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
- The proposal should have an objective with clear expectation for the audience.
- The Proposal description should be short and to the point.
- The proposal should have proper prerequisites like environment setup, library version.
- No proposal will be selected without a 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 a company name throughout the content. Mention of the employer is allowed only at the beginning of the content (presentation/pdf).
- Background image/wallpaper shouldn't contain company name/logos.
- Selection/Rejection about talks will be notified via email.
- For any questions, please write to contact@in.pycon.org.
Important Dates
31st August- Proposal submission deadline14th September.: First round Internal Talk selection announcement21st September: Presentation upload1st October: Final review and Final announcement
Note: If your proposal isn't displayed, you must have saved in draft mode. Edit your proposal to make it public.
Proposal Sections
- Security - Web Security, Server Security, Cryptography, Encryption
- Testing - Unit Testing, Selenium, py.test, Nose
- Network Programming - Socket programming, Async IO, Twisted, Gevent
- Infrastructure - Automation, Deployment
- Web Development - Web Development, API design etc ...
- Standard library - Python Standard library features, usage
- Data Analysis and Visualization - Data Analysis and Visualization
- Scientific Computing - Scientific/Numeric Libraries
- Others - Others
- 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
- Python 3k - Features, Python 2 to 3 migration experience, Writing compatible 2 and 3 code
Proposal Types
- Workshops - Workshops are in depth hands on session for 2 hours and 30 minutes
- Talks - Talks are focussed on a topic for 40 minutes.
Selected Proposals
Talks
4 32
3. Deploying Production ready Kubernetes clusters -Lessons Learnt
3 16
5. Django on Steroids -- Building Applications at Web Scale
5 7
8. Building single page javascript apps with Django, Graphql, Relay and React!
4 19
10. Boosting Python Web Applications with Protocol Buffers and GRPC
2 3
11. Using Python and microservices to fuel WebPush at Mozilla
3 6
15. Geospatial data science and analysis using ArcGIS API for Python
4 9
16. Visualising the world of competitive programming with Python
2 11
17. Scientific computing using Cython: Best of both worlds!
4 46
21. PyBeacon: Eddystone Protocol implementation in Python
8 23
22. Getting Started with Embedded Python: MicroPython and CircuitPython
2 12
23. How to Boost your Tensorflow model inference performance using Asyncio.
Talks
3 8
1. Two to Tango - Building control systems using PyTango
1 4
8. PyTorch - For the TensorFlow developers and others DL enthusiasts
3 9
10. Security lessons learned from building serverless systems
1 2
13. Taming the whale with snakes - Working with Docker using Python
3 13
14. SymEngine: Leveraging The Power Of A Computer Algebra System (CAS) To Another
3 4
16. Deployment Automation for Django Project using Ansible
2 1
22. Python for fun and profit - quite literally. Identifying Investment Opportunities using Python.
1 22
24. Using Sphinx to generate documentation for your codebase
2 2
25. Neo4j and Python - Introduction to Graph databases
4 11
31. Use Jinja and Frozen Flask to build a high performance static website
0 8
36. Natural Language Processing with TensorFlow
3 3
45. Dimensionality Reduction and Principal Component Analysis
2 4
47. Text Generation using Recurrent Neural Networks
5 48
51. Big Data Analytics Using Apache Spark On IOT in Industrial way
0 4
54. Building sophisticated data visualization web-apps with Dash and Python
0 5
55. Creating a crawler service to work efficiently at scale using Gevent and Flask
0 32
57. Python Data Visualization for data scientists (and software developers)
0 28
59. A practical walkthrough from Classification network to Semantic Segmentation, let's do this one pixel at a time.
0 39
65. From Reading CSV to Baseline Submission in 10 minutes. Hackathons unfolded.
3 16
67. Building Django applications with pre-trained ML models in the backend.
2 11
70. Making a Realtime Information Dashboard with Flask, JQuery and Firebase
0 4
74. Automated Deployment of Flask Applications using ansible or docker
1 5
76. Making the most out of web scraping : Optimization using multithreading
4 71
78. Kivy: Developing cross-platform apps with a unified codebase
0 7
80. Developing Robust Data Science / Machine learning Pipeline using scitkit-learn pipeline
2 4
87. Navigating the Python Ecosystem for Data Science
3 2
88. Top 10 tips, code snippets, patterns, and techniques from Two Scoops of Django
1 23
90. Building complicated deep convolutional networks using PyTorch
2 22
91. Tricking a Deep Neural Network with Adversarial Examples
3 7
92. Building a Recommender System for Open Source Software
3 1
97. Swarm Robotics using MicroPython, OpenCV and Open Source Hardware
15 24