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  • [numpy] storing record arrays in object arrays

    - by Peter Prettenhofer
    I'd like to convert a list of record arrays -- dtype is (uint32, float32) -- into a numpy array of dtype np.object: X = np.array(instances, dtype = np.object) where instances is a list of arrays with data type np.dtype([('f0', '<u4'), ('f1', '<f4')]). However, the above statement results in an array whose elements are also of type np.object: X[0] array([(67111L, 1.0), (104242L, 1.0)], dtype=object) Does anybody know why? The following statement should be equivalent to the above but gives the desired result: X = np.empty((len(instances),), dtype = np.object) X[:] = instances X[0] array([(67111L, 1.0), (104242L, 1.0), dtype=[('f0', '<u4'), ('f1', '<f4')]) thanks & best regards, peter

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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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  • find the colour name from a hexadecimal colour code

    - by sree01
    Hi , i want to find the name of a colour from the hexadecimal colour code. When i get a hex colour code i want to find the most matching colour name. for example for the code #c06040 , how to find out if it is a shade of brown, blue or yellow ?. so that i can find the colour of an object in the image without human intervention. Is there any relation between the hexadecimal code of the shades of a colour? please give some sample code if there is any.

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  • user inheritance in django

    - by amateur
    Hi guys, I saw a couple of ways extending user information of users and decided to adopt the model inheritance method. for instance, I have : class Parent(User): contact_means = models.IntegerField() is_staff = False objects = userManager() Now it is done, I've downloaded django_registration to help me out with sending emails to new users. The thing is, instead of using registration forms to register new user, I want to to invoke the email sending/acitvation capability of django_registration. So my workflow is: 1. add new Parent object in admin page. 2. send email My problem is, the django-registration creates a new registration profile together with a new user in the user table. how do I tweak this such that I am able to add the user entry into the custom user table. I have tried to create a modelAdmin and alter the save_model method to launch the create_inactive_user from django_registration, however I do not how to save the user object generated from django_registration into my Parent table when I have using model inheritance and I do not have a Foreign key attribute in my parent model.

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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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  • Add data to Django form class using modelformset_factory

    - by dean
    I have a problem where I need to display a lot of forms for detail data for a hierarchical data set. I want to display some relational fields as labels for the forms and I'm struggling with a way to do this in a more robust way. Here is the code... class Category(models.Model): name = models.CharField(max_length=160) class Item(models.Model): category = models.ForeignKey('Category') name = models.CharField(max_length=160) weight = models.IntegerField(default=0) class Meta: ordering = ('category','weight','name') class BudgetValue(models.Model): value = models.IntegerField() plan = models.ForeignKey('Plan') item = models.ForeignKey('Item') I use the modelformset_factory to create a formset of budgetvalue forms for a particular plan. What I'd like is item name and category name for each BudgetValue. When I iterate through the forms each one will be labeled properly. class BudgetValueForm(forms.ModelForm): item = forms.ModelChoiceField(queryset=Item.objects.all(),widget=forms.HiddenInput()) plan = forms.ModelChoiceField(queryset=Plan.objects.all(),widget=forms.HiddenInput()) category = "" < assign dynamically on form creation > item = "" < assign dynamically on form creation > class Meta: model = BudgetValue fields = ('item','plan','value') What I started out with is just creating a dictionary of budgetvalue.item.category.name, budgetvalue.item.name, and the form for each budget value. This gets passed to the template and I render it as I intended. I'm assuming that the ordering of the forms in the formset and the querset used to genererate the formset keep the budgetvalues in the same order and the dictionary is created correctly. That is the budgetvalue.item.name is associated with the correct form. This scares me and I'm thinking there has to be a better way. Any help would be greatly appreciated.

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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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  • 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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  • 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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  • 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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  • 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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  • 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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  • httplib2 giving internal server error 500 with proxy

