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don't preserve fixConsole output in json #1206

Merged
merged 3 commits into from

4 participants

@minrk
Owner

move utils.fixConsole calls closer to display, so they don't clobber the actual data stored in the notebook.

also store nonexistent input_prompt_number as null, rather than  , which is what should be drawn, not the actual value.

We need to be careful with this one, because currently we do write HTML-escaped text to the notebook (see #1205), so this will change the output. So if you open a notebook written by 0.12, plaintext output will be double-escaped until you run it again. The fixed output seems to display correctly in the old/bad code.

Let's not merge until we check if there's an easy way to avoid escaping to HTML a second time.

fixes #1205

@minrk
Owner

Just kidding - I wasn't diligent with my browser-refresh when switching branches. Bad notebooks (written by 0.12) loaded in this branch will see the HTML markup as plaintext, because the content will be double-escaped on load. Good notebooks (written by this branch) will be loaded unescaped ([0;31m in tact, output uncolored) in 0.12.

Of course, everything should be safe, so the only thing needed when moving from one to the other is to re-run the notebook to generate the outputs with/without the bug so it matches the running frontend.

I don't know if this is fixable, because the escaped HTML output is always perfectly valid as plaintext, so it's impossible to be certain about whether an extra escape should be made.

Note that this is not related to the notebook format, but a bug in the notebook frontend, which puts the wrong information in plaintext fields. However, one way to 'fix' the problem is to define this bug into the current notebook format, and increment the format with no changes. We then edit v2, and patch it to perform the escape/unescape around the files themselves. I do not think this is worth it, but it is an option.

Pinging @ellisonbg as notebook format coder-in-chief.

@hmeine

Would it be a possible third option to increment the nb format without adding the conversion code for now? Then, if someone decides that it is worth the extra code (and possibly volunteers to contribute it), one could already know which notebooks need which treatment.

@minrk
Owner

incrementing the nbformat without adding the conversion code would mean that all your notebooks would immediately be considered unreadable, because they are the old format.

@minrk
Owner

I suppose that's imprecise - If we define the conversion as a no-op initially, then they would be readable and the old notebooks would be identifiable as you describe. New notebooks would be rejected as unreadable by IPython 0.12, and there's no way that updating the nbformat version would not cause that to happen.

The principal reason I am reluctant to fix this via the nbformat is that it is a frontend bug, and really has nothing to do with the notebook format, as evidenced by the fact that the fixes reside purely in javascript.

I would consider this the highest priority bug found in 0.12 so far, and the principal motivation for an 0.12.1 bugfix release, depending on which approach we chose.

@ellisonbg
Owner
@ellisonbg
Owner

I will try to have a look at this one.

@fperez
Owner

I also agree that we shouldn't do a format number change unless it's really necessary, and in this case it isn't. Changing the nb format number has a pretty high cost, and we're starting to have a lot of users in the field, so we shouldn't make things hard for them without careful consideration of the benefit.

It's a bummer that this one is going to produce some glitches on load across this merge point, but there doesn't seem to be a way to avoid that...

@minrk
Owner

@ellisonbg @fperez any further thoughts on this one? I think it's the biggest bug in 0.12, and the fix has been outstanding for a over a month.

@fperez - there is a way to avoid the glitches - defining the bug into the notebook format, and incrementing the version, but I would put the costs of that (unreadability of 0.12.1 notebooks in 0.12) as much higher than the glitches themselves, which are trivially resolved by rerunning the notebook (works both directions).

I would vote for fixing the bug in the frontend (as done here), and pushing out 0.12.1 as a critical bugfix ASAP.

@fperez
Owner

Should we apply this to master and cherry-pick it onto 0.12.1? I don't like cutting 0.12.1 in the middle of a bunch of other work that's being done, the notebook UI has changed significantly, etc. So I think our options are:

  • cherry pick just this onto 0.12 and call it 0.12.1. Obviously we'd also apply it to master.
  • keep going but try to stabilize very quickly so we can release 0.13 soon.

I actually think I'd prefer the latter. The notebook is so much nicer with the menus and the codemirror fixes we just merged, that I think it more than warrants being called 0.13. We could consider making a release in a 2-3 week timeframe, which would also be ideal for PyCon. Thoughts?

@hmeine

Great idea. I also think that the new notebook is much nicer (polished) than the 0.12 one, and that releasing it soon and as 0.13 would be warranted.

BTW: In case someone thinks that the polished appearance would be diminished by doubly-escaped HTML, how about detecting this and adding a notification (similar to modern browser’s "do you want to save this password?" bars at the top) suggesting to the user to re-evaluate all cells? Again, I am not suggesting that it’s worth it, but just wanted to throw in the thought.

@ellisonbg
Owner
@fperez
Owner
@minrk
Owner

If we are doing 0.13 by March, maybe it doesn't make sense anymore to do 0.12.1, which we probably should have done a month ago, closer to when the issue came up.

@fperez
Owner
@ellisonbg
Owner
@minrk
Owner

Reviewed on IRC by @ellisonbg, and merging now.

