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  • Optimising RSS parsing on App Engine to avoid high CPU warnings

    - by Danny Tuppeny
    I'm pulling some RSS feeds into a datastore in App Engine to serve up to an iPhone app. I use cron to schedule updating the RSS every x minutes. Each task only parses one RSS feed (which has 15-20 items). I frequently get warnings about high CPU usage in the App Engine dashboard, so I'm looking for ways to optimise my code. Currently, I use minidom (since it's already there on App Engine), but I suspect it's not very efficient! Here's the code: dom = minidom.parseString(urlfetch.fetch(url).content) if dom: items = [] for node in dom.getElementsByTagName('item'): item = RssItem( key_name = self.getText(node.getElementsByTagName('guid')[0].childNodes), title = self.getText(node.getElementsByTagName('title')[0].childNodes), description = self.getText(node.getElementsByTagName('description')[0].childNodes), modified = datetime.now(), link = self.getText(node.getElementsByTagName('link')[0].childNodes), categories = [self.getText(category.childNodes) for category in node.getElementsByTagName('category')] ); items.append(item); db.put(items); def getText(self, nodelist): rc = '' for node in nodelist: if node.nodeType == node.TEXT_NODE: rc = rc + node.data return rc There isn't much going on, but the scripts often take 2-6 seconds CPU time, which seems a bit excessive for looping through 20ish items and reading a few attributes. What can I do to make this faster? Is there anything particularly bad in the above code, or should I change to another way of parsing? Are there are any libraries (that work on App Engine) that would be better, or would I be better parsing the RSS myself?

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  • Multi choice form field in Django

    - by Dingo
    Hi! I'am developing application on app-engine-path. I would like to make form with multichoice (acceptably languages for user). Code look like this: Language settings: settings.LANGUAGES = ((u"cs", u"Ceština"), (u"en", u"English")) Form model: class UserForm(forms.ModelForm): first_name = forms.CharField(max_length=100) last_name = forms.CharField(max_length=100) languages = forms.MultipleChoiceField(widget=forms.CheckboxSelectMultiple, choices=settings.LANGUAGES) The form is rendered o.k. (all languages have checkbox. IDs, NAMEs is ok.) But if I save some languages for user, those languages don't check checkboxes. User model look like this class User(User): #... languages = db.StringListProperty() #... and view: def edit_profile(request): user = request.user if request.method == 'POST': form = UserForm(request.POST) if form.is_valid(): # ... else: form = UserForm(instance=user) data = {"user":user, "form": form} return render_to_response(request, 'user_profile/user_profile.html', data)

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  • Problem trying to achieve a join using the `comments` contrib in Django

    - by NiKo
    Hi, Django rookie here. I have this model, comments are managed with the django_comments contrib: class Fortune(models.Model): author = models.CharField(max_length=45, blank=False) title = models.CharField(max_length=200, blank=False) slug = models.SlugField(_('slug'), db_index=True, max_length=255, unique_for_date='pub_date') content = models.TextField(blank=False) pub_date = models.DateTimeField(_('published date'), db_index=True, default=datetime.now()) votes = models.IntegerField(default=0) comments = generic.GenericRelation( Comment, content_type_field='content_type', object_id_field='object_pk' ) I want to retrieve Fortune objects with a supplementary nb_comments value for each, counting their respectve number of comments ; I try this query: >>> Fortune.objects.annotate(nb_comments=models.Count('comments')) From the shell: >>> from django_fortunes.models import Fortune >>> from django.db.models import Count >>> Fortune.objects.annotate(nb_comments=Count('comments')) [<Fortune: My first fortune, from NiKo>, <Fortune: Another One, from Dude>, <Fortune: A funny one, from NiKo>] >>> from django.db import connection >>> connection.queries.pop() {'time': '0.000', 'sql': u'SELECT "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", "django_fortunes_fortune"."slug", "django_fortunes_fortune"."content", "django_fortunes_fortune"."pub_date", "django_fortunes_fortune"."votes", COUNT("django_comments"."id") AS "nb_comments" FROM "django_fortunes_fortune" LEFT OUTER JOIN "django_comments" ON ("django_fortunes_fortune"."id" = "django_comments"."object_pk") GROUP BY "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", "django_fortunes_fortune"."slug", "django_fortunes_fortune"."content", "django_fortunes_fortune"."pub_date", "django_fortunes_fortune"."votes" LIMIT 21'} Below is the properly formatted sql query: SELECT "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", "django_fortunes_fortune"."slug", "django_fortunes_fortune"."content", "django_fortunes_fortune"."pub_date", "django_fortunes_fortune"."votes", COUNT("django_comments"."id") AS "nb_comments" FROM "django_fortunes_fortune" LEFT OUTER JOIN "django_comments" ON ("django_fortunes_fortune"."id" = "django_comments"."object_pk") GROUP BY "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", "django_fortunes_fortune"."slug", "django_fortunes_fortune"."content", "django_fortunes_fortune"."pub_date", "django_fortunes_fortune"."votes" LIMIT 21 Can you spot the problem? Django won't LEFT JOIN the django_comments table with the content_type data (which contains a reference to the fortune one). This is the kind of query I'd like to be able to generate using the ORM: SELECT "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", COUNT("django_comments"."id") AS "nb_comments" FROM "django_fortunes_fortune" LEFT OUTER JOIN "django_comments" ON ("django_fortunes_fortune"."id" = "django_comments"."object_pk") LEFT OUTER JOIN "django_content_type" ON ("django_comments"."content_type_id" = "django_content_type"."id") GROUP BY "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", "django_fortunes_fortune"."slug", "django_fortunes_fortune"."content", "django_fortunes_fortune"."pub_date", "django_fortunes_fortune"."votes" LIMIT 21 But I don't manage to do it, so help from Django veterans would be much appreciated :) Hint: I'm using Django 1.2-DEV Thanks in advance for your help.

