Merge branch 'master' of ssh://apples.lambdacomplex.org/git/bus
Merge branch 'master' of ssh://apples.lambdacomplex.org/git/bus

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-<html> 
-  <head> 
-    <link rel="stylesheet" href="main.css" type="text/css"> 
-    <title>Graphserver - The Open-Source Multi-Modal Trip Planner</title> 
-  </head> 
- 
-<body> 
-<div id='container'> 
-<a href="gallery.html"><img src="img/graphbanner.png"></a> 
-<h1>Graphserver</h1> 
-The open-source multi-modal trip planner.
- 
-<h2>Code Repository</h2> 
-<a href="http://github.com/bmander/graphserver/tree/master">http://github.com/bmander/graphserver/tree/master</a> 
- 
-<h2>Mailing List</h2> 
- 
-Direct questions and comments to the <a href="http://groups.google.com/group/graphserver">Graphserver Google Group</a>.
- 
-<h2>Download</h2> 
- 
-<pre style="background-color:#F5F5F5"> $ wget http://github.com/bmander/graphserver/zipball/08132009</pre> 
- 
-Or, for the stout of heart, get a copy of the current working branch
- 
-<pre style="background-color:#F5F5F5"> $ git clone git://github.com/bmander/graphserver.git </pre>
- 
-<h2>Install</h2>
 
-<h3>Cold Start</h3>
-<p>You'll need a computer running linux. The following setup was tested and checked on <a href="http://aws.amazon.com/console/">Amazon EC2</a> small instance running Fedora, built from an image with id "ami-48aa4921", at a cost of $0.20/hour.<p>
-<p>You'll need to get git:</p>
-<p>On Ubuntu:</p>
-<pre style="background-color:#F5F5F5"> $ sudo apt-get install git-core </pre>
-<p>On Fedora:</p>
-<pre style="background-color:#F5F5F5"> $ yum install git-core</pre>
- 
-<h3>Get The Prerequisites</h3>
-
-<p>You're about to compile C code against python development libraries. You need to prepare for that.</p>
-
-On Ubuntu:
-<pre style="background-color:#F5F5F5">$ sudo apt-get install python-setuptools
-$ sudo apt-get install build-essential
-$ sudo apt-get install python-dev
-</pre>
-
-On Fedora:
-<pre style="background-color:#F5F5F5">
-$ yum install python-setuptools-devel
-$ yum install gcc
-$ yum install gcc-c++
-$ yum install python-devel
-$ easy_install simplejson
-</pre>
- 
-<h3>One-step Install</h3>
-<p>Get a copy of Graphserver</p>
-<pre style="background-color:#F5F5F5">$ git clone git://github.com/bmander/graphserver.git</pre> 
-
-This will download and compile the core, download and install package dependencies, and install the python wrappers in one go.
-
-<pre style="background-color:#F5F5F5">$ cd graphserver/pygs
-$ sudo python setup.py install
-</pre> 
- 
-<h3>Install RTree</h3>
-<p>If you want to load OSM Data (and you probably do), you have to laboriously install RTree</p>
-<pre style="background-color:#F5F5F5"> $ wget http://download.osgeo.org/libspatialindex/spatialindex-1.4.0.tar.gz
- $ gunzip spatialindex-1.4.0.tar.gz
- $ tar -xvf spatialindex-1.4.0.tar
- $ cd spatialindex-1.4.0
- $ ./configure --prefix=/usr
- $ make
- $ make install
- $ easy_install RTree
- $ cp /usr/lib/python2.5/site-packages/Rtree-0.5.0-py2.5-linux-i686.egg/libsidx.so /usr/lib
-</pre>
- 
-<h2>A Quick Tour of the Basics</h2> 
- 
-<pre style="background-color:#F5F5F5"> 
-$ python
-&gt;&gt;&gt; from graphserver.core import Graph, Street, State
-&gt;&gt;&gt; gg = Graph()
-&gt;&gt;&gt; gg.add_vertex("A")
-<span class="computeroutput">&lt;graphserver.core.Vertex object at 0xb7d9608c&gt;</span> 
-&gt;&gt;&gt; gg.add_vertex("B")
