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Euroscipy 2018 tutorial requirements
Tutorial "Introduction to Jupyter"
Tuesday August 28, 9:00, Mike Müller
- Jupyterlab (Contained in Anaconda3)
Tutorial "Introduction to Python"
Tuesday August 28, 11:00, 14:00, M.Rastgoo, G.Lemaitre
Tutorial "Introduction to NumPy arrays"
Tuesday August 28, 16:00 and Wednesday August 29, 9:00, Gert-Ludwig Ingold
- The teaching material for the hands-on tutorial is contained in a Jupyter notebook which should be downloaded before the tutorial.
If you do not have the Anaconda distribution installed, you can instead go to the Github repository of the tutorial and click on the
launch binder badge to start the Jupyter notebook on
You can get the complete teaching material by cloning the Github repository of the tutorial:
git clone https://github.com/gertingold/euroscipy-numpy-tutorial.git
Tutorial Introduction to SciPy
For the ndimage part: https://gist.github.com/emmanuelle/a4b6d396d4f24bdcd328378791722cee
Tutorial "Databases for Scientists / SQL Intro"
Tuesday August 28, 09:00, Alexander CS Hendorf
- Python3, Pandas, Jupyter Notebook
- download hubway database file: http://bit.ly/bikedb-sqltut (150 MB)
Any Python editor will do, encouraged:
Tutorial "Blending MongoDB's Aggregation Framework with Numpy and Pandas"
Tuesday August 28, 11:00, A. Herhlihy & N. Leniz
- Pymongo >= 3.6
- MongoDB 3.6+ Note: Enterprise is free to use for evaluation (and this tutorial!)
- mtools (Not strictly required but highly encouraged)
Tutorial "From exploratory computing to performances, a tour of Python profiling and optimization"
Tue August 28, 14:00, A. Ingargiola
Workshop material available at: https://github.com/tritemio/euroscipy2018_python_optimization
- Anaconda3 / miniconda 3
- A working Cython installation, including a C compiler. The C compiler is included in Anaconda 3 on macOS and Linux, but requires downloading the free Visual Studio 2015 on Windows.
Tutorial "Data Privacy for Data Science"
Tue August 28, 16:00, Katharine Jarmul
Materials are available at: https://github.com/KIProtect/data-privacy-for-data-scientists
Please follow details on the README.md (NOTE: the repository is only tested with Py3.6).
Tutorial "CFFI, Ctypes, Cython, Cppyy: The good, the old, the mighty and the unknown"
Wed August 29, 16:00, M. Picus
We will be working through this notebook
Anaconda3 / miniconda 3
A working Cython installation, including a C compiler. The C compiler is included in Anaconda 3 on macOS and Linux, but requires downloading the free Visual Studio 2015 on Windows.
cppyy, can be installed (on linux and Mac OS) via
pip install cppyy
Extra extra bonus: PyPy
Tutorial "The Hitchhiker's Guide to Parallelism with Python"
Wed August 29, 09:00, Declan Valters
The workshop consists of 4 parts, each one a 'mini-tutorial' which introduces a particular Python package supporting parallel programming in some way.
Each part is in the form of a jupyter notebook, however, you may follow along with an IPython console if you prefer. The notebooks can be downloaded/viewed here:
And to view them in smartly rendered "nbviewer" format, each section is here:
- Introduction to Workshop
- Part 1: Multiprocessing
- Part 2: Numba
- Part 3: mpi4py
- Part 4: Cython and parallelism
The Workshop assumes a Python 3 installation.
You should pre-install the following Python packages (or check if they are already included in your distribution)
And verify that the test scripts in the following directory run correctly without errors or traceback:
run_all_workshop_tests.sh script as noted in the readme file)
Tutorial "Bioinformatics with scikit-bio and BioPython"
Tuesday 28 August, 9:00am, Joris Vankerschaver
We'll be working through some of the material in these notebooks, depending on the interest and prior knowledge of the participants.
The workshop is Python 3 only. BioPython should work on all three platforms (Windows, Linux, mac OS), but unfortunately scikit-bio has poor Windows support. If you wish to participate in the workshop but your main platform is Windows, don't worry, as the workshop materials can be run in the browser through Binder.
The repository has an extensive list of dependencies, but 99% of the functionality can be had by installing the following packages in a Python installation of your choice:
Tutorial Handling Geospatial Data using Python, Part I: Base Modules
Tue August 28, 11:00, Martin Christen
Github Repo: https://github.com/martinchristen/EuroSciPy2018
Anaconda 5.2 (Python 3.6) Install the following
conda install shapely conda install fiona conda install rasterio conda install geopandas conda install folium -c conda-forge conda install basemap -c conda-forge
Tutorial "Handling Geospatial Data using Python, Part II: GeoPandas"
Tue August 28, 14:00, Joris Van den Bossche
Materials are available at: https://github.com/jorisvandenbossche/geopandas-tutorial
Requirements of part I should be mostly sufficient, you only need to be sure to have
rtree installed as well (if you installed GeoPandas with conda, this will already be included. When installed with pip, you need to install it explicitly)
Tutorial "Deep Diving into GANs: from theory to production"
Wed August 29, 14:00, M. De Simoni, P. Galeone
Workshop material available at: https://github.com/zurutech/gans-from-theory-to-production/
You can run everything on Google Colab, just visit https://github.com/zurutech/gans-from-theory-to-production open any notebook and press the "Try in a colab Notebook" button.
Or, if you want a local setup just follow:
Tutorial "Deep Learning in Python using Chainer"
Wed August 29, 16:00, C. Loomis
The tutorial will use Google Colab, at the following URLs:
Open the notebooks and press the "Try in a colab Notebook" button.