{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import holoviews as hv\n", "hv.extension('bokeh')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import dask.array as da\n", "x = da.ones((15, 15), chunks=(5, 5))\n", "\n", "y = x + x.T\n", "\n", "# y.compute()\n", "y.visualize(filename='transpose.svg')" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "x" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import dask.dataframe as dd\n", "df = dd.read_csv('aapl.csv')\n", "#df\n", "df.Open.sum().compute() # This uses the single-machine scheduler by default" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from dask.distributed import Client\n", "client = Client() # Connect to distributed cluster and override default\n", "df.Open.sum().compute() # This now runs on the distributed system" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "client" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "df.Open.sum().compute() " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "!export OMP_NUM_THREADS=8" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "gist_info": { "gist_id": null, "gist_url": null }, "kernelspec": { "display_name": "Py3 pangeo", "language": "python", "name": "pangeo" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 2 }