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ESIP 2023 tutorial (#271)
* Add timings for 90 min ESIP tutorial * Update pins in binder environment
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README.md

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## Outline
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0. [Overview](00_overview.ipynb) - dask's place in the universe.
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0. [Overview](00_overview.ipynb) - 10 min - dask's place in the universe.
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1. [Dataframe](01_dataframe.ipynb) - parallelized operations on many pandas dataframes spread across your cluster.
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1. [Dataframe](01_dataframe.ipynb) - 10 min - parallelized operations on many pandas dataframes spread across your cluster.
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2. [Array](02_array.ipynb) - blocked numpy-like functionality with a collection of numpy arrays spread across your cluster.
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2. [Array](02_array.ipynb) - 30 min - blocked numpy-like functionality with a collection of numpy arrays spread across your cluster.
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3. [Delayed](03_dask.delayed.ipynb) - the single-function way to parallelize general python code.
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3. [Delayed](03_dask.delayed.ipynb) - 10 min - the single-function way to parallelize general python code.
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4. [Deployment/Distributed](04_distributed.ipynb) - Dask's scheduler for clusters, with details of how to view the UI.
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4. [Deployment/Distributed](04_distributed.ipynb) - 10 min - Dask's scheduler for clusters, with details of how to view the UI.
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5. [Distributed Futures](05_futures.ipynb) - non-blocking results that compute asynchronously.
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5. [Distributed Futures](05_futures.ipynb) - 10 min - non-blocking results that compute asynchronously.
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6. Conclusion
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6. Conclusion - 10 min

binder/environment.yml

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channels:
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- conda-forge
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dependencies:
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- python=3.9
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- python=3.11
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- jupyterlab=3
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- numpy=1.23
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- scipy=1.8
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- numpy=1.24
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- scipy=1.10
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- bokeh=2.4
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- dask=2022.6.1
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- dask=2023.1.0
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- dask-labextension
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- distributed=2022.6.1
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- distributed=2023.1.0
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- matplotlib
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- pandas=1.4
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- pandas=1.5
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- pip
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- python-graphviz
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- ipycytoscape

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