-<span class="computeroutput">&lt;graphserver.core.Vertex object at 0xb7c397cc&gt;</span> 
-&gt;&gt;&gt; gg.add_edge( "A", "B", Street("1", 100) )
-<span class="computeroutput">&lt;graphserver.core.Edge object at 0xb7c4a92c&gt;</span> 
-&gt;&gt;&gt; gg.add_edge( "A", "B", Street("2", 50 ) )
-<span class="computeroutput">&lt;graphserver.core.Edge object at 0xb7da708c&gt;</span> 
-&gt;&gt;&gt; gg.size   #the graph is quite small
-<span class="computeroutput">2</span> 
-&gt;&gt;&gt; gg.get_vertex("A").outgoing                      <span class="pycomment"># the graph is directional</span> 
-<span class="computeroutput">[&lt;graphserver.core.Edge object at 0xb7b9accc&gt;, &lt;graphserver.core.Edge object at 0xb7b9acac&gt;]</span> 
-&gt;&gt;&gt; gg.get_vertex("A").incoming
-<span class="computeroutput">[]</span> 
-&gt;&gt;&gt; spt = gg.shortest_path_tree( "A", "B", State(1,0) )
-&gt;&gt;&gt; spt
-<span class="computeroutput">&lt;graphserver.core.ShortestPathTree object at 0xb7c45b8c&gt;</span> 
-&gt;&gt;&gt; spt.get_vertex("A")                              <span class="pycomment"># the shortest path tree is a partial copy of the graph</span> 
-<span class="computeroutput">&lt;graphserver.core.Vertex object at 0xb7c4a92c&gt;</span> 
-&gt;&gt;&gt; spt.get_vertex("A").outgoing                     <span class="pycomment"># which only contains the shortest paths to all points closer than 'B' </span> 
-<span class="computeroutput">[&lt;graphserver.core.Edge object at 0xb7b9adec&gt;]</span> 
-&gt;&gt;&gt; vertices, edges = spt.path("B")                  <span class="pycomment"># you can get the path 'A' to 'B' from the shortest path tree</span> 
-&gt;&gt;&gt; vertices                                         <span class="pycomment"># a list of references to the SPT vertices along the shortest path</span> 
-<span class="computeroutput">[&lt;graphserver.core.Vertex object at 0xb7b9ae4c&gt;, &lt;graphserver.core.Vertex object at 0xb7b9adec&gt;]</span> 
-&gt;&gt;&gt; edges                                            <span class="pycomment"># a list of references to the SPT edges along the shortest path</span> 
-<span class="computeroutput">[&lt;graphserver.core.Edge object at 0xb7b9accc&gt;]</span> 
-&gt;&gt;&gt; edges[0].payload                                 <span class="pycomment"># the edge payload contains information about the edge</span>
-<span class="computeroutput">&lt;Street name='2' length=50.000000 rise=0.000000 fall=0.000000 way=0&gt;</span> 
-&gt;&gt;&gt; vertices[-1].payload                             <span class="pycomment"># the payload of the final vertex has useful information</span> 
-<span class="computeroutput">&lt;graphserver.core.State object at 0xb7c4a92c&gt;</span> 
-&gt;&gt;&gt; vertices[-1].payload.time                        <span class="pycomment"># it takes 58 seconds to get from "A" to "B"</span> 
-<span class="computeroutput">58</span> 
-&gt;&gt;&gt; spt.destroy()                                    <span class="pycomment"># these functions are thin wrappers around C functions</span> 
-&gt;&gt;&gt; gg.destroy()                                     <span class="pycomment"># so we have to perform garbage collection explicitly</span> 
-&gt;&gt;&gt; exit()
-</pre>
-<h2>Compiling Graphs</h2>
-<h3>Loading OpenStreetMap Data</h3>
-
-Grab some OSM data. Here, we download an area around of Redding, CA, US from the OpenStreetMap HTTP API.
