PyCon India, the premier conference in India on using and developing the Python programming language is conducted annually by the Python developer community. It attracts the best Python programmers across the country and abroad.
Guidelines
- Proposal should have objective with clear expectation for audience.
- Proposal description should be short and to the point.
- Proposal should have proper prerequisites like environment setup, library version.
- No proposal will be selected without link to appropriate session content like presentation, pdf, code snippets etc ...
- Proposal content links can be updated later.
- Proposal content should adhere to code of conduct.
- Proposal content shouldn't have company name through out the content. Mention of employer is allowed only in the beginning of the content (presentation/pdf).
- Background image/wallpaper shouldn't contain company name/logos.
- Selection/Rejection about talks will notified via email.
- For any questions, please write to contact@in.pycon.org.
Note: If your proposal isn't displayed, you must have saved in draft mode. Edit your proposal to make it public.
Proposal Sections
- Core Python - Language Features, Python Implementations, Standard Library, Algorithms, C APIs
- Embedded Python - Embedded Python, Device Interfacing, Robotics, Raspberry Pi, Arduino
- Concurrency - Parallel Processing, Async IO
- Scientific Computing - Scientific/Numeric Libraries
- Data Visualization and Analytics - Visualizations, Statistics, Big Data
- Web Development - Web Frameworks, Restful Interfaces
- Security - Web Security, Server Security, Cryptography, Encryption
- Testing - Unit Testing, Selenium, py.test, Nose
- Network Programming - Socket programming, Async IO
- Python 3k - Features, Python 2 to 3 migration experience, Writing compatible 2 and 3 code
- Infrastructure - Configuration management, Automation, Cloud Infrastructure, Continuous Integration
- Others - Others
Proposal Types
- Talks - Talks are focussed on a topic for 40 minutes.
- Workshops - Workshops are in depth hands on session for 2 hours and 30 minutes
Selected Proposals
Talks
2 19
2. Avoiding common pitfalls of datetime from a webapp's perspective
0 13
4. Building NextGen IoT solutions using Python and Cloud
1 28
6. Analyzing arguments during a debate using Natural Language Processing in Python
1 2
7. Introduction to nipype and how do we create flexible NeuroImaging pipelines using it.
3 3
8. SymEngine: The future fast core of computer algebra systems
2 9
9. Solving Logical Puzzles with Natural Language Processing
0 0
11. Explore Big Data using Simple Python Code and Cloud Environment
18 27
12. Machine learning techniques for building a large scale production ready prediction system using Python
4 8
15. Laying out your Django projects - Promises and Pitfalls
4 35
16. Simple Hacks to Make Your Django Website Faster
0 43
20. Python load balancer: 0 to 1 million requests per second
5 11
25. Python and Riak DB, a perfect couple for huge scale distributed computing
Talks
2 13
4. Making a contextual recommendation engine using Python and Deep Learning at ParallelDots
0 4
10. Distributed scheduling leveraging multiple nodes in the cluster
1 68
13. Python Multithreading and Multiprocessing - Concurrency and Parallelism
0 2
21. How PyCon inspired me to write a book on Robotics and Python
3 19
22. Real-time processing of high-velocity social media data streams with Apache Storm
5 6
26. Automatic Data Validation and Cleaning with PySemantic
0 4
30. Use DevOps to bootstrap your startup infra and sleep peacefully at night
0 8
32. Why Python is your best friend if you want to be a Data Scientist
0 6
35. Ensuring data consistency across global data centers with low latency.
2 2
36. PyMONGO with Bottle Framework for Passw*rd Change Made Easy!!
5 27
44. Developing Social Robot using Raspberry Pi and Python
0 4
47. Building management frameworks for distributed systems using Python and SaltStack.
0 29
50. Comparing Scrapping Libraries in Python
2 2
52. Architecting large volume streaming data solution in python.
1 12
56. Using Python for Debugging Embedded Realtime Systems
1 6
61. Data processing with Map Reduce : The Python Way
0 4
62. Exploring MicroServices for Cloud with Apache Thrift and Python
3 17