@minrk minrk merged commit f3ee404 into from
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16 IPython/frontend/html/notebook/static/js/codecell.js
@@ -15,7 +15,7 @@ var IPython = (function (IPython) {
var CodeCell = function (notebook) {
this.code_mirror = null;
- this.input_prompt_number = ' ';
+ this.input_prompt_number = null;
this.is_completing = false;
this.completion_cursor = null;
this.outputs = [];
@@ -598,7 +598,9 @@ var IPython = (function (IPython) {
if (last.output_type == 'stream' && json.stream == last.stream){
// latest output was in the same stream,
// so append directly into its pre tag
- this.element.find('div.'+subclass).last().find('pre').append(json.text);
+ // escape ANSI & HTML specials:
+ var text = utils.fixConsole(json.text);
+ this.element.find('div.'+subclass).last().find('pre').append(text);
return;
}
}
@@ -647,6 +649,8 @@ var IPython = (function (IPython) {
CodeCell.prototype.append_text = function (data, element, extra_class) {
var toinsert = $("<div/>").addClass("box_flex1 output_subarea output_text");
+ // escape ANSI & HTML specials in plaintext:
+ data = utils.fixConsole(data);
if (extra_class){
toinsert.addClass(extra_class);
}
@@ -753,9 +757,9 @@ var IPython = (function (IPython) {
};
CodeCell.prototype.set_input_prompt = function (number) {
- var n = number || '&nbsp;';
- this.input_prompt_number = n;
- this.element.find('div.input_prompt').html('In&nbsp;[' + n + ']:');
+ this.input_prompt_number = number;
+ var ns = number || "&nbsp;";
+ this.element.find('div.input_prompt').html('In&nbsp;[' + ns + ']:');
};
@@ -817,7 +821,7 @@ var IPython = (function (IPython) {
var data = {};
data.input = this.get_code();
data.cell_type = 'code';
- if (this.input_prompt_number !== ' ') {
+ if (this.input_prompt_number) {
data.prompt_number = this.input_prompt_number;
};
var outputs = [];
View
10 IPython/frontend/html/notebook/static/js/notebook.js
@@ -816,7 +816,7 @@ var IPython = (function (IPython) {
var json = {};
json.output_type = msg_type;
if (msg_type === "stream") {
- json.text = utils.fixConsole(content.data);
+ json.text = content.data;
json.stream = content.name;
} else if (msg_type === "display_data") {
json = this.convert_mime_types(json, content.data);
@@ -826,11 +826,7 @@ var IPython = (function (IPython) {
} else if (msg_type === "pyerr") {
json.ename = content.ename;
json.evalue = content.evalue;
- var traceback = [];
- for (var i=0; i<content.traceback.length; i++) {
- traceback.push(utils.fixConsole(content.traceback[i]));
- }
- json.traceback = traceback;
+ json.traceback = content.traceback;
};
cell.append_output(json);
this.dirty = true;
@@ -839,7 +835,7 @@ var IPython = (function (IPython) {
Notebook.prototype.convert_mime_types = function (json, data) {
if (data['text/plain'] !== undefined) {
- json.text = utils.fixConsole(data['text/plain']);
+ json.text = data['text/plain'];
};
if (data['text/html'] !== undefined) {
json.html = data['text/html'];
View
13 docs/examples/notebooks/00_notebook_tour.ipynb
@@ -40,7 +40,7 @@
"output_type": "pyout",
"prompt_number": 1,
"text": [
- "u&apos;/home/fperez/ipython/ipython/docs/examples/notebooks&apos;"
+ "u'/home/fperez/ipython/ipython/docs/examples/notebooks'"
]
}
],
@@ -157,7 +157,7 @@
"output_type": "stream",
"stream": "stderr",
"text": [
- "ERROR: File &#96;non_existent_file.py&#96; not found."
+ "ERROR: File `non_existent_file.py` not found."
]
}
],
@@ -178,9 +178,9 @@
"evalue": "integer division or modulo by zero",
"output_type": "pyerr",
"traceback": [
- "<span class=\"ansired\">---------------------------------------------------------------------------</span>\n<span class=\"ansired\">ZeroDivisionError</span> Traceback (most recent call last)",
- "<span class=\"ansigreen\">/home/fperez/ipython/ipython/docs/examples/notebooks/&lt;ipython-input-7-dc39888fd1d2&gt;</span> in <span class=\"ansicyan\">&lt;module&gt;</span><span class=\"ansiblue\">()</span>\n<span class=\"ansigreen\"> 1</span> x <span class=\"ansiyellow\">=</span> <span class=\"ansicyan\">1</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\"> 2</span> y <span class=\"ansiyellow\">=</span> <span class=\"ansicyan\">4</span><span class=\"ansiyellow\"></span>\n<span class=\"ansigreen\">----&gt; 3</span><span class=\"ansiyellow\"> </span>z <span class=\"ansiyellow\">=</span> y<span class=\"ansiyellow\">/</span><span class=\"ansiyellow\">(</span><span class=\"ansicyan\">1</span><span class=\"ansiyellow\">-</span>x<span class=\"ansiyellow\">)</span><span class=\"ansiyellow\"></span>\n",
- "<span class=\"ansired\">ZeroDivisionError</span>: integer division or modulo by zero"
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mZeroDivisionError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m/home/fperez/ipython/ipython/docs/examples/notebooks/<ipython-input-7-dc39888fd1d2>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mz\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;31mZeroDivisionError\u001b[0m: integer division or modulo by zero"
]
}
],
@@ -915,8 +915,7 @@
"collapsed": true,
"input": [],
"language": "python",
- "outputs": [],
- "prompt_number": "&nbsp;"
+ "outputs": []
}
]
}
View
46 docs/examples/notebooks/01_notebook_introduction.ipynb
@@ -43,13 +43,13 @@
"outputs": [
{
"output_type": "pyout",
- "prompt_number": 4,
+ "prompt_number": 1,
"text": [
- "&apos;This is the new IPython notebook&apos;"
+ "'This is the new IPython notebook'"
]
}
],
- "prompt_number": 4
+ "prompt_number": 1
},
{
"cell_type": "markdown",
@@ -82,7 +82,7 @@
]
}
],
- "prompt_number": 3
+ "prompt_number": 2
},
{
"cell_type": "markdown",
@@ -113,7 +113,7 @@
]
}
],
- "prompt_number": 11
+ "prompt_number": 3
},
{
"cell_type": "markdown",
@@ -237,8 +237,7 @@
"list("
],
"language": "python",
- "outputs": [],
- "prompt_number": "&nbsp;"
+ "outputs": []
},
{
"cell_type": "markdown",
@@ -277,25 +276,25 @@
"stream": "stdout",
"text": [
"{",
- " &quot;stdin_port&quot;: 39725, ",
- " &quot;ip&quot;: &quot;127.0.0.1&quot;, ",
- " &quot;hb_port&quot;: 52883, ",
- " &quot;key&quot;: &quot;e7b658da-b60b-42f6-b6b0-5098f5d2e533&quot;, ",
- " &quot;shell_port&quot;: 51742, ",
- " &quot;iopub_port&quot;: 41869",
+ " \"stdin_port\": 53970, ",
+ " \"ip\": \"127.0.0.1\", ",
+ " \"hb_port\": 53971, ",
+ " \"key\": \"30daac61-6b73-4bae-a7d9-9dca538794d5\", ",
+ " \"shell_port\": 53968, ",
+ " \"iopub_port\": 53969",
"}",
"",
"Paste the above JSON into a file, and connect with:",
- " $&gt; ipython &lt;app&gt; --existing &lt;file&gt;",
+ " $> ipython <app> --existing <file>",
"or, if you are local, you can connect with just:",
- " $&gt; ipython &lt;app&gt; --existing kernel-faac4917-d0e0-467a-8467-d3c4d86a3ecc.json ",
+ " $> ipython <app> --existing kernel-dd85d1cc-c335-44f4-bed8-f1a2173a819a.json ",
"or even just:",
