4. Automatic data synchronization
Efficiently synchronizing data across nodes while ensuring consistency.
5. Leveraging Python and PostgreSQL
Combining Python's flexibility with PostgreSQL's robust features.
# Current Tools
For this project, I’m focusing on the following two key modules:
psycopg3: To enable efficient communication with PostgreSQL, especially with its asynchronous capabilities.
aioquic: For leveraging the QUIC protocol to achieve fast and reliable data synchronization, particularly for server-client communications in a distributed setup.
# Challenges and Feedback Needed
Here are some specific points where I’d love to get your insights:
1. Server-Client Design Approach
What’s the best way to dynamically determine which server the client should
/r/Python
https://redd.it/1gwghji
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Best Tech Stack for a Chat App with AI: Python vs Nest.js for Backend?
I am working on a B2C startup and need to design the backend for a website and mobile apps supporting a chat application. The platform will incorporate AI/ML models to analyze chats and user inputs, alongside a notification system for users. My initial idea is to separate the backend and AI services. Should I use Python for both the backend(with flask or django) and AI components, or would it be better to leverage Nest.js for the backend, while using Python for AI?
/r/flask
https://redd.it/1gwatcn
I am working on a B2C startup and need to design the backend for a website and mobile apps supporting a chat application. The platform will incorporate AI/ML models to analyze chats and user inputs, alongside a notification system for users. My initial idea is to separate the backend and AI services. Should I use Python for both the backend(with flask or django) and AI components, or would it be better to leverage Nest.js for the backend, while using Python for AI?
/r/flask
https://redd.it/1gwatcn
Reddit
From the flask community on Reddit
Explore this post and more from the flask community
R BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games
Tired of saturated benchmarks? Want scope for a significant leap in capabilities?
Introducing BALROG: a Benchmark for Agentic LLM and VLM Reasoning On Games!
BALROG is a challenging benchmark for LLM agentic capabilities, designed to stay relevant for years to come.
Check it out!
GitHub: https://github.com/balrog-ai/BALROG
Leaderboard: https://balrogai.com
Paper: https://arxiv.org/abs/2411.13543
/r/MachineLearning
https://redd.it/1gwhnf8
Tired of saturated benchmarks? Want scope for a significant leap in capabilities?
Introducing BALROG: a Benchmark for Agentic LLM and VLM Reasoning On Games!
BALROG is a challenging benchmark for LLM agentic capabilities, designed to stay relevant for years to come.
Check it out!
GitHub: https://github.com/balrog-ai/BALROG
Leaderboard: https://balrogai.com
Paper: https://arxiv.org/abs/2411.13543
/r/MachineLearning
https://redd.it/1gwhnf8
GitHub
GitHub - balrog-ai/BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games
Benchmarking Agentic LLM and VLM Reasoning On Games - balrog-ai/BALROG
HPC-Style Job Scripts in the Cloud
The first parallel computing system I ever used were job noscripts on HPC Job schedulers (like SLURM, PBS, SGE, ...). They had an API straight out of the 90s, but were super straightforward and helped me do research when I was still just a baby programmer.
The cloud is way more powerful than these systems, but kinda sucks from a UX perspective. I wanted to replicate the experience I had on HPC on the cloud with Cloud-based Job Arrays. It wasn't actually all that hard.
[Post here](https://docs.coiled.io/blog/slurm-job-arrays.html)
Video here
This is still super new (we haven't even put up proper docs yet) but I'm excited about the feature. Thoughts/questions/critiques welcome.
/r/Python
https://redd.it/1gwj7e6
The first parallel computing system I ever used were job noscripts on HPC Job schedulers (like SLURM, PBS, SGE, ...). They had an API straight out of the 90s, but were super straightforward and helped me do research when I was still just a baby programmer.
The cloud is way more powerful than these systems, but kinda sucks from a UX perspective. I wanted to replicate the experience I had on HPC on the cloud with Cloud-based Job Arrays. It wasn't actually all that hard.
[Post here](https://docs.coiled.io/blog/slurm-job-arrays.html)
Video here
This is still super new (we haven't even put up proper docs yet) but I'm excited about the feature. Thoughts/questions/critiques welcome.