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  • What algorithms are suitable for this simple machine learning problem?

    - by user213060
    I have a what I think is a simple machine learning question. Here is the basic problem: I am repeatedly given a new object and a list of descriptions about the object. For example: new_object: 'bob' new_object_descriptions: ['tall','old','funny']. I then have to use some kind of machine learning to find previously handled objects that had similar descriptions, for example, past_similar_objects: ['frank','steve','joe']. Next, I have an algorithm that can directly measure whether these objects are indeed similar to bob, for example, correct_objects: ['steve','joe']. The classifier is then given this feedback training of successful matches. Then this loop repeats with a new object. a Here's the pseudo-code: Classifier=new_classifier() while True: new_object,new_object_descriptions = get_new_object_and_descriptions() past_similar_objects = Classifier.classify(new_object,new_object_descriptions) correct_objects = calc_successful_matches(new_object,past_similar_objects) Classifier.train_successful_matches(object,correct_objects) But, there are some stipulations that may limit what classifier can be used: There will be millions of objects put into this classifier so classification and training needs to scale well to millions of object types and still be fast. I believe this disqualifies something like a spam classifier that is optimal for just two types: spam or not spam. (Update: I could probably narrow this to thousands of objects instead of millions, if that is a problem.) Again, I prefer speed when millions of objects are being classified, over accuracy. What are decent, fast machine learning algorithms for this purpose?

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  • Cookies with urllib

    - by CMC
    This will probably seem like a really simple question, and I am quite confused as to why this is so difficult for me. I would like to write a function that takes three inputs: [url, data, cookies] that will use urllib (not urllib2) to get the contents of the requested url. I figured it'd be simple, so I wrote the following: def fetch(url, data = None, cookies = None): if isinstance(data, dict): data = urllib.urlencode(data) if isinstance(cookies, dict): # TODO: find a better way to do this cookies = "; ".join([str(key) + "=" + str(cookies[key]) for key in cookies]) opener = urllib.FancyURLopener() opener.addheader("Cookie", cookies) obj = opener.open(url, data) result = obj.read() obj.close() return result This doesn't work, as far as I can tell (can anyone confirm that?) and I'm stumped.

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  • Django models avaoid duplicates

    - by Hulk
    In models, class Getdata(models.Model): title = models.CharField(max_length=255) state = models.CharField(max_length=2, choices=STATE, default="0") name = models.ForeignKey(School) created_by = models.ForeignKey(profile) def __unicode__(self): return self.id() In templates <form> <input type="submit" save the data/> </form> If the user clicks on the save button and the above data is saved in the table how to avoid the duplicates,i.e, if the user again clicks on the same submit button there should not be another entry for the same values.Or is it some this that has to be handeled in views Thanks..

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  • How To Create Per-Request Singleton in Pylons?

    - by dave mankoff
    In our Pylons based web-app, we're creating a class that essentially provides some logging functionality. We need a new instance of this class for each http request that comes in, but only one per request. What is the proper way to go about this? Should we just create the object in middleware and store in in request.environ? Is there a more appropriate way to go about this?

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  • Socket Lose Connection

    - by Dave Dixon
    I know Twisted can do this well but what about just plain socket? How'd you tell if you randomly lost your connection in socket? Like, If my internet was to go out of a second and come back on.

