Welcome to PyCon India 2023 CFP
- Join us for PyCon India 2023, the 14th edition of the premier Python conference in India, taking place in the vibrant city of Hyderabad from September 29 to October 2.
- This annual gathering brings together Python enthusiasts, developers, and industry professionals for four days of inspiring Talks, hands-on Workshops, and networking opportunities. Visit the official website for more information: https://in.pycon.org/2023/
Talks
- Talks should be 30 minutes long (including Q&A – 5 mins) and can be on any topic related to Python.
Schedule
- Talks will be there across the morning and evening sessions on September 30, 2023, and October 1, 2023,.
- We may have up to 3 parallel tracks of talks in each session. The morning session will run from 10:00 AM to 1:00 PM. The evening session will run from 2:00 PM to 6:00 PM.
Format
- The format of each talk will be up to the speaker but should include a mix of lectures, demos, and Q&A.
Workshops
Workshops are 3 hrs long interactive sessions where attendees can learn by doing.
Schedule
- Workshops will be held on September 29, 2023, across two morning and evening sessions.
- We may have up to 3 parallel tracks of workshops in each session. The morning session will run from 10:00 AM to 1:00 PM. The evening session will run from 2:00 PM to 5:00 PM.
Format
- Workshops are aimed at beginner, intermediate, and advanced experience-level participants.
- Workshop proposals must include a detailed outline of the covered topics and allocated time.
Important Dates
- CFP for Talks and Workshop closes on August 5.
- Selected Talks and Workshops will be announced on September 4.
What to Propose
Any topics of interest to Python programmers, with a focus on the following:
Lessons learned from using Python in projects, including unconventional and conventional wisdom and advice for similar problem-solving. E.g., I tried Python for video processing or in my medical imaging project, and here are the lessons.
Contributions to improving the Python language/ecosystem, such as creating libraries or proposing optimizations.
Knowledge gained from other languages, like type systems, functional programming patterns, or logic programming.
Thoughts on tech culture, diversity and inclusiveness, the physical and mental health of programmers, productivity improvement, workplace issues, and their impact when using Python.
Alternatively, consider offering teaching sessions on niche topics, recent technologies, or scientific papers, even at a beginner level.
Rehearsals
Shortlisted speakers will be expected to participate in rehearsal sessions. We will conduct Rehearsals via teleconferencing, where the speaker shall give a mock run of their talks in a time-bound manner.
The audience will include volunteers, reviewers, and possibly other speakers. We will give feedback to speakers if necessary.
This exercise aims to ensure speakers are ready with their talks beforehand. And also to ensure they can finish the talk within the stipulated time. It is also helpful for the speakers to get feedback on the content delivery and presentation.
Participation in the rehearsal sessions is likely to be required - chances of an unrehearsed talk making it to the final stage are substantially lower.
Diversity
We in the Python community believe in making our community more diverse. This suggests that we encourage content from diverse walks of life and also want to improve participation from under-represented groups.
Our goal is to maximize content from under-represented groups. You can help us by encouraging your friends, family, and colleagues to submit talks. You can also help by mentoring.
Also, note that we have a strict code of conduct. In intent and practice, we are committed to making the conference a pleasant, welcoming, and harassment-free experience for everyone, especially for under-represented groups.
Speaker Best Practices
We've compiled a set of detailed best practices - take a look.
Questions?
Ping us on Zulip. In addition to it, you can reach out to CFP volunteers:
- Soumendra Kumar Sahoo, CFP Lead – DM on Zulip
- Dr. Murali, CFP shadow lead - DM on Zulip
Proposal Sections
- Developer tools and automation - Tools and practices for automating development workflows and enhancing productivity like DevOps, Testing, CI/CD, Containers, Orchestration, Logging, and Monitoring, Selenium
- Concurrency - Approaches to concurrent Python programming using multiple threads like Multiprocessing, Multithreading, Async
- Core Python - Focused on understanding and mastering fundamental Python concepts and syntax like Documentation, Python Libraries, Language Features & Internals, Python Implementations
- Culture and Society - Exploring cultural aspects and societal influences like Diversity, health, life, education, productivity, workspace issues, community, coding for causes
- Ethics and Philosophy - Examination of ethical considerations and philosophical questions in technology like Govt. Policies, Responsible AI, Privacy and Bias.
- Others - Other topics not explicitly covered in the above sections like Quantum Computing, Storage, etc.
- Cloud Computing - Using Python to leverage cloud-based services and infrastructure like Cloud services (AWS, GCP, Azure, etc.) for Python, IaaS for Python.
- Blockchain - Understanding and developing blockchain systems and Web3.0 using Python.
- Distributed Computing - Techniques for processing data across multiple machines or processes using Python like PySpark, Dask, Distributed ML (Horovod), MPI (Message Passing Interface).