/r/Python
https://redd.it/1gwj7e6
Coiled
SLURM-Style Job Arrays on the Cloud with Coiled
Matthew Rocklin 2024-11-19 3 min read Update Jan. 9th, 2025: We’ve added documentation for Coiled Batch. SLURM and other job schedulers have made it easy to run noscripts on HPC systems for decades. ...
Finished my first Django app! (But deployment is hell)
I just finished my first django app. A simple crm for my company. Developing it was an experience that makes me want to switch carrers into web app development. It’s been really really awesome. Sadly I can’t say the same thing about deploying the app. I’ve been trying to get it to work on and off without complete success.
This is how my process looks like:
Pull from repo -> break gunicorn in various ways and spend half and hour figuring out what broke-> get asked to change something -> have fun modifying stuff in my development environment -> pull from repo -> break gunicorn in various ways and spend half and hour figuring out what broke-> get asked to change something -> have fun modifying stuff in my development environment -> …
Is it always like this or am I missing something?
I am just a python/django enthusiast. I know about css and html, but I am not an engineer by any means.
I really enjoy developing in Django but why is deployment hell?
/r/django
https://redd.it/1gwly9h
I just finished my first django app. A simple crm for my company. Developing it was an experience that makes me want to switch carrers into web app development. It’s been really really awesome. Sadly I can’t say the same thing about deploying the app. I’ve been trying to get it to work on and off without complete success.
This is how my process looks like:
Pull from repo -> break gunicorn in various ways and spend half and hour figuring out what broke-> get asked to change something -> have fun modifying stuff in my development environment -> pull from repo -> break gunicorn in various ways and spend half and hour figuring out what broke-> get asked to change something -> have fun modifying stuff in my development environment -> …
Is it always like this or am I missing something?
I am just a python/django enthusiast. I know about css and html, but I am not an engineer by any means.
I really enjoy developing in Django but why is deployment hell?
/r/django
https://redd.it/1gwly9h
Reddit
From the django community on Reddit
Explore this post and more from the django community
How I Escaped Python Dependency Hell with pip-tools
https://medium.com/@erik_48905/escape-python-dependency-hell-with-just-2-commands-3245fb0c0bb8
/r/flask
https://redd.it/1gwq6oj
https://medium.com/@erik_48905/escape-python-dependency-hell-with-just-2-commands-3245fb0c0bb8
/r/flask
https://redd.it/1gwq6oj
Medium
Escape Python Dependency Hell with Just 2 Commands
Introduction
Friday Daily Thread: r/Python Meta and Free-Talk Fridays
# Weekly Thread: Meta Discussions and Free Talk Friday 🎙️
Welcome to Free Talk Friday on /r/Python! This is the place to discuss the r/Python community (meta discussions), Python news, projects, or anything else Python-related!
## How it Works:
1. Open Mic: Share your thoughts, questions, or anything you'd like related to Python or the community.
2. Community Pulse: Discuss what you feel is working well or what could be improved in the /r/python community.
3. News & Updates: Keep up-to-date with the latest in Python and share any news you find interesting.
## Guidelines:
All topics should be related to Python or the /r/python community.
Be respectful and follow Reddit's Code of Conduct.
## Example Topics:
1. New Python Release: What do you think about the new features in Python 3.11?
2. Community Events: Any Python meetups or webinars coming up?
3. Learning Resources: Found a great Python tutorial? Share it here!
4. Job Market: How has Python impacted your career?
5. Hot Takes: Got a controversial Python opinion? Let's hear it!
6. Community Ideas: Something you'd like to see us do? tell us.
Let's keep the conversation going. Happy discussing! 🌟
/r/Python
https://redd.it/1gwub4n
# Weekly Thread: Meta Discussions and Free Talk Friday 🎙️
Welcome to Free Talk Friday on /r/Python! This is the place to discuss the r/Python community (meta discussions), Python news, projects, or anything else Python-related!
## How it Works:
1. Open Mic: Share your thoughts, questions, or anything you'd like related to Python or the community.
2. Community Pulse: Discuss what you feel is working well or what could be improved in the /r/python community.
3. News & Updates: Keep up-to-date with the latest in Python and share any news you find interesting.
## Guidelines:
All topics should be related to Python or the /r/python community.
Be respectful and follow Reddit's Code of Conduct.