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  • PGU Tiles collision detection

    - by user280454
    Hi, I've been using PGU(Phil's Pygame Utilities) for a while. It has a dictionary called tdata, which is passed as an argument while loading tiles tdata = { tileno:(agroup, hit_handler, config)} I'm making a pacman clone in which I have 2 groups : player and ghost, for which I want to collision detection with the same type of tile. For example, if the tile no is 2, I want this tile to have agroups as both player and ghost. I tried doing the following: tdata = {0x02 :('player', tile_hit_1, config), 0x02 : ('ghost', tile_hit_2, config)} However, on doing this, it only gives collision detection for ghost, not the player. Any ideas on how I can do collision detection for both the player and the ghost with the same type of tile?

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  • store/load numpy array from binary files

    - by Javier
    Dear all, I would like to store and load numpy arrays from binary files. For that purposes, I created two small functions. Each binary file should contain the dimensionality of the given matrix. def saveArrayToFile(data, fileName): with open(fileName, 'w') as file: a = array.array('f') nSamples, ndim = data.shape a.extend([nSamples, ndim]) # write number of elements and dimensions a.fromstring(data.tostring()) a.tofile(file) def readArrayFromFile(fileName): _featDesc = np.fromfile(fileName, 'f') _ndesc = int(_featDesc[0]) _ndim = int(_featDesc[1]) _featDesc = _featDesc[2:] _featDesc = _featDesc.reshape([_ndesc, _ndim]) return _featDesc, _ndesc, _ndim An example on how to use the functions is: myarr=np.array([[7, 4],[3, 9],[1, 3]]) saveArrayToFile(myarr,'myfile.txt') _featDesc, _ndesc, _ndim = readArrayFromFile('myfile.txt') However, an error message of 'ValueError: total size of new array must be unchanged' is shown. My arrays can be of size MxN and MxM. Any suggestions are more than welcomed. I think the problem might be in the saveArrayToFile function. Best wishes, Javier

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  • Iterating through nested dictionaries

    - by Framester
    I want to write an iterator for my 'toy' Trie implementation. Adding already works like this: class Trie: def __init__(self): self.root = dict() pass def add(self, string, value): global nops current_dict = self.root for letter in s: nops += 1 current_dict = current_dict.setdefault(letter, {}) current_dict = current_dict.setdefault('value', value) pass The output of the adding looks like that: trie = Trie() trie.add("hello",1) trie.add("world",2) trie.add("worlds",12) print trie.root {'h': {'e': {'l': {'l': {'o': {'value': 1}}}}}, 'w': {'o': {'r': {'l': {'d': {'s': {'value': 2}, 'value': 2}}}}}} I know, that I need a __iter__ and next method. def __iter__(self): self.root.__iter__() pass def next(self): print self.root.next() But AttributeError: 'dict' object has no attribute 'next'. How should I do it? [Update] In the perfect world I would like the output to be one dict with all the words/entries with their corresponding values.

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  • Pretty-printing of numpy.array

    - by camillio
    Hello, I'm curious, whether there is any way to print formated numpy.arrays, e.g., in the way similar to this: x = 1.23456 print '%.3f' % x If I want to print the numpy.array of floats, it prints several decimals, often in 'scientific' format, which is rather hard to read even for low-dimensional arrays. However, numpy.array apparently has to be printed as a string, i.e., with %s. Is there any solution ready for this purpose? Many thanks in advance :-)

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  • How to chroot Django

    - by Brian M. Hunt
    Can one run Django in a chroot? Notably, what's necessary in order to set up (for example) /var/www as a chroot'd directory and then have Django run in that chroot'd directory? Thank you - I'm grateful for any input.

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  • how to load an image to a grid using pygame, instead of just using a fill color?

    - by yao jiang
    I am trying to create a "map of a city" using pygame. I want to be able to put images of buildings in specific grid coords rather than just filling them in with a color. This is how I am creating this map grid: def clear(): for r in range(rows): for c in range(rows): if r%3 == 1 and c%3 == 1: color = brown; grid[r][c] = 1; else: color = white; grid[r][c] = 0; pygame.draw.rect(screen, color, [(margin+width)*c+margin, (margin+height)*r+margin, width, height]) pygame.display.flip(); Now how do I put images of buildings in those brown colored grids at those specific locations? I've tried some of the samples online but can't seem to get them to work. Any help is appreciated. If anyone have a good source for free sprites that I can use for pygame, please let me know. Thanks!

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  • How hard is it to modify the Django Models?