-<pre style="background-color:#F5F5F5"> $ wget http://api.openstreetmap.org/api/0.6/map?bbox=-122.4624,40.5505,-122.2876,40.6334 -O map.osm
-</pre>
-<p>Compile the OSM file into an OSMDB file, and then load that OSMDB file into a graph.</p>
-<pre style="background-color:#F5F5F5"> $ gs_osmdb_compile map.osm map.osmdb
- $ gs_import_osm map.gdb map.osmdb
-</pre>
-<p>Take a look at your new graph. This prints every vertex label in the graph:</p>
-<pre style="background-color:#F5F5F5"> $ gs_gdb_inspect map.gdb</pre>
-<p>Pick one and see all edges outgoing from that vertex:</p>
-<pre style="background-color:#F5F5F5"> $ gs_gdb_inspect map.gdb osm-92080455</pre>
-Prints:
-<pre style="background-color:#F5F5F5">osm-92080455 -> osm-91938757
-	&lt;Street name='10585937-1' length=136.119463 rise=0.000000 fall=0.000000 way=849&gt;
-osm-92080455 -> osm-92080457
-	&lt;Street name='10585937-2' length=139.452776 rise=0.000000 fall=0.000000 way=849&gt;
-osm-92080455 -> osm-92601143
-	&lt;Street name='10596654-0' length=126.551782 rise=0.000000 fall=0.000000 way=1809&gt;
-osm-92080455 -> osm-92080381
-	&lt;Street name='10596654-1' length=6.382770 rise=0.000000 fall=0.000000 way=1809&gt;</pre>
-
-<h3>Loading Public Transit Data</h3> 
-
-Grab the GTFS file for your favorite transit agency. Here, we grab the GTFS for the transit system in Redding, CA:
-<pre style="background-color:#F5F5F5"> $ wget http://trilliumtransit.com/transit_feeds/redding/google_transit.zip -O redding_gtfs.zip</pre>
-<p>Compile the GTFS into a GTFSDB, and then compile that GTFSDB into a graph<p>
-<pre style="background-color:#F5F5F5"> $ gs_gtfsdb_build redding_gtfs.zip redding.gtfsdb
- $ gs_import_gtfs redding.gdb redding.gtfsdb</pre>
-<p>Use gs_gdb_inspect to check that your new transit graph is in good shape</p>
-<pre style="background-color:#F5F5F5"> $ gs_gdb_inspect redding.gdb sta-3622</pre>
-should print
-<pre style="background-color:#F5F5F5">sta-3622 -> psv-0-000-004
-	&lt;TripBoard int_sid=0 sid=105A166 agency=0 calendar=165157760 timezone=164034504 boardings=[('1572A105B166', 23964), ('1598A105B166', 27564), ('1602A105B166', 31164), ('1607A105B166', 34764), ('1600A105B166', 38364), ('1605A105B166', 41964), ('1603A105B166', 45564), ('1608A105B166', 49164), ('1601A105B166', 52764), ('1606A105B166', 56364), ('1599A105B166', 59964), ('1604A105B166', 63564), ('1609A105B166', 67164)]&gt;
-sta-3622 -> psv-0-000-004
-	&lt;TripBoard int_sid=1 sid=106A166 agency=0 calendar=165157760 timezone=164034504 boardings=[('2459A106B166', 34764), ('1635A106B166', 38364), ('1640A106B166', 41964), ('1638A106B166', 45564), ('1643A106B166', 49164), ('1636A106B166', 52764), ('1641A106B166', 56364), ('1634A106B166', 59964), ('1639A106B166', 63564), ('1637A106B166', 67164)]&gt;
-</pre>
-
-<h3>Intermingling Public Transit and Street Data</h3> 
-<p>You can load both OSM and GTFS data into the same graph, then run a command to link them.</p>
-<pre style="background-color:#F5F5F5"> $ gs_import_gtfs redding_all.gdb redding.gtfsdb
- $ gs_import_osm redding_all.gdb map.osmdb
- $ gs_link_osm_gtfs redding_all.gdb map.osmdb redding.gtfsdb</pre>
-<p>Inspect:</p>
-<pre style="background-color:#F5F5F5"> $ gs_gdb_inspect redding.gdb sta-3622</pre>
-<p>prints:</p>
-<pre style="background-color:#F5F5F5">sta-3622 -> osm-92366549
-	&lt;graphserver.core.Link object at 0x9a0b20c&gt;
-sta-3622 -> psv-0-000-004
-	&lt;TripBoard int_sid=0 sid=105A166 agency=0 calendar=163855912 timezone=161122808 boardings=[('1572A105B166', 23964), ('1598A105B166', 27564), ('1602A105B166', 31164), ('1607A105B166', 34764), ('1600A105B166', 38364), ('1605A105B166', 41964), ('1603A105B166', 45564), ('1608A105B166', 49164), ('1601A105B166', 52764), ('1606A105B166', 56364), ('1599A105B166', 59964), ('1604A105B166', 63564), ('1609A105B166', 67164)]&gt;