- Embedded Python and IOT - Using Python in embedded systems and Internet of Things (IoT) devices like MicroPython, Python on Hardware, Robotics, Arduino, and Raspberry Pi.
- Desktop Applications - Design and implementation of applications for desktop environments using Python like Qt, GTK+, Tkinter, Gnome, KDE.
- Web & App development - Building interactive websites and mobile applications using Python like APIs, REST, GraphQL, PyScript, Django, Flask, FastAPI, Kivy.
- Networking and Security - Concepts and practices for secure, efficient networking using Python like Network Programming, Network Security and Encryption.
- Game Design and 3D Modelling - Creation and manipulation of 3D models, AR/VR and principles of game design using Python.
- Scientific Computing - Using Python to solve complex scientific and mathematical problems like Python usage in scientific computing and research. GIS, Mathematics, Simulations.
- Data Science, AI & ML - Exploration and implementation of data science techniques, artificial intelligence, and machine learning algorithms using Python like Generative AI, Data Analytics & Visualisation, Data Engineering, Speech Processing, NLP, Computer Vision, MLOps and Others.
Proposal Types
- Workshops - Workshop is a 3 hr interactive session where attendees can learn by doing. Workshops can have one or more facilitators.
- Talks - Talk is a 30 minute presentation on a specific topic related to Python.