    - by alex
    I am doing geolocation, and Django does not have a PointField. So, I am forced to writing in RAW SQL. GeoDjango, the Django library, does not support the following query for MYSQL databases (can someone verify that for me?) cursor.execute("SELECT id FROM l_tag WHERE\ (GLength(LineStringFromWKB(LineString(asbinary(utm),asbinary(PointFromWKB(point(%s, %s)))))) < %s + accuracy + %s)\ I don't nkow why GeoDjango library cannot do this in MYSQL database. I hate writing RAW SQL for calculating distances between two points. Is there a way I can create my own library for Django that can handle this? If so, how hard is it?

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  • Pylons/Routes Did url_for() change within templates?

    - by Charles Merram
    I'm getting an error: GenerationException: url_for could not generate URL. Called with args: () {} from this line of a mako template: <p>Your url is ${h.url_for()}</p> Over in my helpers.py, I do have: from routes import url_for Looking at the Routes-1.12.1-py2.6.egg/routes/util.py, I seem to go wrong about line it calls _screenargs(). This is simple functionality from the Pylons book. What silly thing am I doing wrong? Was there a new url_current()? Where?

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  • Django TestCase testing order

    - by ziang
    If there are several methods in the test class, I found that the order to execute is alphabetical. But I want to customize the order of execution. How to define the execution order? For example: testTestA will be loaded first than testTestB. class Test(TestCase): def setUp(self): ... def testTestB(self): #test code def testTestA(self): #test code

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  • Math on Django Templates

    - by Leandro Abilio
    Here's another question about Django. I have this code: views.py cursor = connections['cdr'].cursor() calls = cursor.execute("SELECT * FROM cdr where calldate > '%s'" %(start_date)) result = [SQLRow(cursor, r) for r in cursor.fetchall()] return render_to_response("cdr_user.html", {'calls':result }, context_instance=RequestContext(request)) I use a MySQL query like that because the database is not part of a django project. My cdr table has a field called duration, I need to divide that by 60 and multiply the result by a float number like 0.16. Is there a way to multiply this values using the template tags? If not, is there a good way to do it in my views? My template is like this: {% for call in calls %} <tr class="{% cycle 'odd' 'even' %}"><h3> <td valign="middle" align="center"><h3>{{ call.calldate }}</h3></td> <td valign="middle" align="center"><h3>{{ call.disposition }}</h3></td> <td valign="middle" align="center"><h3>{{ call.dst }}</h3></td> <td valign="middle" align="center"><h3>{{ call.billsec }}</h3></td> <td valign="middle" align="center">{{ (call.billsec/60)*0.16 }}</td></h3> </tr> {% endfor %} The last is where I need to show the value, I know the "(call.billsec/60)*0.16" is impossible to be done there. I wrote it just to represent what I need to show.

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  • Authkit - deferring action for HTTP '401' response to client application

    - by jon
    Form, Redirect and Forward all send an unauthenticated user to a Form on a login page specified within an Authkit middleware application. I'd like to allow a client application to request a service via XHR and then present a custom 'client side' form if a HTTP status code of 401 is returned, which would then post to Authkit for authentication until valid authentication/authorization occured. Specifically, 1) a jquery $.get request might request a resource. 2) if an Authkit cookie check confirmed previous authorization the content would be returned. 3) if not I would like Authkit to simply return the '401 response' (and not redirect to another page, or return a form template) where a client side exception handler would notify the user and present an authentication form. Can Authkit work like this?

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  • PyML 0.7.2 - How to prevent accuracy from dropping after storing/loading a classifier?