-sta-3622 -> psv-0-000-004
-	&lt;TripBoard int_sid=1 sid=106A166 agency=0 calendar=163855912 timezone=161122808 boardings=[('2459A106B166', 34764), ('1635A106B166', 38364), ('1640A106B166', 41964), ('1638A106B166', 45564), ('1643A106B166', 49164), ('1636A106B166', 52764), ('1641A106B166', 56364), ('1634A106B166', 59964), ('1639A106B166', 63564), ('1637A106B166', 67164)]&gt;</pre>
-
-<h3>Inspecting the graph with gs_crawl</h3>
-<p>Start gs_crawl, a little graph inspection web service</p>
-<pre style="background-color:#F5F5F5"> $ gs_crawl redding.gdb 80</pre>
-<p>Then steer your web browser to the appropriate location.<p>
-<p>If you're using Amazon EC2, using your own public DNS:</p>
-<pre style="background-color:#F5F5F5">http://YOUR-EC2-ADDRESS.compute-1.amazonaws.com/</pre>
-<p>Or if you're simply running on your local machine:</p>
-<pre style="background-color:#F5F5F5">http://localhost:80/</pre>
- 
-<h3 id="routeserver">Getting routes with gs_routeserver</h3>
-<p>First, you'll need PyYAML</p>
-<pre style="background-color:#F5F5F5"> $ sudo easy_install pyyaml</pre>
-<p>The routeserver finds a path, and then uses a series of "handlers" to convert that path into a human-readable format. Those handlers are enumearted and set up by a configuration file called handlers.yaml. Graphserver comes with an example handlers.yaml which you can use to get started</p>
-<pre style="background-color:#F5F5F5"> $ cp /path/to/graphserver/pygs/graphserver/ext/routeserver/handlers.yaml .</pre>
-<p>This handlers.yaml file is filled with "CHANGEME" stubs. Replace every "CHANGEME.gtfsdb" with "redding.gtfsdb" and every "CHANGEME.osmdb" with "redding.osmdb"</p>
-<p>Fire up a routeserver on the compiled graph</p>
-<pre style="background-color:#F5F5F5"> $ gs_routeserver redding.gdb handlers.yaml -p 80</pre>
-<p>Get a list of all vertices in the system</p>
-<pre style="background-color:#F5F5F5">http://YOUR_DOMAIN_NAME/vertices</pre>
-<p>Get a route narrative</p>
-<pre style="background-color:#F5F5F5">http://YOUR_DOMAIN_NAME/path?origin="osm-92011649"&amp;dest="sta-3803"&amp;currtime=1260839444</pre>
-<p>or</p>
-<pre style="background-color:#F5F5F5">http://YOUR_DOMAIN_NAME/path_raw?origin="osm-92011649"&amp;dest="sta-3803"&amp;currtime=1260839444</pre>
-
-<h3>What about a really big city?</h3>
-<p>First, get Java 1.6. Or Java6. I think they're the same thing. Get the JDK, but not the JVM, the JRE, SDK, SDN, or the JCE. Note Java SE comes with Jave EE, which is apparently at version 5, and may or may not have anything to do with J2EE. I don't know what those have to do with anything. Google it or something. I don't know. They don't make it particularly easy for you. It's like, they've got more money than god and nothing pleases them better than pouring all that expertise into baffling the hell out of you. Honestly, I can't stand Java, but you need it to run Osmosis.</p>
-<p>Then, get Osmosis</p>
-<pre style="background-color:#F5F5F5"> $ wget http://gweb.bretth.com/osmosis-latest.zip
- $ unzip osmosis-latest.zip
- $ chmod a+x ./osmosis-0.30/bin/osmosis</pre>
-<p>Download a biggie GTFS file. Here's the one for the Seattle area:</p>
-<pre style="background-color:#F5F5F5"> $ wget http://www.gtfs-data-exchange.com/gtfs/badhill_20091208_1910.zip</pre>
-<p>Compile it into a GTFSDB. This will take a few minutes</p>
-<pre style="background-color:#F5F5F5"> $ gs_gtfsdb_build badhill_20091208_1910.zip kingco.gtfsdb</pre>
-<p>Check the bounds of the GTFSDB</p>
-<pre style="background-color:#F5F5F5"> $ sqlite3 kingco.gtfsdb "select min(stop_lon),min(stop_lat),max(stop_lon),max(stop_lat) from stops"</pre>
-returns:
-<pre style="background-color:#F5F5F5">-122.506729|47.1553345|-121.78244|47.9323654</pre>
-This will come in handy soon.