## Example Topics:
1. New Python Release: What do you think about the new features in Python 3.11?
2. Community Events: Any Python meetups or webinars coming up?
3. Learning Resources: Found a great Python tutorial? Share it here!
4. Job Market: How has Python impacted your career?
5. Hot Takes: Got a controversial Python opinion? Let's hear it!
6. Community Ideas: Something you'd like to see us do? tell us.
Let's keep the conversation going. Happy discussing! 🌟
/r/Python
https://redd.it/1gwub4n
Redditinc
Reddit Rules
Reddit Rules - Reddit
MetaDataScraper: A Python Package for scraping Facebook page data with ease!
Hey everyone! 👋
I’m excited to introduce MetaDataScraper, a Python package designed to automate the extraction of valuable data from Facebook pages. Whether you're tracking follower counts, post interactions, or multimedia content like videos, this tool makes scraping Facebook page data a breeze. No API keys or tedious manual effort required — just pure automation! 😎
Usage docs here at ReadTheDocs.
# Key Features:
Automated Extraction: Instantly fetch follower counts, post texts, likes, shares, and video links from public Facebook pages.
Comprehensive Data Retrieval: Get detailed insights from posts, including text content, interactions (likes, shares), and multimedia (videos, reels, etc.).
Loginless Scraping: With the LoginlessScraper class, no Facebook login is needed. Perfect for scraping public pages.
Logged-In Scraping: The LoggedInScraper class allows you to login to Facebook and bypass the limitations of loginless scraping. Access more content and private posts if needed.
Headless Operation: Scrapes data silently in the background (without opening a visible browser window) — perfect for automated tasks or server environments.
Flexible & Easy-to-Use: Simple setup, clear method calls, and works seamlessly with Selenium WebDriver.
# Example Usage:
1. Installation: Simply install via pip:
​
pip install MetaDataScraper
2) Loginless Scraping (no Facebook login required):
from MetaDataScraper import
/r/Python
https://redd.it/1gwn9yd
Hey everyone! 👋
I’m excited to introduce MetaDataScraper, a Python package designed to automate the extraction of valuable data from Facebook pages. Whether you're tracking follower counts, post interactions, or multimedia content like videos, this tool makes scraping Facebook page data a breeze. No API keys or tedious manual effort required — just pure automation! 😎
Usage docs here at ReadTheDocs.
# Key Features:
Automated Extraction: Instantly fetch follower counts, post texts, likes, shares, and video links from public Facebook pages.
Comprehensive Data Retrieval: Get detailed insights from posts, including text content, interactions (likes, shares), and multimedia (videos, reels, etc.).
Loginless Scraping: With the LoginlessScraper class, no Facebook login is needed. Perfect for scraping public pages.
Logged-In Scraping: The LoggedInScraper class allows you to login to Facebook and bypass the limitations of loginless scraping. Access more content and private posts if needed.
Headless Operation: Scrapes data silently in the background (without opening a visible browser window) — perfect for automated tasks or server environments.
Flexible & Easy-to-Use: Simple setup, clear method calls, and works seamlessly with Selenium WebDriver.
# Example Usage:
1. Installation: Simply install via pip:
​
pip install MetaDataScraper
2) Loginless Scraping (no Facebook login required):
from MetaDataScraper import
/r/Python
https://redd.it/1gwn9yd
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Finally launched my portfolio with Django
https://preview.redd.it/0wec41h4pa2e1.png?width=1904&format=png&auto=webp&s=0b06f10f26406892d7a7a85f02f0b3c334630595
After years of working with Django, I always postponed building my own personal site. Recently, I decided it was time, and that’s how eriktaveras.com came to life.
# What’s included?
Backend: Django to manage projects and a contact form with spam protection (rate limiting and content detection).
Frontend: Tailwind CSS for a clean design and Alpine.js for light interactivity.
Extras: Automatic Telegram notifications whenever someone submits the contact form.
I’m also working on adding a blog and still uploading more projects to the portfolio, so it’s very much a work in progress.
# What I learned
Using Tailwind CSS for quick, efficient design.
Combining Django with lightweight frontend tools like Alpine.js.
Building a secure contact form without relying on external services.
If you’re curious, feel free to check it out at www.eriktaveras.com. I’d love to hear your feedback or ideas for improvement!
Thanks for reading! 🚀
/r/django
https://redd.it/1gwlx9o
https://preview.redd.it/0wec41h4pa2e1.png?width=1904&format=png&auto=webp&s=0b06f10f26406892d7a7a85f02f0b3c334630595
After years of working with Django, I always postponed building my own personal site. Recently, I decided it was time, and that’s how eriktaveras.com came to life.