    - by Michael Aaron Safyan
    This is a followup from "Save PyML.classifiers.multi.OneAgainstRest(SVM()) object?". The solution to that question was close, but not quite right, (the SparseDataSet is broken, so attempting to save/load with that dataset container type will fail, no matter what. Also, PyML is inconsistent in terms of whether labels should be numbers or strings... it turns out that the oneAgainstRest function is actually not good enough, because the labels need to be strings and simultaneously convertible to floats, because there are places where it is assumed to be a string and elsewhere converted to float) and so after a great deal of hacking and such I was finally able to figure out a way to save and load my multi-class classifier without it blowing up with an error.... however, although it is no longer giving me an error message, it is still not quite right as the accuracy of the classifier drops significantly when it is saved and then reloaded (so I'm still missing a piece of the puzzle). I am currently using the following custom mutli-class classifier for training, saving, and loading: class SVM(object): def __init__(self,features_or_filename,labels=None,kernel=None): if isinstance(features_or_filename,str): filename=features_or_filename; if labels!=None: raise ValueError,"Labels must be None if loading from a file."; with open(os.path.join(filename,"uniquelabels.list"),"rb") as uniquelabelsfile: self.uniquelabels=sorted(list(set(pickle.load(uniquelabelsfile)))); self.labeltoindex={}; for idx,label in enumerate(self.uniquelabels): self.labeltoindex[label]=idx; self.classifiers=[]; for classidx, classname in enumerate(self.uniquelabels): self.classifiers.append(PyML.classifiers.svm.loadSVM(os.path.join(filename,str(classname)+".pyml.svm"),datasetClass = PyML.VectorDataSet)); else: features=features_or_filename; if labels==None: raise ValueError,"Labels must not be None when training."; self.uniquelabels=sorted(list(set(labels))); self.labeltoindex={}; for idx,label in enumerate(self.uniquelabels): self.labeltoindex[label]=idx; points = [[float(xij) for xij in xi] for xi in features]; self.classifiers=[PyML.SVM(kernel) for label in self.uniquelabels]; for i in xrange(len(self.uniquelabels)): currentlabel=self.uniquelabels[i]; currentlabels=['+1' if k==currentlabel else '-1' for k in labels]; currentdataset=PyML.VectorDataSet(points,L=currentlabels,positiveClass='+1'); self.classifiers[i].train(currentdataset,saveSpace=False); def accuracy(self,pts,labels): logger=logging.getLogger("ml"); correct=0; total=0; classindexes=[self.labeltoindex[label] for label in labels]; h=self.hypotheses(pts); for idx in xrange(len(pts)): if h[idx]==classindexes[idx]: logger.info("RIGHT: Actual \"%s\" == Predicted \"%s\"" %(self.uniquelabels[ classindexes[idx] ], self.uniquelabels[ h[idx] ])); correct+=1; else: logger.info("WRONG: Actual \"%s\" != Predicted \"%s\"" %(self.uniquelabels[ classindexes[idx] ], self.uniquelabels[ h[idx] ])) total+=1; return float(correct)/float(total); def prediction(self,pt): h=self.hypothesis(pt); if h!=None: return self.uniquelabels[h]; return h; def predictions(self,pts): h=self.hypotheses(self,pts); return [self.uniquelabels[x] if x!=None else None for x in h]; def hypothesis(self,pt): bestvalue=None; bestclass=None; dataset=PyML.VectorDataSet([pt]); for classidx, classifier in enumerate(self.classifiers): val=classifier.decisionFunc(dataset,0); if (bestvalue==None) or (val>bestvalue): bestvalue=val; bestclass=classidx; return bestclass; def hypotheses(self,pts): bestvalues=[None for pt in pts]; bestclasses=[None for pt in pts]; dataset=PyML.VectorDataSet(pts); for classidx, classifier in enumerate(self.classifiers): for ptidx in xrange(len(pts)): val=classifier.decisionFunc(dataset,ptidx); if (bestvalues[ptidx]==None) or (val>bestvalues[ptidx]): bestvalues[ptidx]=val; bestclasses[ptidx]=classidx; return bestclasses; def save(self,filename): if not os.path.exists(filename): os.makedirs(filename); with open(os.path.join(filename,"uniquelabels.list"),"wb") as uniquelabelsfile: pickle.dump(self.uniquelabels,uniquelabelsfile,pickle.HIGHEST_PROTOCOL); for classidx, classname in enumerate(self.uniquelabels): self.classifiers[classidx].save(os.path.join(filename,str(classname)+".pyml.svm")); I am using the latest version of PyML (0.7.2, although PyML.__version__ is 0.7.0). When I construct the classifier with a training dataset, the reported accuracy is ~0.87. When I then save it and reload it, the accuracy is less than 0.001. So, there is something here that I am clearly not persisting correctly, although what that may be is completely non-obvious to me. Would you happen to know what that is?

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  • How to list directory hierarchy in PyGTK treeview widget?

    - by lyrae
    I am trying to generate a hierarchical directory listing in pyGTK. Currently, I have this following directory tree: /root folderA - subdirA - subA.py - a.py folderB - b.py I have written a function that -almost- seem to work: def go(root, piter = None): for filename in os.listdir(root): isdir = os.path.isdir(os.path.join(root, filename)) piter = self.treestore.append(piter, [filename]) if isdir == True: go(os.path.join(root, filename), piter) This is what i get when i run the app: I also think my function is inefficient and that i should be using os.walk(), since it already exists for such purpose. How can I, and what is the proper/most efficient way of generating a directory tree with pyGTK?

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