-<p>Get a huge chunk of OSM data from the CloudMade state files. Here's Washington State:</p>
-<pre style="background-color:#F5F5F5"> $ wget http://downloads.cloudmade.com/north_america/united_states/washington/washington.osm.highway.bz2
- $ bunzip2 washington.osm.highway.bz2</pre>
-<p>Then, use the bounding box coordinates we just got to cut down the OSM file to the area surrounding the agency. Check it:<p>
-<pre style="background-color:#F5F5F5"> $ /path/to/osmosis-0.30/bin/osmosis --read-xml washington.osm.highway --bounding-box left=-122.506729 bottom=47.1553345 right=-121.78244 top=47.9323654 --write-xml kingco.osm</pre>
-<p>Then, compile and set it up like normal. It's a trip-planning bonanza.</p>
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-
-				<div class="entry">
-					<p>People frequently ask me how I manage to collect and input the data that is used by hbus.ca, given Metro Transit&#8217;s intransigence. The &#8220;bike and GPS&#8221; angle is well known <a href="http://www.thecoast.ca/halifax/beta-the-public-transit-day-tripper/Content?oid=1098826">by now</a>, but what about the rest of the process? How do I get the data into a format that hbus.ca can consume?</p>
-<p>The defacto standard for the interchange of transit information is <a href="http://code.google.com/p/googletransitdatafeed">Google Transit Feed</a> (GTFS). This exceedingly simple comma seperated value format is now supported by a plethora of software, including <a href="http://google.com/transit">Google Transit</a>, <a href="http://github.com/bmander/graphserver">graphserver</a>, as well as my very own <a href="http://github.com/wlach/libroutez">libroutez</a> (used by hbus.ca). It was obvious to me right from the beginning that the first step to building hbus.ca would be to create one of these feeds. </p>
-<p>Manipulating a GTFS by hand is probably not a great idea. It&#8217;s basically a dump of a relational database, and is pretty inscrutable from the point of view of a human being. What I really want to be able to do is be able<br />
-to manipulate things on the level of stops, service periods, and routes&#8211; and let some kind of abstraction layer take care of the low-level details. Fortunately, the awesome engineers at google created a python library called <a href="http://code.google.com/p/googletransitdatafeed">Google Transit Data Feed</a>, which can help with creating one of these things by providing abstractions of the key elements of a google transit feed (stops, service periods, etc.). You can then write a program which uses these abstractions to create and save a GTFS.</p>
-<p>Of course, providing the library appropriate information is easier said than done. Metro Transit&#8217;s PDF schedules are not readily computer parsable (being designed to be printed out, after all). I needed some kind of semi-automated way of converting a Metro Transit schedule into GTFS, or this whole project was<br />
-going nowhere fast. </p>
-<p>As an initial step, it turns out that it&#8217;s quite possible to extract textual information from a PDF using the open source <a href="http://poppler.freedesktop.org/">popplar</a> library. From there, it&#8217;s possible to extract the stopping times for an individual bus route. Let&#8217;s give an example. For example, let&#8217;s take the case of adding the 60 (Portland Hill&#8217;s route), something I&#8217;m currently working on. All I had to do was download the PDF file from Metro Transit&#8217;s site and then run the following on the command line:<br />
-<code><br />
-pdftotext -raw route60.pdf<br />
-</code><br />
-The raw option basically makes sure the raw strings are dumped to disk, and that no attempt is made to preserve formatting. The result is a text file with content like this in it:<br />
-<code><br />
-842a 847a 855a 858a 903a 906a 912a -<br />