- " $&gt; ipython &lt;app&gt; --existing ",
+ " $> ipython <app> --existing ",
"if this is the most recent IPython session you have started."
]
}
],
- "prompt_number": 8
+ "prompt_number": 4
},
{
"cell_type": "markdown",
@@ -361,14 +360,14 @@
"text": [
"",
"Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].",
- "For more information, type &apos;help(pylab)&apos;."
+ "For more information, type 'help(pylab)'."
]
},
{
"output_type": "pyout",
- "prompt_number": 12,
+ "prompt_number": 5,
"text": [
- "[&lt;matplotlib.lines.Line2D at 0x43a2890&gt;]"
+ "[<matplotlib.lines.Line2D at 0x11165bcd0>]"
]
},
{
@@ -376,7 +375,7 @@
"png": 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KENI/dkzdg4/aoskrBQ+Ya9OYpuCp/w5kB1k7O0nQMmkFr0Lwfgp+dJTc1GgKm/szBwYI\nwVsFHw94Cl7VogHit2l4aZJAmvSpgpcRmrIEHzaLJm8UPKBO8Bs2pOtIRAnTPHhqzwDZQdbOTmD6\n9Nwg+EOH5BQ8JbtUKpiCP3Qo+YlfqqAxBz+YQPCyRM3mwQPxZ9KIFLyb4GVmYKt68EGzaApawT/y\nSLA6y6owUcFTgucp+HPOIW1NktR0ZtGwataL4EUKvqcnuaJcQZFLCl7WajFdwZ99NvltikVT8Ap+\ncDAeS8c0gqc58ABfwU+aRCbBJNlemVIFsh48O5FHFGT1UvDV1bln0+QSwQcJsgLxE7yXgq+t9e5j\nbqgGWWUI/sUXM0VKXip4lTtdnARfVWWWRUMHv/sxt6ODTMBIakEFCj+Lhs5inTpVTcHz/FE/BT9n\njiV4nQhj0bAEH7dFIyLM6uq0PQNEo+BluOPuu4HHHyd/R7VcH2AVPPc448ebo+D9LJoJE5JbEo3C\nrxZNRwdpY1VVdAp+YIAMlFmzLMHrRC5aNI5D+lF5efZ7F1wALFyY/l83wadScsL18OE0wff2ptOC\ndSNWgmfL2ppK8END5C5vCsH7WTRUwZtA8KLrQ+0ZIDoPnk71PuccEmjNJZhM8GyxMSC4RROnCBke\nJouncCqW48orgUcfTf+vc6ITnQ/iR/BdXSRT7L33yE9U/juQYwo+jnVch4ZIh5Yh+GPHom+PX5ok\nVfAmWzSHDxPiBeSzaAA1BU8Jfto0q+B1IohFQyc1sZlBcdqIKgXZdHvw48b5WzR0PHzuc8ATT0Rn\nzwAJErzqqk5xKvjx4+VmW55/fvRevV+apCkK3ivIqqLg3RaN+zP9FLwleL0Ikgc/MEDGN7tcXpx9\nVDbtFPAn+NFRMgYrKuQsmnHj/IUojUfdfjsh+KgKjQE5puDjJHg/BX/oENnm5Mlo28Pz4GlKpCkE\n71eqgCX4sApeVNkvlwne1GJjvOCfTF9z58AD8T5l6lTw9GZRWqqP4OmC3/PmERtp06Y8VPAqBE8L\n6ZtE8AcPkt9REzzrwZeUkB96Hmip4FywaIIqeFWLxnrw+tDfT9pVwhQVl7Fa3P473S8uESJ7wwT8\nCZ6tiyRL8DIWzbRp5Ann9tvJHJ+CVvB0u7gIXsaDpwTf0RFte1gPHsgkc1MUvArB61Dw48eT88K+\nRwl+6lSikHJpNqupBM/zhmWCpaoE39sLLFgQvJ1uqCh4v1IF9LN4lU15244fL2fR0PHwF38BfPBB\nnij4oFk0cRI8vUh+d+EDB8jvOC0aINOmMSHISouhVVbqz6LhDT7q744dm0kYNBOhspKQSdTXRSdk\nCX78+PgJ3r1amKxF4yZ4rz7a3Q28+Wbwdrqh6sF78QpL8H5BVioOVQj+/POBRYuiU/C+KzrpRHFx\n+u8gBB9XFo1MmuTBg+QRKw4FzxI8DbR2dxOiKy1NVsHTx2Gqth0nM7gGqCl4L4uG5jeXlZHv3N2d\nno7OBqqoD19bq+c7Rg1ZQho7lnxn3jmOAiIFr9uiGRhIP5HpyAXX6cGrKngVi4biW9+K7sYdK8Gz\nUCF4egFM8+AvvDBeDx5IK3iq3oHkCb6sjBAOVTns4BodJemktPYHzZ4aHeXnKXtZNMPDZJ/i4mwF\nzxL8OeeQQXTJJXq/a1SQJbaSEnL+ensz7c6owCP4oArej+AB8r145QVUEYUHX1REbqyifku3VQmy\nUnzmM3JtDYJYLRoWplo07ILPXguSHDwIXHZZPBaN24Pv68sk+CQtGpbQedf0xAmisuk2qZS3TeOl\n4NnZiVTBU7gVfC4FWlWUa5w+fFCCZ2vBU3j1UdpndPVh3QqerW7qpeLZCVEi7mDLdsQBS/AuUMIq\nL/d+1DpwgBB8EhaNiQoe4Hvm7sdRwJvg3QqevebssbwUfK6lSuYSwUdl0QD6CF5nHjz7WX4+PBUg\nXnW2PvqIPAFEFVR1wxK8C3SweXnFPT3kPZFF09UF7Nihpz2iIKspCt5N8O5rxFMrXufWS8EPDKTf\n81PwluDDI4xF486D99rPdAXPEryfgi8rIzc3EcHzBE+UsATvggzBHzwInHsuKdXLI/iXXwa++U19\n7eEFWWkOPGCWgndfI97amCoKXmTRyHjwuYJcI/ggCt5LhFAy1NWHVTz44mJip4gsFRWCZ5/+LcEb\nmkXD3oVFJMQSPM+iOXqUEJsOuD14E4OsbFqj+5r29WWrOa+bpxfBswqeZpRQWA9eP+LKg09SwYtW\nDuN9lowH72fvWoLnwFQFP3EiX8EfPapveUFRmiStBU9fMzXIKiJ4mSCr29N3B1mtBx8t3JUkAXLt\nBgbS8x94yCUPHpAneBmLprTU26JxZ9BEDUvwLsgQ/IEDmQrePWvy2DF9BM+zaExT8KoEX1ERrYKf\nMoVk7/jlLZsCFUvB/b2jBE/Bp1L+cxmCWjRJKHhAjeBl/Hpr0UBtRaekCN7PoqERc/eAoxaNjuny\nshaNqUHWMAreL01SpOBLS8nN9/jxYN8pKvzqV8Df/m326yoKPs6nNVEZWz9BwSP48nLSl3k33Sgs\nGpUJU17lCoIEWf0smrhSJIEcUvBska0oQQebl8o8eBCYMYP8zbNpjh4lj7A6VLXIonFn0eSrgmc/\nT6TgR0bI57GTf0wMtP7sZ8CePdmv5xvB8/LgUynxfiYoeBG32CyagFAleK9iVjqh4sED/EDrsWOk\nQ+sItMqkSZps0fBS5rwUvF8WDS9NkhIRO33ftEBrTw/w7//OH/i5RvB+beApeK/9dCv4qDx4lSCr\nJXhFgpeZAqwDtHOICN5x0h48kK3gHYcQ/MyZenx4rzRJE4Ks7OMwTwmpKnhZi4ZNk+QtmGBaoPXl\nl8nvsAQfpx0XxqJxX3Ov/aJIk0zCg/ebJBn3LFYgQYJXWdHJb0EJnaCEJVKZnZ3kQlNCcSv4U6fI\nvlOn6iF4Lw+ezYNnFwKJE7qzaGSDrKyCzwWC//WvgeXLxQQvS0hx3sy7u7OrSQL+NxkvBR+XRaPi\nwceVRXPqFHkvjjpCFDmj4OO2aEQqk/XfgezJTkePkiyO6upoLBo6SE6dSk8gKi4mbY56+UAedHvw\nsmmSfgreJA9+aAh4/nngs5/lXyNViyYuO06VqP32E90YBgf13riiVPBhLJq47RnAEnwW/Dx41n8H\nsi2ao0dJ5cSaGn0K3k3wx4+TASRaCCRO+NWi4QXc4lLwcXnwf/gD8Nxz4vdfew2oqwNmzcotD549\n3yyCZNEA4rYPDJDxkk8ePK9/W4IXwGSCd1s0x46lFXwUHnxlJeko1H+nSCrQGmcevIqCr68Htm8H\nnnpK/Tup4j/+A1izRvz+r38N/Omfih/dTSV49nyrtEFE8CJlOzhI+nO+KHjRdY7bfwdyiODHjYvf\nouHdhdkAK+Ct4HVZNG6lfuhQNsEnqeCDlCoIkgevouDPPx/YvBn4X/8L+NKXorWvenuBd94Bdu3K\nfm90FPi3fwP+7M/EBGcqwdPVs9wIquBFxDcwoJ/go/Lgw0x0MlLBt7a2or6+HnV1dVi/fj13m+3b\nt2P+/Pmor69HY2Oj1IFVCX7MmPiyaMIq+CgtGkqOpij4IEHWoHnw7GDzU/AAcPnlwBtvkOtz1VXR\nnZ+eHtLWf/3X7Pd27CBtmzNH/OhuahZNUILn2XKA+Pvni4L3y6IxkuBXr16N5uZmbN68GRs2bEB7\ne3vG+47j4I477sAPfvAD7Nq1C88884zUgU21aOgF9SL4OIOsvDRJwByCT3Imq5eCpxg/HviXfyHk\nsX+/9NdSQm8vcOONfIL/9a+JegdyS8GPjmY/Pcq2IYiCr6nR13+T9OC9smjirkMD+BD86Y8ZavHi\nxZg5cyaWLl2KrVu3ZmyzY8cOXHLJJbjuuusAALWSC2GaSPCOQ2ZFlpSISSjpICslS5MsmiRq0bBF\nr7wIHiAToKqqonsC7O0Frr2WpK7u3Jl+vbMT2LgR+Pznyf+6PPg4buT0uvLWfg2aBy9StlFYNDaL\nhsBzTdbt27djzpw5Z/6fO3cutmzZguXLl5957eWXX0YqlcI111yDmpoafPWrX8X111/P/bz777//\nzN+zZzdicLBRqpGDg8DkydETPFXLdFk5NwmNjhL/e/r09GsiiyaViiYPnip4mgNPkS8KnlVfPAVP\nv39RUZrs/AgeUJt3oYreXiJAbr2VqPj77iOv33cfUe8XX5xugyjIaJqC9yLJoHnwohtcFBZNVLVo\nZD14XhlxWYJvaWlBS0uL/4YSCL3odn9/P/7rv/4LmzdvRm9vL/7kT/4E77zzDio5t3CW4D/4QN2D\nHxqKdkV5VknxLJpjx4j1wnbeCRMIkdPFeKlFMzAQXR48PS6LJBU8nQwjW6rALw+eDdq6FTy7eAj1\n4WUIXqW4nSp6e8n5/+xngb/+a0Lsb78NPP10pqKn58fdh020aET+O21DkCCrl4LXmSapuxYNvTZh\nsmgch1g0Mlk0jY2NGbHMtWvX+u8kgKdFM3/+fOzevfvM/21tbVi4cGHGNldddRU+/elP4+yzz8as\nWbMwb948tLa2+h5Y1aKhed+8O6iufGc/gnf77wC56GPHEjIfHQXa24GzztJn0bg9eDpwTPLgdWbR\nyKZJAmkfXlbBR0XwPT2E9BoaSD9oawNWryZEzzqWRUX8onlBCD7qWcteBB8miyaOIGvS9eB5fe3k\nSXLeeOclSngSfHV1NQCSSbN//35s2rQJDQ0NGdssXLgQr732Gnp7e9HR0YE333wTV199te+BVQm+\nrIyvwj78EJA4nBTcBO/ujB9+mGnPUNBA68mThGjKyvTlwbstmqIi0klMIXi3pcJe05ER8uMmr6C1\naNwTb1QUfNQWTVUVuTa33grccQe50Tc18dvh7sMqBF9SEk9lVT8FrzMPPlc8eK8g68gIuf7Fxfwn\nlRMniPCLG74Wzbp169DU1IShoSGsWrUKtbW1aG5uBgA0NTVh0qRJWLlyJebNm4fJkyfje9/7Hsby\nCli4oELwlER4+3R3642+04HGI6H2dhILcIMGWvv6iD0D6M2DL3FdpcpKsywakQdP1bvbUlNR8O40\nSZZ0aMlgEywaWl/k1luBBx8kk5/c1w3gP76rEDyQvtYiAtaBoArecci15e1bUcFfAW1ggAiiwUFC\nlMXFwdsN6M2DZwWMlwfPjgPeNZbpo1HAl+CXLFmCXa4ZHE0uaXLXXXfhrrvuUjqw6oIfIoLv79c3\ncNmLxLNoTp4kat0NGmjt6iIBVoAMwqEhdTXhBo/gq6r4Cl7XOrAq8CpVIMqHDlNNkj2XlGhMUfAA\nsHAh8Lvfkbx7UTvY/spmbsmCeuDuPqATojIFgDfBDw2lrSg3vILM5eXpSqkS+tATSWTRsDcV3vcU\nVeaMGonNZKUnVcZL9CL4vj59BO/nwZ88mZ29AqQVPA2wAkS16siFd3vwAHDZZdmxAJMVvBs6atEA\nago+Sg+eJfhUSkzutB3sd6ffVyVxII5rLSpTQI8vIniRPQOIPXh6XXWlgCbhwbPb8SyagiN4epf3\nSjuiYNOPeAqeZiaEhZ8H76fgaYokhY5AK2+yyXPPZUfjTUyTFBG8jlo0APnOXV1ygydKi4YGWWXg\nvtGo2jOAOsEfPw48+qjaMbwsGq8btB/B+yl4HTeuJDx4P4um4AgekPfh6eOPyKKh24SFnwff0SEm\neKrgWYLXEWjlWTQ8mJhFE0TBe1k+PAV//Dj5PD/fNi6Lxg86CF61XMHbbwM//rHaMbwIXqTEAfEk\nJ8A7TZIqeF0EH3c9eLeCtwQPNYIXZdFQEtahznRaNICeQKsswSdl0XjVoolDwR8+LBe8isqicRzx\n9+TBre7iUPC9vfyJN17wInivc5nPCt7LcWDHgbVoPoasqvILstJtwsKt4Pv7M62fJCwangfPQ65Z\nNCJbTTVN8sgROYKPyqKhGSOymR8iD14FqkTY16eX4P0UvIjg41LwSXvw1qL5GEEUvIjgdSv44uLs\nfGORRcMqeLdFo0PByxBALhF8KkW29ausKKPgZQk+KotGxZ6h7dCh4FWudW8v2V5ljHipYPodeDfo\nIAqe3kySUvAqpQpsFo0CTCN4d8dgbRrHIQTPs2ioB08X+6DQFWQ12aLxIngvP1bkw7OERwcUJZIw\nCj4qi0aRh/xQAAAgAElEQVQlwMprh6pfDART8AApfiYLLwVP6zXxyC6Igqc3bl5s4YUXgG9+U77d\n9PNUPXivUgWqQVZr0XwMVYLnqbCoPHggk+A/+oh0XJ4ymDSJBPs6OjInQukIsuaCRaMaZAX4Przj\nZF6DVCrT9+Tlwct68FFZNKoKPikPHlCzabwIHhCrcdHcB699vNIk9+4lPypIwoO3Fg0Hpil4HsHT\nzxfZMwBR9QcPkt+sF1toQVa3EvIieJ6CHx4m56+I6ZXs4OPNZO3tLTyLRjWLht5IdRK8SI2rKviR\nEfK7pITfhzs60nX/ZZG0B28tmo+hI4smSoJnVaYowAoQpV5UlOm/A9HlwfNgqgfvpebcCp6nvNjB\n57ZoaHkAmYETlUXDlimQQRJB1qgUvCrB8/Zhrynve3V2qhN8EjNZbRYNB7IE71WLhpKE7iwaINOi\nEaVIAoTcJ0zIJvg48+Dp423UVQbdCBJkBfgKnkd2bACMp+CB3LJokpjoFFTBe5Gk6Ibplwfv3oe9\nkYgIXkW40AJ3KvVsdE90Ki0lbRgdTb9vCd4DSVo07OAQKXiAvMcGWAE9Fo2sB19aSjp11FUG3fCr\nRaPiwfMerWUUfJIWTdgga1xZNJWVagTvVaoA0Kfg2f6jw6KhfUil9IOI4OmyhXT8yWbRpFLZ19kS\nvAfoyROVKgCiy6Khn+9l0QDkvagUvMqCzHHbNDoVPC/7wc+DB5LNotERZFUtRhdEwZ9zTjxBVj8P\nPoiCD0LwKhARvPtmIRtkBbJtGkvwArB3US+LJg4PXmTRAOQ9ngcfV5AVSCbQqjOLhqdm2aJ07huA\nioI3yaIJ68GrBll7e8k6BrxSvSIEDbL29fnPgGVtRPamzfteqhaNqv8OiAne/VmyQVYg+wZoCV4A\n9i4qsmiKi5O3aBYtAi6/PPO1OPPggWQUfJBSBYBYwfMsmsHBtFXFZtioKviosmhUg6xJePBxKnjR\nNaeTB0Wzk3nWEyV41s/2QpB5BVEQPHud6e8o6/eLYDzBuy0AXhYNXSwgLLzSJP0smm9/G/jv/z3z\ntfHjyZ1btnOK2mQywQe1aFQVPM8Tpso5KgW/ezfwxhve2+RCkJUqeN1BVpGC96rL497Py6KhkwtL\nSsS1i9zQreDZa+MVZHVbQ+z3TEq9AzlI8DwFX1OTvEXDQ3FxuqRtUKh48HFbNDSHmWYsULVNH8F1\nKfihIT7hFBeTz4nKg//FL4Cf/cx7G9UgaxITnYIo+CiCrHQ/90xeUZC1ry+doSbrwwfx4EWlCngK\nXtaDZ79nQRO836DzI/i+PqLgk7ZoRAhr05hs0bg7NZ2kRInf63Fdh4IHiE0TlUXT0eFPpLlSiyaI\ngvfz4EUzWXUp+M5OIqrowi4ySNKDZ68je34KmuBVFLwoi2b8+OgJ3s+iESFsJo3JQVae38leU515\n8CLL4Kc/Bc47z7+tQSwamQBf2CBrHLVoenuj8eB1KXgvgp8wQU24BPXgeTyky4P/6CNL8ELIWDQy\nCn5kBHjkEfljAdkevKpFA4TLpKFKuEjyKsWt4EV56zIErzqTVaTgb7hBblJLEItGluDjDrIGKVVw\n9tnku8isoAaEq0WjquBFFk1HByF4UxS87EQnIPMGaBW8B2QsGhkP/sQJ4J57vLcRefAjI+Qi1dR4\n789DGAWv4r8DyVs0QLaCF6k5WQXv5cGrIKhFE4WCTyLIOmYMIUvZvhhFLRogmIIfO1a+X0eRB08R\nVMEXLMHLDDpdWTR9feTHayq/yKLp7CTHUJn+TBFGwavYM0AyFo0fwetQ8IODwZSZu11BFLzf+cyV\nIGtVFXkClbVp/M53FAre/WRCPfgxY8xQ8LIrOgHZBC8TJ4oCxit4rzxrQN6i6esj6YpexxMRfFD/\nHQgXZFVJkQTMVPBhPXg/i0YWUVo0cU90otvL2C0jI+TcVVSoEXxcCt4dZGXPd1CLxoQ8eGvRQN6i\nYVdKCUPwgLfyEeXBB/XfgfAWTS4SPB0sOvPgrUWTCdlMGkq4qZRegvcKsqooeLYP0fFG540EsWhs\nFk0mcoLgRQrecchJlMmiocSuQvCUhIKmSALhLRqVwZ/rWTRBgqyycOfo+6Gvj/QpE4OsgPy1Zm9A\nuhW86oIfQPaNgT1OUVHmDYDNookyDz6KIKsleIQneKrqRH4gi6AKPqxFk88KnjeY6DVyHD0K3i9N\nUhZFRd5Ls7nR2SlHojoUfJDvJZtJw14DExS8V5AVyDznJubBq0x0shZNSIKnj58yj98yBC9Kkwxj\n0cTpwZsUZB0aIqQqan/cCh5Qs2k6OkjuuF+N/SSCrEA8Cj5okNVLwXsFWYHM78V68FHnwUdZi8YS\nvAe8smhoZ5IJoIVR8Lli0ZjiwQ8O+mdTxO3B07bJBlo7O4GzziKD2mufJIKsgDzBB1XwfjdUryCr\nioJ3Pym4FbyqRRNEwauUKrAErwAdCr6yMjqCpyRkLRo+whC8KIvGS8GHJXiVTBpKLl5E6jjJBlmT\n9OB1KXj3dRVZNFHmwVPidj+pqXjw7uNaiwbhSxVQi0ZGmVGC96pK5+XBh7FoCjEPXkbJ8fLgeQp+\ncNCfcGSgatH4TZOnTxUq8yPizqJxK3jZmvBB0iRp0kPQNEkg83yz14Cn4L/4ReDllzNfCyIEUim+\nv24VfEiEVfBxWDT9/eEtmnzOgxdl0fgpuSB58HFbNHSSjeicqqp3QJ8HLxtkDaLgh4cJ6XnduEQL\naJeWepfW4Cl4nkXjOGTceOXBv/8+cPRo5mtBPHiA78OrBlltmqQLhWTRBFkMW9WDnzYNOHBAfRX6\noPCqRRPEgzcpyCpT6Eo1wAoQknCctBIMSkhRevAyT0u8Mef31AbwFTzPounuJscoLRVbNLyJaEGF\ngCzB24lOCsiFLJqwFk1FBVE0PGtodBQ4ckS8r6pFc9ZZwOLFwFNPqbczCKLw4KMMsqp48NQe8CLS\nIAre3Q4TPXgZkuQpeL+nNkBewdMnKEBs0fBKSQRNO9VN8FbBI3wWDUvwMgo+lYrfogHEA+u114Db\nbhPvp0rwAHDXXcDDDwd7YlBFWIKXUfA0w0GHgjfBogHiJ3h6HWpqSOlaWqVUBBkFzwuy+pUp4O0n\nUvD0BguILRoewUep4INMdHIc0n/o8pJxw5fgW1tbUV9fj7q6Oqxfv1643fbt21FSUoJf/epX0geX\nGXDsAHArdVUPfsIENYIvLU0v9hzmAk2eTKpZunHkiLc/r+rBA8DSpSSou3272n5B4EXIMkWn3Asw\nx6HgdVo0qrNY2XbERfC00BhAPPXx4/2D/rIWDU/B+1k0Xgt+AJkKniV49zUYHSU3Kx7BR+XBFxfz\ns20AcRZNTw/5O0ihQh3wJfjVq1ejubkZmzdvxoYNG9De3p61zcjICL71rW9h2bJlcBSkoy4PXjaL\nZtIkNYIH0kWaUinvz/dCbS3AOW1ob/f2y1U9eIDYQU1NRMVHDb8gq9dgLyrKvm5RB1mDWDRRKHjW\n3og6i8bdRvfTJG+4xqngRWmSLMHzLJrTp9NpqiyiVPBFRZkrlnltS/takvYM4EPwpz++1S9evBgz\nZ87E0qVLsXXr1qzt1q9fj1tuuQWTJ09WOrhOD16G4CdOVCf4yspw9gwgVvAnTvgTvKqCB4CVK4F/\n+ze1FXyCwKtUgYyac/u4oiCrrjTJIBaNl1IOEmQF9Cj4IKUKgGyCX7MmeyGcJBU8vaGyHnxVVboa\nLEVnJ/ntvsnp9uDd10bkw4uyaIwm+O3bt2POnDln/p87dy62bNmSsc2hQ4fw7LPP4q677gIApBSk\nrirB08ccegdVtWgmTVLLgweSJfggFg093vLl/gtGh0UYDx7I9uHjUPC6LZpc8OC9FPxvfwscPpy5\nj4wdplPB8ywa1oMvLibbsH2FEnycCp5uJyJ4nkWTNMEHoI9M3H333XjggQeQSqXgOI6nRXP//fef\n+buxsRF1dY1KBA+kCYQGQGmapEwWzdSpySh4kUVz4gRpz8gI36MLquABEmy94w7g7rvD2UteCEvw\nsgqeDjwdaZIyCt5x4iX4IIQUJE0SyCT4o0eBnTuBZcsy95EJaAdV8Lxqkn4WDZAOtNKYhxfBB7lh\n8soV8PqjKBdeZNEEWY+1paUFLS0tajsJ4Ekf8+fPx7333nvm/7a2Nixz9YY33ngDt32cCtLe3o4X\nX3wRpaWluPHGG7M+jyV4sr2aggfSj9mU4CsqyEkfHRUTJZBW8Pv3yx8LSHvwYTB5MvDWW9mvU1Xf\n28vvBEE8eIr/9t/I7zffBK64Qn4/+hgssw4sL/hcVkYGom4FPzoa30QnmoNdVkYIRxQID+PBm6Dg\nX32V/HbfwFTy4B0nLSBkFLxskDWVAs49N/26O9Da2UkCxnEreC+LRpcH39jYiMbGxjP/r127Vu0D\nGHgO4+rqagAkk2b//v3YtGkTGhoaMrbZt28f3n//fbz//vu45ZZb8PDDD3PJnQdViwbIVOvUokml\n/NVZ0CBr1BYNILZpwij4VAq46CJg3z61/R57DGDu6Z4IU6oAyFZzIk8/7olO7gCfVx580CwaHUHW\nsAr+lVeABQuy+58MwRcXZ6tZWQUvE2RlLRogO9Da2Zmu9skiyjx4gE/wjsOfJGmCReOr09atW4em\npiZcd911+PKXv4za2lo0Nzejubk59MGDEDy7D6sY/NRZXx+xSkyzaMaNExN8UA+e4rzzvJ9YeNi7\n13vyFYswpQqAbAUvqkUTdzVJllx0z2QF9HnwYbJoHIcQ/I03BlPwQLYa16ngRRYNBSV4nQrezUWy\nBE+dA/ap15Qgqy99LFmyBLt27cp4rampibvtY489pnRwdpUdkU/sR/BUMUSl4HVZNG4FPzJCHv3r\n670VfFCLBgBmzgTefVdtn8OHiW8oA69SBaOjwRS8iOAdJ740SfcsSi8PfurUcO1IIovmP/+TPNkN\nDgLz5pEJdyxkb6ZuNa5Twff0ZBM8ex1OnSIE/8EHmZ+vMw9e1L/dBM87pikEn+hMVnrX85pZJ6vg\n/R6//Qh+dJT8uD38ujryEwY8gu/oIHVqamqisWgAouDdA8APhw7JE7zuLBqvIGuc1SRZ9Rh1qYKo\na9GIFPyrrwKf+hR/lqisHRa1gmeFlciiScKDl9nOFIsmdBZNWFBCEBGZewCwBM/aADIK3isPniop\n95PEj34k9z28MHEi6ZBsEPjECUL8XsuR6SB4VYvm8GF5wvEieJ0KfnCQnDsdFo1XmiyFrEWT9ESn\nMB78K68A11/P/36yN1NdCp6XB+/24HlB1ksuibcWDcC3aHjbsQp++nT19uhCogoe8PfhvYr4BLFo\nRAM86ECTQWkpifjT1C6AEHxtrTfBh/XgZ84kBK9Sl0bFogmr4N0+st+CH3GlSapYNKaXKuAp+Pb2\nTAWftAfvtmi6u0kfrKlJv85T8NOnx1tNEpAn+JISIkpOnyZjPykYT/DuQe9l0YgG78gIuSg1NeJB\noWMijRfcNg1V8F7LkYX14GtqyBMDe2PxQk8P6ZBhCV6mFg0AzJiR+YQRdZA1aBaNqUHWoAr+3XcJ\n6cycye9/KgqeJWtVBU8XCHFbNMeOkXaxdikvyHr22WSMsIQbZS0aup2b4HnCJJUi37W9vYA9eEBd\nwYssGq8MCdrx2MUE3IhSwQOEzNlMmjgsGiCt4mVw5AhRRbTOhx9450xFwV94YWYQ2G8ma1ylClh7\nwNRywWVlaeHiBXcb6fe69lryW6dFI6vgaf78yEj2wiJVVeR9d2IDz6Kh5Zz94jgy0O3BA+S7WoL3\nGXQqQVY/gi8uFh8vaoKvreUr+CgtGkAt0Hr4MNm+tFTOqw5r0Vx4IbBnj//nxV0PXsWiSWqiUyol\np+LZapJA2i5kCd4temTPNc+i8bvmRUVpkuTdSOj+rP9O2+lW8DU12ecgKQ+edw3Ly9Op0EkhcYL3\n66QqaZKiJwGWbETHi0PBswTf3p4meBGB6FDwKoHWQ4fIqlDV1XI2TViCr6sjBE/JxZRaNLIWTRgF\n39/PnyCjAr+xMzzMJ7y//EvguuvI31T0uFVw0CCrn4IH0t+fd5zSUvLjJnhWCDkOecrkEXzQfqJS\nqkDGgwesRQOAfHkvMhGVKgDks2hYsqmsTI7gg1g0YdukYtEcPkwIXqZmOBCe4CdNIgRDb3xRp0mq\nWDRsJUORrRc2yDoyki5BGwR+BE/VuzszbMOG7BRE9iYWJsjqd82B9I1B9KRQVeVt0XR1keOUlma3\nPWoPXoXgy8tJvn5BE/z48eSCieBVqkDVogGSU/A8i8Yvi0aXglexaM45h1yTsApexo8FMm0aU+rB\nswqeKlx3YS0gfJA1qJ1AIUPwMoQblOCDKnganBUdp6rK26LxmqeQRDVJL4IHCpzgx41TI/ggM1lN\nIHhRFk0cHryqgq+ullfwYYKsgBzBDw4mN9EJENs0YYOsYfucH8HLts/dB6NW8KxFwyPGMWP4Fg29\nBl4EH8aDly1VIDPjFUjf7CzBhyB4lSwaIDvqLjqObuRCFg1r0cgoeK9SBUEIXqSYBgf12FUyFg1d\nCs6dg+0meLqakMx3dIMq2LAE7xUfAMIpeNlSBe40SVkFTy0aWQXPjpMkFbyqRVNUFKyP6IIRBK/q\nwYtmspocZGUtGsfJDLJG6cFPnJiue+MHVYIXWTQDA/Jqrq6OpEqKAo6lpYR8ysrC17WXsWhOnybX\nxJ26x5tQU1wc7PqYpuB5PnbQNEkdCp7nwXtZNLTtdP1kHR786ChfYKlm0YwbF916DDJInOBlPHhe\nqYLR0cyOmEsWzenTpL0VFdEr+FSKqHg/H95xCMFPnapm0fAIvquLnEuZ4CFV8LycaCC98LmOpysZ\ni8ZtzwD8wl5BA6y0HXEQvKyCd2dyBbVoolbwrEVDn7DYazM8nF3VURZugqdPp25yVvHgKyqStWcA\nAwjey6LhqTo6OAYG0rXg2dd5MIXg29sz1TsQvQcPyAVaT58mg2PcuPAK/vRp+cfS2bNJieKBAf75\np99fB8HLWDRsBg0FzwoJGmAF0n01qNqk0Kngg3jwQSY6Ad5pkgDw138NXHWVuI0iiyZM0NpN8KJr\nozrRKWmCT7zY2LhxYo+YEhx7R2aDeGxnMp3gabpaT0/afweit2gAuUArzaABCMHzFihxQ0TwIyPy\nBD92LEmX3LePP0hSKXIOwgZYATmLRqTg3QQfNMDKtsMUBR8mTZIVZ7LHozcGUQG5jxeIywCr4E+d\n4hN8mDgaj+B5n6XqwSdN8EYoeJFaFK3ww0vDkw2yJpUHD6RtGpoiCURv0QBygVbqvwPhs2gAtcDS\nhRcC77wjPv+lpclaNDwiDUPwuoKsUXnwQevBqyp4lcwo+l1HR8UKPswTURiC98qiKXiC9/LgVfKs\nwyr4qLNogLRNwyp4+ujJm0iji+BlLBqW4MNk0QQl+LY2b4LXoeB1WjQmKHhdWTQ60iQdR92DVxlz\nxcXkeH194iCrVfDZSJzgvTx4lZmSpmfRAJkKnhJ8aSnpNKL6OLoIXlXB+xE8XaTFHRQtLia2igrB\n19URghcNTp0KXqdFY3qQNY4sGrauPV2n1Q9BFDyQtmlEa+aG8eDdpQpEpK060ckSfECC163g4yB4\nmirJEjwgtml0efCqFo1MqQJRp06lyOsmKvgwFk0UQdZc9+BZi0b2WOx+qhVC6TjxsmjiUPC8ICvv\nOlqLBt4evNdKKWEInjfRKS4F396emUUDeBO8DgU/eTL5zl7pqIcOZQZZ/RS812AqK5N7VKe48ELg\nvfeiV/BhLJp89uB1WDSy/ju7n2qFUGpnmubBm5wmmXgWTRgP3m3RmK7geRYNICZ4XRYNmwt/8cX8\nbVQtGj+CV1Hw55+fzpYRfZ4Ogqfnkl060Q2RRXPyZOZrJnjwMgqenZErQlIKvqgouEVDv5cpWTS8\nvrByJQkKJwkjFHxQDz5IFk2uWTQ6CB7wD7SqWjRe50uV4MvKCMlHbdEA/j583GmSYW5cvCcLFrKl\nFIJm0QRV8PQJRpWQqYJ3p0nStofNg2ftO9ENS3ZFJ4CIqvPPD9YeXUic4MeMISeTBu1Y6PLg2Y6e\ntIKnWTQ0TRKI3oMHvAOto6PA0aNkFiuQvul6rerkNThLS9Xrb9TVRW/RAN5C4PRpYOdO4NxzM1/n\nefAmBFlrajLrG7nhXuxDBHf/C1KqQEXBs5MVVRX88eNE9ND92JucTgV/9CgwZUr2dioTnUxA4gRf\nVJReaNcNr2qFPIKXyaIR5cHHlSaZlIKfOxf4m78Brr4a+MIXgJ/8JP3eyZOE1OmgKSkh58krBU+n\nRQMQHz4uBS/qJ/feC9x0E2kLC55SDhNkpX047EzWCy4gs4BFCKPgo/Tggyr4sWOBgwczn7Ci8uCP\nHiVrvrqh4sGbgMQ9eCDtw1dXZ76umiaZCxbNBx+QDsIGX6L24AHgq18Fbr6ZEMLevcD99wP19YTw\nWXuGgto0Y8fyPy8Kgn/nHf57cSj4zZuBl17it0Fk0fAUngyKikg7urvD9blp08i4+egjcr3cCJIm\nScuDqFaTVFXw/f3kGO4x79fODz/0JnidCl6F4KPmjqAwguBFPnxUWTRJWjS0JABbxCgOBZ9KEUKY\nNg1YvJgEGb/5TeD//b/MDBoKmknjfp1CN8EvWgQcO8Z/L2oPvquL1D959FE+Uer24Gk7whJ8UVFa\nxV9xRfb7KmmStP9RspKpgMhaNKoKPmia5N692QSvy4N3E7z7SQ7IPQWfuEUDqBF8LufB19QQYmXt\nGSAeD96Nv/xLcs6ffZav4P3KFXipliAEf8klwNq1/Pd0KnieRbNmDdDYCCxbxt9H5MEnTfBAutwy\nDyppkvT7qaQushZNEAWvmibJs2ii9OBpTMpru7DHjRrGEDwvLU8lTVIliyapPPiiIlJYS4XgdSl4\nN4qLgQceIOR24ADfovFKlfRSS0EI3gtRWjQHDgBPPw384z+K99GdBw+kC3VFSfBBJjqpqOqwCl41\nyEotGjb103rw3jCC4EW58F7FxnjVJE0vVQAQcpcleJ0ePA+f/jTpxI88ok7wui0aL5SVRWfRHD5M\nbA53aiQLUbngoFk0AOm7uhS8KNAqexOqrExXd1Qh3bAKPkiQ9cSJzGtFx/3ISHIefNh01yhhBMEX\nikUDEHJnUySBZCwagPisP/whGTRBLBpdM1n9EKVFw8t7d0Nk0YS5icVh0ciSbiqVvompEHwSCh7I\nvF6pVPqpXFctmpERklnmFmKAVfCBoBpkDUPwlZXkf3eOd1wXSUXBR2nRUMyfDzz4ILBwYebrJil4\nnUFWt0UjQ/A8i+bQIb5HKwuTPHggGMHTc+k48sv1AeEUPCCuFaRLwR8/TspV8MaeqNiYzaLxgKqC\nHxiQT5N0dz6aoubukHEp+EWLyKBkkSTBA8Ddd2e/Fobgv/AF4PLL9bQN0K/gVQmeKsTRUdJ/hoZI\nuuusWeHaocODP/ts0rbTp7NTDlVskyAET8cSHY9RK3gRwdMbsC4PXmTPALk30ckIgheRiQ6Lhubb\nsqtCUZsmCYJftSr7taQ8eC9UVxOVyqKnh8ycHBkhwS7R+frzP9fblignOskQfFER6Wt9fYRM9u8n\nllYYG0qXgk+lyLKH774LzJuX+Z6qgu/uVs9soWTd3y9/rKDlgnkWDZAez2EVPO0XfgRvLRpFeCl4\n2Zms9HW39cJTMTwfPi6C5yEpD94LvJvun/850NAAXHcdsGEDSW2MA+XlyVo0QKYP/+672U9hqqBB\nVh3EwLNphobIWJDtPzRVUjU3nZJ1EAWv06Lp7dWXBy9KkQRyj+CNUPBBgqxu4i4qSj8+sfvw6nHk\nEsEnpeB5BL9rF/D738dfQGnNGvGMWlXwLJq5c/33Y314HQSvS8EDfIKn40NmwhKQtmhUKzyyCl6l\nmmTQBT+A6BS8rEWTV1k0ra2tqK+vR11dHdavX5/1/pNPPolLL70Ul156KT7/+c9jz549yo1QIXh6\nIXiKgWfTiBS8OxfeNIKnU8aTtGjYLJq+PhJ8chfiigMzZmTXaA8Kt0XT0SGn4NlUyT17+LMcVdsR\nNcGr5OmzFk3UCp6O0yDVJIHsEshskDWsB+843gSfdxOdVq9ejebmZmzevBkbNmxAu6t83axZs9Da\n2oo//OEPuP766/F3f/d3yo1Q8eDpikFdXeEI3q3gk4yE8wh+dJR816KETDT3Ndm3j5Q/TeqGowtB\nLRqW4HUpeB1BVoBP8KppnNSiUSV4VsGrFhuLIsgalGiLisjPyEgwD97ULBpP+jj9sYRbvHgxZs6c\niaVLl2Lr1q0Z21x11VWo/jh8v3z5crz22mvKjVBR8AB57fRpvQSf5GMWj+CT9N+B7EU/9u4lwbxc\nR5AsGiDbgw+r4CsqSB80ScFTglcZB6yCD5ImqRpkXblSPJ7DjmGqzo8cyZ8gq6ce2759O+bMmXPm\n/7lz52LLli1Yvnw5d/tHH30UN9xwg/Dz7r///jN/NzY2orGxEUBwgndfaFmC55UMTtKiKS8nnYZt\nQ5L+O5C96Ec+EbxqFg2QVon9/YQAzjsvfDsAPX1u8mTSd9jlBlUVPLVoKiujV/DsXBYVYiwqAjZu\nzH5dhwcPpAk+6SyalpYWtLS0aPksbRSyefNmPPHEE/jd734n3IYleBZBCP7kyewORQOwLHIhiyaV\nSj8iU38xSf8dyLZo9u6VC0aajrAWzb59JCYQ9troJPhUKq3iGxrIa6oKnva/8ePVCV5VwdOEiO5u\nPdlROjx4QI7gRROddBI8K34BYK2oCp8EPC2a+fPnY/fu3Wf+b2trw0L3lEcAb731Fr70pS/hN7/5\nDWpkFoF0QeTBix656LRi3RZNkpaI26ZJWsGPG0cGDV1Tcu/e8L6zCWD7yNAQ+VtmYWRKIjoCrLQd\ngL4+57Zpgij4IB48tVtUFDxAtu3q0kOMuhQ8dQaGhsR16nkTnXI2i4Z6662trdi/fz82bdqEBioR\nPnfW6QQAAA+mSURBVMaBAwdw880348knn8TsgM/w48YRcpMtH0A7YFCLJlcIPsn2FBWRQU+frPLR\noqGLN8ukElIC1BFgpe0AoiX4OLJoqEWjouABcgzH0aPgdQRZAXItDh4k6l3UJ9wWDc12MzXI6qsR\n161bh6amJgwNDWHVqlWora1Fc3MzAKCpqQnf+9730NHRgS996UsAgNLSUmzbtk2tESXkBLkfK70s\nGsAq+KhBn6wqKkjVxZkzk22PDrAWjaw9A6RJZO9ePWUYaN/VSfAvvZT+X5VwwwZZgyh4QJ+CP3pU\nT5CVErwIboIfHialt2XnG8QNXwpZsmQJdu3alfFaU1PTmb9/8pOf4CfsAp8BQX14FYIXrfbEQjYP\nPulIuJvgk/bggXQufG8vyX83VaWogO0jqgRPLZrPflZPOwC9BM9OU1FV8GHTJIMo+OJi8hMWrEUT\n1oM/cECN4JPmDT8YUaoA4PvwogtGy9G675q8RT9yWcEnTaj0muSLPQNkWzSyBE89eNMtGmpzBlXw\nQUsVBFHwuspP6KgmCcgpePdEJ0vwkuBl0ngpeF7n5S36kQtpkoDZFs277+YPwYexaI4fJ6mIOmbz\n6ib4SZPI9Xr6afK/6R58RYU+YozCgxch1xS8MfMSVQmepxZEFo07SyIXFLxJFk2+KfigBP/WW2T1\nJx2ziymJ6iKHVAp44QVg6VKS+RQ0TTIIwQdR8DoLyOmc6HTgAOAxlSeL4E3OoAFyVMGXl6sRfK5a\nNEkTPGvR5EOKJBDcohkzBmhr05MiCegPsgLAxRcDmzYB994L/OpX8aVJ0n6r8l10KnidHvzBg94L\nueSagjeG4EUevKpFk08Ebz14/Qhq0VRVkWui60an26KhuOgi4JVXyDKMMvn9FGHqwZ86pV4bPwoF\nr8OiOXXK34PPJYIvCIvGj+BNyGUdO5Z0LgoTFHx1NZkxfPBg+Kn5psBt0cjOzqWVDE0neACorwfe\nfju+IOupU+pLNOpW8D09ZByHJXjA34Nng6wDA8kLMS8Yo+B1EHzQLJqREeJh6kjZCgoTPfjx44nv\nPG2aPrWVNNhyFqoWDaDPoomS4AGysDttswzCePBJK3gaZNXhwQPAlCnibdwWzYkT/MW5TUFeEbxs\nFo07Dz5p9Q6Y68H/53/mjz0DBA+y0oClLgUfhQcfBnScdXXFp+CjsGjCnM+yMtIfvNrlJvgPPwSm\nTw9+zKhhDMHzPHjRHbm8XK8HbyrBJ92m6mpSOTHfCD6Igh87lvx4Pb6rtgNI/hqzGDOGpIHGpeCj\nCLKGVfB+17e4mGQp0RpNluAlEacH786DN5XgTVDwQH4RfNAg64wZQGurvinpJhL82LEk5hIkyJqk\ngmdLFkdN8KlUpoq3BC8JEcF7zWR1I5cVPM1ioDDFgwfyJ0USCG7RpFJ6atCw7QCS73csgih4atEk\nqeBTKTLGwy5iXlrqnSJJYQk+AHTNZM1VgjdRwdOSqfmk4KlFQ9f1VUkl1N0OIPl+x4IGK1UtGtXS\nxHQ/nYF7GlAOmwcvY8FZgg8AtwfvOMGyaGRLFfT3p300Uwk+6TaNH0/U0axZybZDJ6hFc+qUfKng\nKGBakBVIr3mqquCBZLNogHQQPIwoKivLP4I3Ng/eK3Wxujq76D4gr+CLitJFkqqqzJisYKKCnzIF\n+Md/VB+8JoP2ERV7Jqp2AMmm5rpBVbCqgmd/q+ync8xVVZHPC3PD/vrX5Z7o6GSnvj4yZmtrgx8z\nahhL8F6k++UvZy8OAsgTPJC2aaqqzFTwJnjwJSXA3Xcn2wbdoKuBnTyZLMFXVpKSAibVEQ9C8KLF\nd/wwblz6iUEHKMGHgawVSSc7HToEnHOOWdfQjZwkeBEZByF4wAyCp+0ZHSVPGCZYNPmIVIqc1+PH\n0wtUJ4GiIuCHP0zu+DxQglfNomF/y+L22/XU1acYMya+8UItGtPtGcBgDz6IbeImeGrj8C58ZWV6\nspMJBF9cnJm+aYJFk68oLycrACWp4E1EEA+eEnuQIKto3dMg0KHgZWEJPgDKy4l6pUFSHQTvVaPa\nNAUPkJvciRPkbxMsmnyFJXg+wlg0Scdp4iR46sFbgldAKpVp0wQheHcWTa4R/E03AXT1Q6vgo0NZ\nGXDsmCV4N8aMIdaRSr8LquB1I24FPzRkCV4ZLMEHmbTgVvBe+bljx5IgCWBGFg1Agm7NzcSqsh58\ndLAKno+xY9VTF01S8NaDz4ZRBM/68D/9KfCZz6jtr2LR/M//CXz72+RGYoqCv+ACsiLPI49YBR8l\nLMHzMWZMsKdmIHkFH6TtQWEJPiCogj96FHj8caJoVaBC8DfcACxZQo5hCsED5Kazbh05D5bgo4G1\naPgYM0ZdwadS4hXW4oQNsvJhJMH/7/9N0qhUK/epEDxAiPT558mPKQR/ySWk5snjj1uCjwpWwfMR\nhOABQu5JK/i4g6w9PaRuz1lnxXPMoDCO4PftAzZuBL75TfX93fXg/Qi+upoc66c/NYfgAWDNGhIf\nMKlN+YTychKfsQSfiSAePEAI3gQFH6cHf+AAKUxm0kxkHozSiOPHAw88ANx2G5khpgr3ik5+BA8A\n110HfOUr6bo0JmDRIvJjCT4aUKVnCT4TQRW8aH2GOBG3RbN/v/n2DGAYwY8bRxaY+Na3gu3Ps2ho\nESIvrF+fPQM2afz858mronwFJTFL8JmYPZvEplRhgoKPO8iaKwRvlEUzeTKwciUwc2aw/VU9eIpU\nKvkO6sa555q91mMuo7ycPFonVSrYVEyZAvzgB+r7maDgzzsPmDMnnmOVluYOwRul4L/9bX4RMVmU\nlBCrZWSEDODu7uQ7noV5KCtLtlRwvuErX4mPXEW4+mryEwdKSoD33wf+9E/jOV4YGKXgS0rC+c40\nZYuq+GefJV62hQWL8nJrz+hEU1Nhnc+SEpIEYRV8AqDlCg4eBN56C7j11qRbZGEaLMFbhAF1CnKB\n4I1S8DpAFfyPfwzceafeVWMs8gNlZZbgLYKDzk/JBYLPOwVfXk4mIDzxBPDmm0m3xsJEWAVvEQal\npaQom+pEzCSQlwp+40bgmmuAGTOSbo2FibAK3iIMSkoIuefCPJW8VPCPPgo880zSLbEwFXHOerTI\nP5SU5IY9A0go+NbWVtTX16Ourg7r16/nbrNmzRrMmjULV155JXbv3q29kSooLyd312uvTbQZnmhp\naUm6CcYgiXPx1a8CX/ta7If1he0XaZh8LvKK4FevXo3m5mZs3rwZGzZsQHt7e8b727Ztw+uvv44d\nO3bgnnvuwT333BNZY2VQXk4W5S4y2HwyufPGjSTOxaRJ5Mc02H6RhsnnorQ0Twj+9OnTAIDFixdj\n5syZWLp0KbZu3ZqxzdatW3HLLbdg4sSJWLFiBXbt2hVdayWwYQPJy7WwsLCIAp/4BLBgQdKtkIMn\nwW/fvh1zmClqc+fOxZYtWzK22bZtG+bOnXvm/8mTJ+O9997T3Ex5XHGFeWUHLCws8gf/438Af/EX\nSbdCDqGDrI7jwHHVF0gJ5oCLXi9ErF27NukmGAN7LtKw5yINey7Cw5Pg58+fj3uZZZXa2tqwbNmy\njG0aGhqwc+dOXH/99QCAEydOYNasWVmf5b4JWFhYWFhEC0+Lprq6GgDJpNm/fz82bdqEhoaGjG0a\nGhrwy1/+EidPnsTPf/5z1NfXR9daCwsLCwtp+Fo069atQ1NTE4aGhrBq1SrU1taiubkZANDU1IQF\nCxZg0aJFmDdvHiZOnIgnnngi8kZbWFhYWEjAiRivvfaaM2fOHGf27NnOj370o6gPZxQOHDjgNDY2\nOnPnznWWLFniPPnkk47jOM5HH33k3Hjjjc65557r3HTTTU5XV1fCLY0Pw8PDzmWXXeZ85jOfcRyn\ncM9Fd3e381d/9VdOXV2dU19f72zZsqVgz8Wjjz7qXHXVVc4VV1zhrF692nGcwukXK1eudM466yzn\n4osvPvOa13d/6KGHnNmzZzv19fXO66+/7vv5kWeL++XR5zNKS0vx4IMPoq2tDc888wy++93voqur\nCw8//DBmzJiBd999F9OnT8cjjzySdFNjw0MPPYS5c+eeCbgX6rm47777MGPGDLz11lt46623MGfO\nnII8Fx0dHfj+97+PTZs2Yfv27dizZw9efvnlgjkXK1euxEsvvZTxmui7Hz9+HD/+8Y/xyiuv4OGH\nH8aqVat8Pz9SgpfJo89nnH322bjssssAALW1tbjooouwfft2bNu2DXfeeSfKy8txxx13FMw5+fDD\nD/HCCy/gi1/84pmge6Gei82bN+M73/kOKioqUFJSgurq6oI8F5WVlXAcB6dPn0ZfXx96e3tRU1NT\nMOfimmuuwQRXYSTRd9+6dSuWLVuGGTNmYMmSJXAcB11dXZ6fHynBy+TRFwr27t2LtrY2LFiwIOO8\nzJkzB9u2bUu4dfHga1/7Gv7hH/4BRcw040I8Fx9++CH6+/tx1113oaGhAX//93+Pvr6+gjwXlZWV\nePjhh3Heeefh7LPPxtVXX42GhoaCPBcUou++devWjCSWT3ziE77nxeAJ/fmDrq4ufO5zn8ODDz6I\nsWPHFmTK6HPPPYezzjoLl19+ecb3L8Rz0d/fjz179uDmm29GS0sL2tra8Itf/KIgz8WJEydw1113\nYefOndi/fz9+//vf47nnnivIc0Gh8t395hZFSvDz58/PKD7W1taGhQsXRnlI4zA0NISbb74Zt99+\nO2666SYA5LzQkg67du3C/Pnzk2xiLPjd736H3/zmNzj//POxYsUKvPrqq7j99tsL8lzMnj0bn/jE\nJ3DDDTegsrISK1aswEsvvVSQ52Lbtm1YuHAhZs+ejUmTJuHWW2/F66+/XpDngkL03emcI4rdu3f7\nnpdICV4mjz6f4TgO7rzzTlx88cW4++67z7ze0NCAjRs3oq+vDxs3biyIm973v/99HDx4EO+//z6e\nfvppfOpTn8Ljjz9ekOcCAOrq6rB161aMjo7i+eefx3XXXVeQ5+Kaa67Bjh070NHRgYGBAbz44otY\nunRpQZ4LCtF3X7BgAV5++WUcOHAALS0tKCoqwrhx47w/TGPGDxctLS3OnDlznAsuuMB56KGHoj6c\nUXj99dedVCrlXHrppc5ll13mXHbZZc6LL75YMClgIrS0tDg33HCD4ziFkw7nxh//+EenoaHBufTS\nS51vfOMbTnd3d8Gei8cee8xZvHixM2/ePOe73/2uMzIyUjDn4rbbbnOmTp3qlJWVOdOnT3c2btzo\n+d3XrVvnXHDBBU59fb3T2trq+/kpxylgs8vCwsIij2GDrBYWFhZ5CkvwFhYWFnkKS/AWFhYWeQpL\n8BYWFhZ5CkvwFhYWFnkKS/AWFhYWeYr/D/Y0b3ewfmEHAAAAAElFTkSuQmCC\n"
}
],
- "prompt_number": 12
+ "prompt_number": 5
},
{
"cell_type": "markdown",
@@ -412,10 +411,9 @@
"collapsed": true,
"input": [],
"language": "python",
- "outputs": [],
- "prompt_number": "&nbsp;"
+ "outputs": []
}
]
}
]
-}
+}
View
2  docs/examples/notebooks/formatting.ipynb
@@ -117,7 +117,7 @@
"collapsed": true,
"input": [],
"language": "python",
- "outputs": [],
+ "outputs": [],
"prompt_number": "&nbsp;"
}
]
View
13 docs/examples/notebooks/sympy.ipynb
@@ -40,7 +40,7 @@
"text": [
"",
"Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].",
- "For more information, type &apos;help(pylab)&apos;."
+ "For more information, type 'help(pylab)'."
]
}
],
@@ -123,7 +123,7 @@
"output_type": "pyout",
"prompt_number": 6,
"text": [
- "Add(Symbol(&apos;x&apos;), Mul(Integer(2), Symbol(&apos;y&apos;)))"
+ "Add(Symbol('x'), Mul(Integer(2), Symbol('y')))"
]
}
],
@@ -317,10 +317,11 @@
"",
" b ",
" ___ ",
- " \\ &#96; ",
- " \\ \u239b n 2\u239e",
- " / \u239d2 + 6\u22c5n \u23a0",
- " /__, ",
+ " \u2572 ",
+ " \u2572 \u239b n 2\u239e",
+ " \u2571 \u239d2 + 6\u22c5n \u23a0",
+ " \u2571 ",
+ " \u203e\u203e\u203e ",
"n = a "
]
}
View
3  docs/examples/notebooks/trapezoid_rule.ipynb
@@ -110,8 +110,7 @@
"collapsed": true,
"input": [],
"language": "python",
- "outputs": [],
- "prompt_number": "&nbsp;"
+ "outputs": []
}
]
}
View
151 docs/examples/parallel/helloworld.ipynb
@@ -1,65 +1,92 @@
{
- "nbformat": 2,
- "metadata": {
- "name": "helloworld"
+ "metadata": {
+ "name": "helloworld"
+ },
+ "nbformat": 2,
+ "worksheets": [
+ {
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Distributed hello world",
+ "",
+ "Originally by Ken Kinder (ken at kenkinder dom com)"
+ ]
},
- "worksheets": [
- {
- "cells": [
- {
- "source": "# Distributed hello world\n\nOriginally by Ken Kinder (ken at kenkinder dom com)",
- "cell_type": "markdown"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 3,
- "input": "from IPython.parallel import Client"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 4,
- "input": "rc = Client()\nview = rc.load_balanced_view()"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 5,
- "input": "def sleep_and_echo(t, msg):\n import time\n time.sleep(t)\n return msg"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 6,
- "input": "world = view.apply_async(sleep_and_echo, 3, 'World!')\nhello = view.apply_async(sleep_and_echo, 2, 'Hello')\n"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [
- {
- "output_type": "stream",
- "text": "Submitted tasks: [&apos;9e533683-d54e-4588-929e-984dd3eb6dc4&apos;] [&apos;90395f15-723f-44df-a743-a5d88cdeb6a0&apos;]\nHello"
- },
- {
- "output_type": "stream",
- "text": "World!"
- }
- ],
- "collapsed": false,
- "prompt_number": 7,
- "input": "print \"Submitted tasks:\", hello.msg_ids, world.msg_ids\nprint hello.get(), world.get()"
- }
- ]
- }
- ]
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [
+ "from IPython.parallel import Client"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [
+ "rc = Client()",
+ "view = rc.load_balanced_view()"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 2
+ },
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [
+ "def sleep_and_echo(t, msg):",
+ " import time",
+ " time.sleep(t)",
+ " return msg"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 3
+ },
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [
+ "world = view.apply_async(sleep_and_echo, 3, 'World!')",
+ "hello = view.apply_async(sleep_and_echo, 2, 'Hello')"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 4
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "print \"Submitted tasks:\", hello.msg_ids, world.msg_ids",
+ "print hello.get(), world.get()"
+ ],
+ "language": "python",
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Submitted tasks: ['dd1052e0-aa75-4b25-9d35-ecbdaf6e3ed7'] ['1b46aa21-20d1-459c-bc36-2d8d03336f74']",
+ "Hello"
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ " World!"
+ ]
+ }
+ ],
+ "prompt_number": 5
+ }
+ ]
+ }
+ ]
}
View
357 docs/examples/parallel/parallel_mpi.ipynb
@@ -1,139 +1,224 @@
{
- "worksheets": [
- {
- "cells": [
- {
- "source": "# Simple usage of a set of MPI engines\n\nThis example assumes you've started a cluster of N engines (4 in this example) as part\nof an MPI world. \n\nOur documentation describes [how to create an MPI profile](http://ipython.org/ipython-doc/dev/parallel/parallel_process.html#using-ipcluster-in-mpiexec-mpirun-mode)\nand explains [basic MPI usage of the IPython cluster](http://ipython.org/ipython-doc/dev/parallel/parallel_mpi.html).\n\n\nFor the simplest possible way to start 4 engines that belong to the same MPI world, \nyou can run this in a terminal or antoher notebook:\n\n<pre>\nipcluster start --engines=MPIExecEngineSetLauncher -n 4\n</pre>\n\nNote: to run the above in a notebook, use a *new* notebook and prepend the command with `!`, but do not run\nit in *this* notebook, as this command will block until you shut down the cluster. To stop the cluster, use \nthe 'Interrupt' button on the left, which is the equivalent of sending `Ctrl-C` to the kernel.\n\nOnce the cluster is running, we can connect to it and open a view into it:",
- "cell_type": "markdown"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 21,
- "input": "from IPython.parallel import Client\nc = Client()\nview = c[:]"
- },
- {
- "source": "Let's define a simple function that ",
- "cell_type": "markdown"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 22,
- "input": "@view.remote(block=True)\ndef mpi_rank():\n from mpi4py import MPI\n comm = MPI.COMM_WORLD\n return comm.Get_rank()"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [
- {
- "output_type": "pyout",
- "prompt_number": 23,
- "text": "[3, 0, 2, 1]"
- }
- ],
- "collapsed": false,
- "prompt_number": 23,
- "input": "mpi_rank()"
- },
- {
- "source": "For interactive convenience, we load the parallel magic extensions and make this view\nthe active one for the automatic parallelism magics.\n\nThis is not necessary and in production codes likely won't be used, as the engines will \nload their own MPI codes separately. But it makes it easy to illustrate everything from\nwithin a single notebook here.",
- "cell_type": "markdown"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 4,
- "input": "%load_ext parallelmagic\nview.activate()"
- },
- {
- "source": "Use the autopx magic to make the rest of this cell execute on the engines instead\nof locally",
- "cell_type": "markdown"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 24,
- "input": "view.block = True"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [
- {
- "output_type": "stream",
- "stream": "stdout",
- "text": "%autopx enabled\n\n"
- }
- ],
- "collapsed": false,
- "prompt_number": 32,
- "input": "%autopx"
- },
- {
- "source": "With autopx enabled, the next cell will actually execute *entirely on each engine*:",
- "cell_type": "markdown"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 29,
- "input": "from mpi4py import MPI\n\ncomm = MPI.COMM_WORLD\nsize = comm.Get_size()\nrank = comm.Get_rank()\n\nif rank == 0:\n data = [(i+1)**2 for i in range(size)]\nelse:\n data = None\ndata = comm.scatter(data, root=0)\n\nassert data == (rank+1)**2, 'data=%s, rank=%s' % (data, rank)"
- },
- {
- "source": "Though the assertion at the end of the previous block validated the code, we can now \npull the 'data' variable from all the nodes for local inspection.\nFirst, don't forget to toggle off `autopx` mode so code runs again in the notebook:\n",
- "cell_type": "markdown"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [
- {
- "output_type": "stream",
- "stream": "stdout",
- "text": "%autopx disabled\n\n"
- }
- ],
- "collapsed": false,
- "prompt_number": 33,
- "input": "%autopx"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [
- {
- "output_type": "pyout",
- "prompt_number": 34,
- "text": "[16, 1, 9, 4]"
- }
- ],
- "collapsed": false,
- "prompt_number": 34,
- "input": "view['data']"
- },
- {
- "input": "",
- "cell_type": "code",
- "collapsed": true,
- "language": "python",
- "outputs": []
- }
- ]
- }
- ],
- "metadata": {
- "name": "parallel_mpi"
+ "metadata": {
+ "name": "parallel_mpi"
+ },
+ "nbformat": 2,
+ "worksheets": [
+ {
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Simple usage of a set of MPI engines",
+ "",
+ "This example assumes you've started a cluster of N engines (4 in this example) as part",
+ "of an MPI world. ",
+ "",
+ "Our documentation describes [how to create an MPI profile](http://ipython.org/ipython-doc/dev/parallel/parallel_process.html#using-ipcluster-in-mpiexec-mpirun-mode)",
+ "and explains [basic MPI usage of the IPython cluster](http://ipython.org/ipython-doc/dev/parallel/parallel_mpi.html).",
+ "",
+ "",
+ "For the simplest possible way to start 4 engines that belong to the same MPI world, ",
+ "you can run this in a terminal or antoher notebook:",
+ "",
+ "<pre>",
+ "ipcluster start --engines=MPI -n 4",
+ "</pre>",
+ "",
+ "Note: to run the above in a notebook, use a *new* notebook and prepend the command with `!`, but do not run",
+ "it in *this* notebook, as this command will block until you shut down the cluster. To stop the cluster, use ",
+ "the 'Interrupt' button on the left, which is the equivalent of sending `Ctrl-C` to the kernel.",
+ "",
+ "Once the cluster is running, we can connect to it and open a view into it:"
+ ]
},
- "nbformat": 2
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [
+ "from IPython.parallel import Client",
+ "c = Client()",
+ "view = c[:]"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 21
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "Let's define a simple function that gets the MPI rank from each engine."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [
+ "@view.remote(block=True)",
+ "def mpi_rank():",
+ " from mpi4py import MPI",
+ " comm = MPI.COMM_WORLD",
+ " return comm.Get_rank()"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 22
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "mpi_rank()"
+ ],
+ "language": "python",
+ "outputs": [
+ {
+ "output_type": "pyout",
+ "prompt_number": 23,
+ "text": [
+ "[3, 0, 2, 1]"