Selected Proposals
Talks
0 6
1. Taking a Multilingual Conversational Engine to Production: Theory to Reality
1 2
3. Python-powered Game Design and 3D Modelling: Unleashing Creativity and Immersion
0 5
5. Data Encoding Formats: A Comparison of Text-Based and Binary Encoding
0 9
6. OpenAI Whisper and it’s amazing power to do fine-tuning demonstrated on my mother-tongue
0 21
7. Securing your python applications and network using Zero Trust Security
0 1
8. Harnessing the Power of Django StreamingHttpResponse for Efficient Web Streaming
0 0
9. Fine-Tuning Insights: Lessons from Experimenting with a Large Language Model on Slack Data
0 4
10. Lessons from optimising inter-process communication: Path to zero-copy
0 1
11. The programmers guide to timestamps and timezones
0 3
12. Kubernetes + Python: Unleashing the Power of Python Controllers
0 15
14. Unleashing the Power of Python: Teaching Computer Science to Kids
0 6
16. Unlocking the Cosmos: Querying Space Observatories with Python
0 0
17. PyVelox: Interfacing Python bindings for the unified execution engine by Meta
0 1
18. Evaluating Generative Vision Models: Insights into the Fréchet Inception Distance and CLIP
0 1
20. Embracing Observability in Modern Python Applications: Harnessing the Power of OpenTelemetry
0 -1
23. Unlock the Power of Automation: Codify AWS Infrastructure with Python CDK
0 3
25. Revealing Uncommon Tricks: 25 Obscure Pandas & NumPy Hacks learnt over 5 years of being a Data Scientist
0 9
26. Architecting Scalable Python micro-services with GraphQL: Valuable Lessons and Best Practices
1 9
27. Data Pipelines in Production - Bad vs Best Practices
0 1
28. Speeding up Python with Rust: GeoIP Lookup Database as a case study.
0 0
30. The Why Conundrum - Practical causal inference and discovery with python
0 0
31. Amaze your friends by painting images on Google Sheets using Python
0 5
32. How Differential Privacy Changed The World, and What The Math Really Means
0 4
34. Accelerating testing cycles of embedded devices using Python
Talks
2 1
2. Unleashing the Power of the Lambda Function in Python
1 5
3. Building modular plugin-based Python distributions with Plux
0 9
4. From bulky to lean: Achieving 95% size reduction for Python containers
2 1
5. AutoGPT: The AI That Will Make You More Productive
0 0
6. Python for MLOps: Simplifying and Scaling Machine Learning Operations
2 4
7. LLM Building on our own data | Low Internet Availability Space | PDF - Video Summarisation using OpenAI
0 2
8. Dive deep into Video Surveillance to redefine women's safety in the Indian roads
0 3
9. Python's Indented Blocks: Efficient Code Structuring
0 4
10. Learn and Adapt: Shaping AI with Reinforcement Learning using the Gymnasium Framework
2 15
11. Algorithmic Trading Unveiled: From Complexity to Profits with AI Integration
0 1
13. Demystifying MLOps: Managing the Machine Learning Model Deployment Process
0 4
14. Model deployment with Nvidia Triton and deploying LLMs
0 3
15. Having an interesting idea about product? Create MVP with Django within weekend!
1 6
19. LLMs for the Masses: How to Train Your Own Language Models on a Limited Budget
0 1
20. Three factors that are blocking contributions to your Open Source project
0 22
23. From Chaos to Order: How MLFlow Transforms Experiment Tracking and Reproducibility
0 3
24. The Future of Serverless Computing: How Python is Leading the Way into Programmable Cloud!
2 1
26. The Sound of Your Footsteps can Predict for Dementia
2 2
28. Python's Role in Empowering the Internet of Things (IoT) Ecosystem.
0 2
31. Demystifying Explainable AI: A Comprehensive Guide with Python
1 0
33. Demystifying Process and Worker Models in Python Web Frameworks
0 3
35. Resilient Data Pipelines: Managing EMR Clusters with Python and Airflow
0 10
38. Unlocking Your Potential: Becoming a High-Value Asset in the Software Industry
0 6
39. Mathematical Modelling of AI: Unveiling Insights Beyond Artificial Intelligence
0 0
41. OLAF: One Load Audit Framework for provisioning efficient infrastructure and ideal scaling setting of ML services
0 11
44. FastAPI: A Paradigm Shift in Python Web Development
0 15
45. Let's build a thread-safe HTTP Connection Pool in 30 minutes
0 1
46. Python's Punchlines, Jest's Jestful Code: Unleashing Testing Potential
0 45
47. Virtual Assistants 2.0: How Gen AI elevates the game of domain-specific virtual assistants
0 2
48. How to build a unit testing library from scratch?
0 3
49. ChatGPT and Elasticsearch: OpenAI meets private data
0 4
50. Blocking Vs Non-Blocking: Is your Code really concurrent ?
0 4
53. Datafication of Indian Court Judgments using Natural Language Processing (NLP)
0 18
55. Making UI Testing easier with Widgetastic - A python library
0 0
58. Who broke the build? —Using Kuttl to improve E2E testing and release faster
0 10
59. Closing the faucet - fixing leaky applications by shifting privacy left
0 0
60. ML Defender: Deep Learning Based Image-Malware Detection
0 3
61. Messaging Systems: A talk about Distributed Task Processing
0 1
62. Advanced-Data Encryption using Hybrid Crypto-system as a makeshift resistance towards Quantum+AI
1 22
64. Python-based approach to simplify complex JSON structures by flattening them
0 1
67. Making 1k OpenAI calls to GPT-3.5/4 models in under 5 minutes with asyncio - the right way!
0 2
68. API lifecycle in Open Source Projects feat. Dapr
0 7
69. Proactive System Failure Detection with Log Analysis
0 11
71. Breaking Down Microservices: A Python Developer's Guide (Best Practices and Lessons Learned)
0 11
73. How not to shoot yourself in the foot with cryptography
1 0
74. Explainable AI: Demystifying Complex Models with Shapley Values
0 0
75. Satellite Image Processing and Analysis using Python
0 3
76. Shrinking Your Execution Time with Concurrency and Parallelism in Python
0 0
77. Integer Optimization in Python: A Practical Exploration through case studies and Beyond
0 0
78. Wayfarer AI: How I Built a Web-Searching and Multimodal Travel Chatbot with LLMs, Powered by Langchain & Gradio
0 0
80. Deploying Python on the edge: Mistakes, pain and learnings of scaling Python applications on millions of IoT devices
0 0
82. Accelerate Your Data Science and MLOps Workflow with DVC, PyCaret, and FastAPI
0 1
83. Exploring the Enigma of Diffusion models: Revealing the Science Behind Artificial Creativity
0 0
85. Exploring CoNLL-U Annotation Schema for Linguistic Structures with Python
0 0
87. ⚡Streamlining Machine Learning Projects: An Introduction to the Python Machine Learning Template
