PyConf Hyderabad 2017

PyConf Hyderabad

Selected Talks for PyConf Hyderabad 2017 have been announced. Please Check the Confirmed Proposals section for the Selected Talks

Guidelines for Proposal Submission

Following are the guidelines for proposal submission

  • Please mention type of Proposal as given below in the Title of the Proposal.
  • 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 should adhere to code of conduct.
  • Proposal content links can be updated later.
  • 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.
  • For any questions, please write to

Proposal Types

We have three kind of Proposals - General Talks, Lightning Talks and Workshops. Please mention the Proposal type in the Title of the Proposal. Give a Title like Proposal Type : Proposal Title

General Talks

These are the traditional talk sessions scheduled during the first day of conference. They will be conducted on Day 2 of Conference, Sunday, 8th Oct. The length of these tracks are 45 minutes.

Lightning Talks

These are short length talks that will be conducted on Day 2 of Conference, Sunday, 8th Oct. The time limit is 5 minutes. But we can extend it depending on number of talks submitted.


As with the talks, we are looking for Workshops that can grow this community at any level. We aim for Workshops that will advance Python, advance this community, and shape the future. Each session runs for 6 full hours plus a break for lunch. There will be 2 workshops going parallely on Day 1 of Conference, Saturday, 7th Oct in the same venue that hosts the main conference. Workshop I is aimed for Begineers while Workshop II is a Advaced Session aimed for Professionals.

Themes and Topics

These will be the themes and topics

  • Core Python and Python 3 features
  • Concurrent and Asynchronous programming in Python
  • Data Science and Analysis
  • Web Development
  • Python and IOT
  • Functional Programming
  • Artificial Intelligence
  • Continuous integration and Deployment
  • Testing
  • Scientific Computing
  • Cloud computing with Python

Important Dates

  • 31st August, 2017 : Deadline for Proposal Submission
  • 16th September, 2017 : Talk selection and announcement

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Workshops : Scientific Computing in Python

Submitted Aug 24, 2017

Numpy, Pandas and Matplotlib are the three pillars which support Scientific Computing in Python. Pandas depends on Numpy for speed but Pandas provides a better user experience for data analysis. Both of Numpy and Pandas depend on Matplotlib to create effective visualizations and convey your results.

After the workshop, you will have a better understanding of the packages and how to effectively use them. You will also have a better understanding of where they fit into the broader ecosystem of Scientific libraries in Python.

This workshop is intended for Beginners and Intermediate audience. Participants with some/no experience in Python can jump directly into using the packages and participants with experience using the packages will be able to get a better understanding of how the packages work and use them more effectively.


The workshop is broadly split into two sections.

In the first section, we will go through Numpy and the Numpy Array datatype. We will look at how it’s different from Python’s List & Arrray datatypes and why it’s faster & more efficient to use than the latter. We will create multi-dimensional Numpy Arrays and understand how we can use them to perform fast calculations. Towards the end, we will look at a few downsides of using the Numpy library.

In the second section, we will look at how the Pandas library builds on top of Numpy to provide easier access to the underlying data. We will create and use the Pandas Series and DataFrame datatypes.

As we create and use Numpy Arrays and Pandas DataFrames, we will use Matplotlib to visualize what we are creating and we will look at how Matplotlib can be weilded to create powerful visualizations.

Towards the end of the workshop, I will talk about what other packages are used for Scientific Computing & Visualization in Python.


The participants should have Numpy, Pandas, Matplotlib and their relevant dependencies installed. The participants are also recommended to install Jupyter Notebooks and it’s dependencies.

Speaker bio

I am a Scientific Software Developer at Enthought India. I graduated from IIT Madras with a B.S. & M.S. in Physics.

I have been involved with the Python community in Pune over the last year, during which I gave talks on Using Cython and on Using virtualenvs. I conducted two workshops at SciPy India 2016 on Using Git & GitHub and on Automated testing using the unittest and mock libraries. Finally, I was invited to IIT Madras, my almamater, to give a conduct a workshop on Scientific Computing using the Numpy, Pandas and Cython libraries.

I hope that answers both the question of whether or not I am competent in Python and it’s ecosystem of packages and the question of whether or not I am good at public speaking.




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