-857a 902a 910a 913a 918a 921a - 925a<br />
-910a 915a 923a 926a 931a 934a 940a -<br />
-940a 945a 953a - 1000a 1003a 1009a -<br />
-...and every 30 minutes until<br />
-210p 215p 223p - 230p 233p 239p -<br />
-</code><br />
-This type of format can be parsed easily enough. To create a proper transit feed though, schedule information isn&#8217;t enough: you also need to know the locations of the stops, names of routes, etc. After some deliberation, I came to the determination that I needed some kind of intermediate format to store the above schedule information and this additional information. It would be readable both by humans (to ease its creation) and machines.</p>
-<p>The obvious markup for something like this is <a href="http://yaml.org">YAML</a> (if you&#8217;re still using XML to store structured information, run, don&#8217;t walk, and look at YAML: you can thank me later). Simple, clean, effective. GTFS is still the better choice for using the information in another application as its representation is much more amenable to being stored in a graph. Here&#8217;s a few examples of my YAML format in action:</p>
-<p><a href="http://github.com/wlach/halifax-transit-feed/blob/fef68c18928272670b3c57ae5530260deed85883/7-robie-to-gottingen.yml">7 (Robie to Gottingen)</a><br />
-<a href="http://github.com/wlach/halifax-transit-feed/blob/fef68c18928272670b3c57ae5530260deed85883/10-to-westphal.yml">10 (Westphal)</a></p>
-<p>Besides the scheduling information, the other main interesting component of a GTFS is the location of the stops. As anyone who&#8217;s used a Metro Transit schedule has noticed, only major timepoints are covered in the PDF schedules. What of all the stops in between? This is where the bike and GPS come in.</p>
-<p>What I did was take a standard GPS from Mountain Equipment Co-op (The Garmin GPSMap 60x), get on my bike, take the readings of individual gotime numbers and positioning information, of the individual stops between the major timepoints. I then took this device back to my computer and, using a utility called <a href="http://gpsbabel.org">GPSBabel</a>, dumped out the stop information in a format called &#8220;comma seperated value&#8221;. It looks like this:<br />
-<code><br />
-44.65825, -63.59252, 6785-21-31-33-34-35-3-7<br />
-44.65982, -63.59452, 6768-21-31-33-35-86-3-7<br />
-44.66113, -63.59659, 6782-21-31-33-34-35-3-7<br />
-</code><br />
-The first two items are latitude and longitude, providing the positioning of the stop. The last item is a gotime number, followed by the set of buses which pass by the stop. Turning this into YAML is a matter of applying<br />
-the following regular expression to the input:<br />
-<code><br />
-\([0-9]+.[0-9]+\), \(-63.[0-9]+\), \([0-9]+\)- -> - { name: xxx, stop_code: \3, lat: \1, lng: \2 }<br />
-</code><br />
-To get an actual name for the stop (i.e.: &#8220;Gottingen and Young&#8221;), I wrote a simple script which finds the nearest intersection close to the stop in the <a href="http://geobase.ca">GeoBase</a> dataset. I then (at my discretion) corrected it based on my on-the-street knowledge of the layout of Halifax as well as adding certain details to help the user (e.g. bus stops on the way to the south end of Halifax are marked &#8220;south bound&#8221;).</p>
-<p>With these two elements in place (a format for creating human-readable transit information and a library for creating GTFS), the only thing left to do is create a program which bridges the gap. Behold, the magic of<br />
-<a href="http://github.com/wlach/halifax-transit-feed/blob/fef68c18928272670b3c57ae5530260deed85883/createfeed.py">createfeed.py</a>. With all of this in place, creating a google transit feed for Halifax is a simple matter of typing &#8220;make&#8221;.</p>
