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{
"metadata": {
"name": "publish_data"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"IPython's Data Publication API"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"IPython has an API that allows IPython Engines to publish data back to the Client. This example shows how this API works."
]
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Setup"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We begin by enabling pylab mode and creating a `Client` object to work with an IPython cluster."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"%pylab inline"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n",
"For more information, type 'help(pylab)'.\n"
]
}
],
"prompt_number": 48
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from IPython.parallel import Client"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"c = Client()\n",
"dv = c[:]\n",
"dv.block = False"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 13
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Simple publication"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here is a simple Python function we are going to run on the Engines. This function uses `publish_data` to publish a simple Python dictionary when it is run."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def publish_it():\n",
" from IPython.zmq.datapub import publish_data\n",
" publish_data(dict(a='hi'))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 14
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We run the function on the Engines using `apply_async` and save the returned `AsyncResult` object:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ar = dv.apply_async(publish_it)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 15
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The published data from each engine is then available under the `.data` attribute of the `AsyncResult` object."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ar.data"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 16,
"text": [
"[{'a': 'hi'}, {'a': 'hi'}, {'a': 'hi'}, {'a': 'hi'}]"
]
}
],
"prompt_number": 16
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Each time `publish_data` is called, the `.data` attribute is updated with the most recently published data."
]
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Simulation loop"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"In many cases, the Engines will be running a simulation loop and we will want to publish data at each time step of the simulation. To show how this works, we create a mock simulation function that iterates over a loop and publishes a NumPy array and loop variable at each time step. By inserting a call to `time.sleep(1)`, we ensure that new data will be published every second."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def simulation_loop():\n",
" from IPython.zmq.datapub import publish_data\n",
" import time\n",
" import numpy as np\n",
" for i in range(10):\n",
" publish_data(dict(a=np.random.rand(20), i=i))\n",
" time.sleep(1)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 57
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Again, we run the `simulation_loop` function in parallel using `apply_async` and save the returned `AsyncResult` object."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ar = dv.apply_async(simulation_loop)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 58
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"New data will be published by the Engines every second. Anytime we access `ar.data`, we will get the most recently published data."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"data = ar.data\n",
"for i, d in enumerate(data):\n",
" plot(d['a'], label='engine: '+str(i))\n",
"title('Data published at time step: ' + str(data[0]['i']))\n",
"legend()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "pyout",
"prompt_number": 61,
"text": [
"<matplotlib.legend.Legend at 0x10a8ed8d0>"
]
},
{
"output_type": "display_data",
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E3ib3eDzDxbMVFWRrVRUhhJBFFy6QvY7eb29TU0NIVJTHpxlCCRg2uHZ2Nhw5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Ul1yOcQURQ2enqi/8Xvw5iIQqnBZkOTrBktI4+gbkwGxUw1xBXx7XxhYIJ651gn7my6M+6vD8xJ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\nXAzooHCcX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}
],
"prompt_number": 61
}
],
"metadata": {}
}
]
}
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