    - by NJTechie
    Following is the code and error it throws. It works fine without the proxy http = httplib2.Http() . Any pointers are highly appreciated! Usage : http = httplib2.Http(proxy_info = httplib2.ProxyInfo(socks.PROXY_TYPE_HTTP, '74.115.1.11', 80)) main_url = 'http://www.mywebsite.com' response, content = http.request(main_url, 'GET') Error : File "testproxy.py", line 17, in <module> response, content = http.request(main_url, 'GET') File "/home/kk/bin/pythonlib/httplib2/__init__.py", line 1129, in request (response, content) = self._request(conn, authority, uri, request_uri, method, body, headers, redirections, cachekey) File "/home/kk/bin/pythonlib/httplib2/__init__.py", line 901, in _request (response, content) = self._conn_request(conn, request_uri, method, body, headers) File "/home/kk/bin/pythonlib/httplib2/__init__.py", line 862, in _conn_request conn.request(method, request_uri, body, headers) File "/usr/lib/python2.5/httplib.py", line 866, in request self._send_request(method, url, body, headers) File "/usr/lib/python2.5/httplib.py", line 889, in _send_request self.endheaders() File "/usr/lib/python2.5/httplib.py", line 860, in endheaders self._send_output() File "/usr/lib/python2.5/httplib.py", line 732, in _send_output self.send(msg) File "/usr/lib/python2.5/httplib.py", line 699, in send self.connect() File "/home/kk/bin/pythonlib/httplib2/__init__.py", line 740, in connect self.sock.connect(sa) File "/home/kk/bin/pythonlib/socks.py", line 383, in connect self.__negotiatehttp(destpair[0],destpair[1]) File "/home/kk/bin/pythonlib/socks.py", line 349, in __negotiatehttp raise HTTPError((statuscode,statusline[2])) socks.HTTPError: (500, 'Internal Server Error')

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  • Use localeURL middleware with apache prefix

    - by Olivier R.
    Good morning everyone, I Got a question about localeURL usage. Everything works great for me with url like this : www.mysite.com/ If I type www.mysite.com/ in adress bar, it turns correctly in www.mysite.com/en/ for example. If I use the view change_locale, it's also all right (ie change www.mysite.com/en/ in www.mysite.com/fr/). But my application use apache as server, and use a prefix for the site, that gives url like this : www.mysite.com/prefix/ If I type www.mysite.com/prefix/ in the adress bar, the adress turns into www.mysite.com/en/ without prefix (so 404) I change code of view to manage our settings.SERVER_PREFIX value : def change_locale(request) : """ Redirect to a given url while changing the locale in the path The url and the locale code need to be specified in the request parameters. O. Rochaix; Taken from localeURL view, and tuned to manage : - SERVER_PREFIX from settings.py """ next = request.REQUEST.get('next', None) if not next: next = request.META.get('HTTP_REFERER', None) if not next: next = settings.SERVER_PREFIX + '/' next = urlsplit(next).path prefix = False if settings.SERVER_PREFIX!="" and next.startswith(settings.SERVER_PREFIX) : prefix = True next = "/" + next.lstrip(settings.SERVER_PREFIX) _, path = utils.strip_path (next) if request.method == 'POST': locale = request.POST.get('locale', None) if locale and check_for_language(locale): path = utils.locale_path(path, locale) if prefix : path = settings.SERVER_PREFIX + path response = http.HttpResponseRedirect(path) return response with this customized view, i'm able to correctly change language, but i'm not sure that's the right way of doing stuff. Is there any option on localeURL to manage prefix of apache ?

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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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  • 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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  • Extracting value in Beautifulsoup

    - by Seth
    I have the following code: f = open(path, 'r') html = f.read() # no parameters => reads to eof and returns string soup = BeautifulSoup(html) schoolname = soup.findAll(attrs={'id':'ctl00_ContentPlaceHolder1_SchoolProfileUserControl_SchoolHeaderLabel'}) print schoolname which gives: [<span id="ctl00_ContentPlaceHolder1_SchoolProfileUserControl_SchoolHeaderLabel">A B Paterson College, Arundel, QLD</span>] when I try and access the value (i.e. 'A B Paterson College, Arundel, QLD) by using schoolname['value'] I get the following error: print schoolname['value'] TypeError: list indices must be integers, not str What am I doing wrong to get that value?

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  • How to get HTTP status message in (py)curl?

    - by mykhal
    spending some time studying pycurl and libcurl documentation, i still can't find a (simple) way, how to get HTTP status message (reason-phrase) in pycurl. status code is easy: import pycurl import cStringIO curl = pycurl.Curl() buff = cStringIO.StringIO() curl.setopt(pycurl.URL, 'http://example.org') curl.setopt(pycurl.WRITEFUNCTION, buff.write) curl.perform() print "status code: %s" % curl.getinfo(pycurl.HTTP_CODE) # -> 200 # print "status message: %s" % ??? # -> "OK"

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  • How can I conditionally only log something if it's a certain Class?

    - by BryanWheelock
    Something like this: if self.class == "User": logging.debug("%s non_pks were found" % (str(len(non_pks))) ) In [2]: user = User.objects.get(pk=1) In [3]: user.class Out[3]: In [4]: if user.class == 'django.contrib.auth.models.User': print "yes" ...: In [5]: user.class == 'django.contrib.auth.models.User' Out[5]: False In [6]: user.class == 'User' Out[6]: False In [7]: user.class == "" Out[7]: False

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