# What’s included?
Backend: Django to manage projects and a contact form with spam protection (rate limiting and content detection).
Frontend: Tailwind CSS for a clean design and Alpine.js for light interactivity.
Extras: Automatic Telegram notifications whenever someone submits the contact form.
I’m also working on adding a blog and still uploading more projects to the portfolio, so it’s very much a work in progress.
# What I learned
Using Tailwind CSS for quick, efficient design.
Combining Django with lightweight frontend tools like Alpine.js.
Building a secure contact form without relying on external services.
If you’re curious, feel free to check it out at www.eriktaveras.com. I’d love to hear your feedback or ideas for improvement!
Thanks for reading! 🚀
/r/django
https://redd.it/1gwlx9o
How do you handle speeding up frequent reads on aggregations without redundancy risks?
I've built an internal tool for Estimating, Inventory, Schedule & Dispatch, Job Costing & Reconciliation at a construction contractor business. We're using postgres. Now that much of the operational functionality is there with proper normalization, I'm building out dashboards that do a lot of aggregation on deeply nested fields.
So the (possibly misguided/skill issue?) goal is to persist some aggregated values to distant parent model objects. But the values can never be out of sync!
I've implemented the new
So there's a few options I'm aware of, and I'm curious what you use in production environments where data validity and integrity is vital (this affects what people are paid, records for taxes, etc).
Side effects in the child model's `save()` method override
1. Slow on save
2. Error prone, No guarantees on data integrity
3. Tons of clutter and poor maintainability in models . py
Django Signals to update affected parent fields
1. Slow on save
2. Does this roll back
/r/django
https://redd.it/1gwt719
I've built an internal tool for Estimating, Inventory, Schedule & Dispatch, Job Costing & Reconciliation at a construction contractor business. We're using postgres. Now that much of the operational functionality is there with proper normalization, I'm building out dashboards that do a lot of aggregation on deeply nested fields.
So the (possibly misguided/skill issue?) goal is to persist some aggregated values to distant parent model objects. But the values can never be out of sync!
I've implemented the new
GeneratedField with db_persist=True in a number of places, which just simplifies some things, but as I understand it I can't use a GeneratedField to sum a value on a child related model.So there's a few options I'm aware of, and I'm curious what you use in production environments where data validity and integrity is vital (this affects what people are paid, records for taxes, etc).
Side effects in the child model's `save()` method override
1. Slow on save
2. Error prone, No guarantees on data integrity
3. Tons of clutter and poor maintainability in models . py
Django Signals to update affected parent fields
1. Slow on save
2. Does this roll back
/r/django
https://redd.it/1gwt719
Reddit
From the django community on Reddit
Explore this post and more from the django community
Networking applications should not be opening sockets
From my first development project involving networking I was hooked. I also found some areas of networking software a bit unresolved. There was some strong modeling for people who make networking components but that seemed to peter out after the sockets library. Nobody seemed to have a good compelling way to bundle all that block I/O, byte framing, encoding/decoding, message dispatching etc into something that was reused from project to project.
I finally did something about this and have produced a software library. I also wrote a discussion paper that is the first link in the readme of the following github repo. The repo contains demonstration modules that are referred to in the other readme links.
Networking is not about sockets
Is there anyone else out there that has thought along similar lines? Has anyone seen something better?
/r/Python
https://redd.it/1gw3hwi
From my first development project involving networking I was hooked. I also found some areas of networking software a bit unresolved. There was some strong modeling for people who make networking components but that seemed to peter out after the sockets library. Nobody seemed to have a good compelling way to bundle all that block I/O, byte framing, encoding/decoding, message dispatching etc into something that was reused from project to project.
I finally did something about this and have produced a software library. I also wrote a discussion paper that is the first link in the readme of the following github repo. The repo contains demonstration modules that are referred to in the other readme links.
Networking is not about sockets
Is there anyone else out there that has thought along similar lines? Has anyone seen something better?
/r/Python
https://redd.it/1gw3hwi
GitHub
GitHub - mr-ansar/from-sketches-to-networking-code: Implementation of guide to async networking
Implementation of guide to async networking. Contribute to mr-ansar/from-sketches-to-networking-code development by creating an account on GitHub.