0 3
88. Exploring Hardware Projects with MicroPython: Unleash Your Creativity without the C Confusion
1 1
89. How to land your new Python Developer job: a Recruiter's perspective
0 1
90. FastAPI-Listing: Streamlining Data Listing in FastAPI Applications
0 4
91. Effortless API Testing: Unleash the Power of Python, Schemathesis and Open Api for Automated Test Cases Generation!
0 3
96. Writing a Python interpreter from scratch, in half an hour.
0 3
98. Dangers of Large Language Models: How to Mitigate the Risks ?
0 48
99. 🚀 Unlocking Performance in Large-Scale Systems: Explorations with MongoDB
0 47
101. PyTest Optimization - Supercharging Your CircleCI Pipeline for Efficient Testing
0 0
102. How YouTube is Democratizing Data Science Education?
0 0
104. Build production ready LLM powered applications using Langchain and FastAPI
0 2
106. Beyond the Hype: Understanding Diffusion Models for Cutting-Edge Generative Artistry
0 0
107. When principles meet constraints: DevOps and Clean Code for bootstrapped SMEs
0 1
109. Htmlipi - Building a Python native, no-parse HTML templating module using extended context-manager context and decorators
0 3
110. Exploring the Python Kubernetes Client: Unleashing K8s Capabilities through Python Programming
0 15
111. Designing Robust Celery Task Workflows for Python Applications
0 1
112. Bridging the Silos: Building a No Framework/Framework(NFF) using Apache Airflow
0 1
113. Build semantic search with MongoDB Atlas, OpenAI and PyMongo
0 0
114. Digital Twins - The Intersection of Generative AI and Quantum Computing
0 5
115. Python Concurrency Patterns: Thread-Based vs. Async-Based Approaches
2 5
116. Functional Programming in Python: A Guide to writing beautiful One-Liners and significantly Shorter code
0 1
118. The Rise of the AI-Powered Developer: Are Humans Still Relevant?
0 1
119. Creating data-aware applications with large language models
0 8
120. Data Validation & serialisation in Flask: Integration of Pydantic with Flask using Flask-Dantic
1 7
121. Enhance Code Quality and Streamline Code Reviews: Elevate Python Projects with Custom Git Hooks
0 6
122. Rhinestone: Simplifying API Documentation and API Testing Across Every Tech Stack
0 6
123. Scaling Heights: Mastering Load Testing in Python with Locust
0 0
124. On-premise solution to unleash the power of large language models (LLMs)
0 0
125. Explainability approaches for deep learning, shining light on black box AI models
0 6
128. From Design to Deploy in 1 Minute: DazzlePy's Instant Backend Alchemy
0 2
129. Python and the CI Factory: Crafting Effective Integration Pipelines
0 6
131. Orchestrating Dynamic Workflows with Python and MWAA with a containerised deployment
1 2
133. Pytest-Ansible: Simplifying Automation and Streamlining Testing
0 2
134. Using Open Source LLMs to implement an offline Assistive Guide [ + insights on how Open Source Solutions can be more user friendly for the General Public]
0 4
135. Robyn: An async Python web framework with a Rust runtime
0 1
139. Supercharge Your Django Apps: Unveiling Performance Secrets with the Magic of Django Silk!
0 2
140. Transforming Audio-Video Content Management: Unleashing the Power of OpenAI Whisper and GPT at Egnyte
0 0
141. Creating performant and scalable microservices with gRPC and protobuf
0 0
142. Composition over inheritance ? What about pythonic code
0 1
143. Importance of Validations and Sanitization in Web Development
0 0
145. Unified Cloud Agnostic Infrastructure: Empowering MLOps and DevOps with Cluster API
0 51
146. From Notebook Wizardry to Real-World Power: Python's Path to Production
0 7
150. Wielding Python's Wizards: A Guide to itertools and functools
0 4
152. Time Made Easy: Simplify Date and Time Handling with Python's Pendulum
0 4
153. Unlocking the Power of Python Using Asyncio
0 1
154. Pandas vs Polars: The Evolution of Data Manipulation in Python
0 6
155. Py-powered Pi: Lessons learnt with Python and Raspberry Pi for Home Automation
0 6
157. Unveiling the Third Dimension: A Journey into 3D Reconstruction with OpenCV
1 3
158. AsyncIO from the bottom up: building it from scratch with generators
0 0
159. Crafting Agile Flask Applications: Architecting for Scalability and Flexibility
0 6
160. Python and GTK: Crafting Beautiful User Interfaces for Your Applications
0 0
161. An open source Python library for microwave circuit design and analysis.
0 2
164. Building a Better Tomorrow: Responsible AI and the Ethical Imperative
0 3
165. BackdropAI: AI-powered context-based background changes for immersive live streaming
0 0
166. Doppelgänger: A tool to cater the need of data governance for businesses.
0 1
167. Building Sustainable Applications with Python: Navigating Generative AI, Computer Vision, and More with RecyloVision
0 24
168. Ingest, Analyze, Validate, Train, Test, Deploy: TFX - One Tool to Rule Them All
0 1
169. Cloud Native Buildpacks: An Alternative To (Defective) Dockerization For Python
0 0
171. Standardizing Class and Method Documentation for Libraries: Enhancing Clarity and Developer Productivity
0 1
173. Build complex chat apps using LLMs with ChainFury
0 0
174. Writing enterprise grade security tools in Python: Lessons Learned
0 0
175. Interpreting rationale behind Machine Learning model predictions using InterpretML
0 1
178. The Quest for Knowledge: Enabling Intelligent Chats and Fast Document Retrieval through Semantic Search and LLM with Langchain
0 2
180. Building a Production Ready LLM Application using MongoDB Atlas
0 1
181. Empower Python Developers with ReactPy: Building Frontends in a Pythonic way
0 1
183. Collaboration in Data Science: Tools, Challenges, and Best Practices
0 2