+ ]
+ }
+ ],
+ "prompt_number": 23
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "For interactive convenience, we load the parallel magic extensions and make this view",
+ "the active one for the automatic parallelism magics.",
+ "",
+ "This is not necessary and in production codes likely won't be used, as the engines will ",
+ "load their own MPI codes separately. But it makes it easy to illustrate everything from",
+ "within a single notebook here."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [
+ "%load_ext parallelmagic",
+ "view.activate()"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 4
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "Use the autopx magic to make the rest of this cell execute on the engines instead",
+ "of locally"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [
+ "view.block = True"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 24
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "%autopx"
+ ],
+ "language": "python",
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "%autopx enabled"
+ ]
+ }
+ ],
+ "prompt_number": 32
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "With autopx enabled, the next cell will actually execute *entirely on each engine*:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [
+ "from mpi4py import MPI",
+ "",
+ "comm = MPI.COMM_WORLD",
+ "size = comm.Get_size()",
+ "rank = comm.Get_rank()",
+ "",
+ "if rank == 0:",
+ " data = [(i+1)**2 for i in range(size)]",
+ "else:",
+ " data = None",
+ "data = comm.scatter(data, root=0)",
+ "",
+ "assert data == (rank+1)**2, 'data=%s, rank=%s' % (data, rank)"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 29
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "Though the assertion at the end of the previous block validated the code, we can now ",
+ "pull the 'data' variable from all the nodes for local inspection.",
+ "First, don't forget to toggle off `autopx` mode so code runs again in the notebook:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "%autopx"
+ ],
+ "language": "python",
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "%autopx disabled"
+ ]
+ }
+ ],
+ "prompt_number": 33
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "view['data']"
+ ],
+ "language": "python",
+ "outputs": [
+ {
+ "output_type": "pyout",
+ "prompt_number": 34,
+ "text": [
+ "[16, 1, 9, 4]"
+ ]
+ }
+ ],
+ "prompt_number": 34
+ },
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [],
+ "language": "python",
+ "outputs": []
+ }
+ ]
+ }
+ ]
}
View
174 docs/examples/parallel/taskmap.ipynb
@@ -1,71 +1,109 @@
{
- "nbformat": 2,
- "metadata": {
- "name": "taskmap"
+ "metadata": {
+ "name": "taskmap"
+ },
+ "nbformat": 2,
+ "worksheets": [
+ {
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Load balanced map and parallel function decorator"
+ ]
},
- "worksheets": [
- {
- "cells": [
- {
- "source": "# Load balanced map and parallel function decorator",
- "cell_type": "markdown"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 4,
- "input": "from IPython.parallel import Client"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [],
- "collapsed": true,
- "prompt_number": 5,
- "input": "rc = Client()\nv = rc.load_balanced_view()"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [
- {
- "output_type": "stream",
- "text": "Simple, default map: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
- }
- ],
- "collapsed": false,
- "prompt_number": 6,
- "input": "result = v.map(lambda x: 2*x, range(10))\nprint \"Simple, default map: \", list(result)"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [
- {
- "output_type": "stream",
- "text": "Submitted tasks, got ids: [&apos;2a25ff3f-f0d0-4428-909a-3fe808ca61f9&apos;, &apos;edd42168-fac2-4b3f-a696-ce61b37aa71d&apos;, &apos;8a548908-7812-44e6-a8b1-68e941bee608&apos;, &apos;26435a77-fe86-49b6-b59f-de864d59c99f&apos;, &apos;6750c7b4-2168-49ec-bcc4-feb1e17c5e53&apos;, &apos;117240d1-5dfc-4783-948f-e9523b2b2f6a&apos;, &apos;6de16d46-f2e2-49bd-8180-e43d1d875529&apos;, &apos;3d372b84-0c68-4315-92c8-a080c68478b7&apos;, &apos;43acedae-e35c-4a17-87f0-9e5e672500f7&apos;, &apos;eb71dd1f-9500-4375-875d-c2c42999848c&apos;]\nUsing a mapper: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
- }
- ],
- "collapsed": false,
- "prompt_number": 7,
- "input": "ar = v.map_async(lambda x: 2*x, range(10))\nprint \"Submitted tasks, got ids: \", ar.msg_ids\nresult = ar.get()\nprint \"Using a mapper: \", result"
- },
- {
- "cell_type": "code",
- "language": "python",
- "outputs": [
- {
- "output_type": "stream",
- "text": "Using a parallel function: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
- }
- ],
- "collapsed": false,
- "prompt_number": 8,
- "input": "@v.parallel(block=True)\ndef f(x): return 2*x\n\nresult = f.map(range(10))\nprint \"Using a parallel function: \", result"
- }
- ]
- }
- ]
+ {
+ "cell_type": "code",
+ "collapsed": true,
+ "input": [
+ "from IPython.parallel import Client"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "rc = Client()",
+ "v = rc.load_balanced_view()"
+ ],
+ "language": "python",
+ "outputs": [],
+ "prompt_number": 3
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "result = v.map(lambda x: 2*x, range(10))",
+ "print \"Simple, default map: \", list(result)"
+ ],
+ "language": "python",
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Simple, default map: "
+ ]
+ },
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
+ ]
+ }
+ ],
+ "prompt_number": 4
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "ar = v.map_async(lambda x: 2*x, range(10))",
+ "print \"Submitted tasks, got ids: \", ar.msg_ids",
+ "result = ar.get()",
+ "print \"Using a mapper: \", result"
+ ],
+ "language": "python",
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Submitted tasks, got ids: ['5100a4c7-73a4-4832-aa91-e774f6f3ede8', 'd0cae1cf-2b32-4092-9eb7-f17b43fb3849', 'e08d3ee2-f221-47fe-9556-ed938e692030', '065585e4-cdf9-4240-a5fe-e44b2ae5d023', 'd2162f23-68e5-4318-ba1e-e34fd03a72ac', '5b3b835f-2099-4a70-9896-d1aa810c77e6', 'e2c2a823-bd44-4f91-8db3-c154d0d86e56', '991e0c25-f98a-44b5-9d9e-889d4180b9a5', '4ad41221-28bd-482f-a300-97c404648161', '5b730eb3-e0bb-4cdd-b228-c3b8d158828a']",
+ "Using a mapper: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
+ ]
+ }
+ ],
+ "prompt_number": 5
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "@v.parallel(block=True)",
+ "def f(x): return 2*x",
+ "",
+ "result = f.map(range(10))",
+ "print \"Using a parallel function: \", result"
+ ],
+ "language": "python",
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Using a parallel function: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]"
+ ]
+ }
+ ],
+ "prompt_number": 6
+ }
+ ]
+ }
+ ]
}
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