-<p>Is this a ridiculous amount of work? I wouldn&#8217;t say so. The vast, vast majority of my work on hbus.ca has been in creating the pathfinding code and geocoding functionality. This is work that can be translated to many different municipalities, and can easily be extended and made more useful in a myriad of ways.</p>
-<p>What does seem a little intimidating to me is completing what I started. Capturing bus stop information for the Halifax peninsula is one thing, but covering the outlying areas (Bayer&#8217;s Lake, Sackville, etc.) is quite<br />
-another. There&#8217;s a lot of biking involved there, more perhaps than what one person can reasonably be expected to do. It was my hope that the initial release of hbus would validate the model of community-developed transit software to Metro Transit and they would see the benefit of releasing their internal copy of this data to the public, but unfortunately that doesn&#8217;t seem to have happened. </p>
-<p>Getting that problem solved seems to be more a political problem than a technical one, and it&#8217;s not my specialty. It really does make me wonder if I shouldn&#8217;t reconsider the option of crowd sourcing, which I had<br />
-<a href="http://masalalabs.ca/2009/03/hbusca-and-thoughts-about-crowdsourcing/">rejected</a> earlier.</p>
-				</div>
-
-				<p class="postmetadata"> Posted in <a href="http://hbus.ca/blog/?cat=1" title="View all posts in Uncategorized" rel="category">Uncategorized</a> |   <a href="http://hbus.ca/blog/?p=9#respond" title="Comment on Creating a google transit feed for fun and profit">No Comments &#187;</a></p>
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 Binary files a/origin-src/wlach-halifax-transit-feed-fef68c1.tar.gz and /dev/null differ
--- a/origin-src/wlach-halifax-transit-feed-fef68c1/.gitignore
+++ /dev/null
@@ -1,3 +1,1 @@
-hfxfeed.zip
-hfxtable.yml
-*~
+

--- a/origin-src/wlach-halifax-transit-feed-fef68c1/1-to-dartmouth.yml
+++ /dev/null
@@ -1,214 +1,1 @@
-short_name: 1
-long_name: To Dartmouth
-time_points: [ 7284, 7412, 6087, 7351, 7151 ]
-between_stops:  
-  7284-7412: [ 6203, 7423 ]
-  7412-6087: [ 7419, 7409, 7402, 6453, 6447, 6449, 6454, 6452, 8328, 8337, 8333, 8336, 8327, 8338, 6121, 6106 ]
-  6087-7351: [ 6455, 6773, 6778, 6779, 6775, 6787 ]
-stop_times: [
-  [ -, -, -, 604a, 607a],
-  [ 600a, 611a, 625a, 633a, 637a],
-  [ 610a, 621a, 635a, 643a, 647a],
-  [ 620a, 631a, 645a, 653a, 657a],
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-  [ 925a, 938a, 953a, 1001a, 1005a],
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-  [ 1010a, 1023a, 1038a, 1046a, 1050a],
-  [ 1025a, 1038a, 1053a, 1101a, 1105a],
-  [ 1040a, 1053a, 1108a, 1116a, 1120a],
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-  [ 1110a, 1123a, 1138a, 1146a, 1150a],
-  [ 1125a, 1138a, 1153a, 1201p, 1205p],
-  [ 1140a, 1153a, 1208p, 1216p, 1220p],
-  [ 1155a, 1208p, 1223p, 1231p, 1235p],
-  [ 1210p, 1223p, 1238p, 1246p, 1250p],
-  [ 1225p, 1238p, 1253p, 101p, 105p],
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-  [ 520p, 533p, 548p, 556p, 600p],
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-  [ 540p, 553p, 608p, 616p, 620p],
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-  [ 600p, 613p, 627p, 635p, 639p],
-  [ 615p, 626p, 640p, 648p, 652p],
-  [ 630p, 641p, 655p, 703p, 707p],
-  [ 645p, 656p, 710p, 718p, 722p],
-  [ 700p, 711p, 725p, 733p, 737p],
-  [ 715p, 726p, 740p, 748p, 752p],
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-  [ 745p, 756p, 810p, 818p, 822p],
-  [ 800p, 811p, 825p, 833p, 837p],
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-  [ 1115p, 1126p, 1140p, 1148p, 1152p],
-  [ 1150p, 1201x, 1215x, 1221x, 1225x],
-  [ 1215x, 1226x, 1240x, 1248x, 1252x]
-]
-stop_times_saturday: [
-  [ -, -, -, 602a, 605a],
-  [ -, -, -, -, -],
-  [ 605a, 616a, 628a, 634a, 637a],
-  [ 620a, 631a, 643a, 649a, 652a],
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