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  • Clean Method for a ModelForm in a ModelFormSet made by modelformset_factory

    - by Salyangoz
    I was wondering if my approach is right or not. Assuming the Restaurant model has only a name. forms.py class BaseRestaurantOpinionForm(forms.ModelForm): opinion = forms.ChoiceField(choices=(('yes', 'yes'), ('no', 'no'), ('meh', 'meh')), required=False, )) class Meta: model = Restaurant fields = ['opinion'] views.py class RestaurantVoteListView(ListView): queryset = Restaurant.objects.all() template_name = "restaurants/list.html" def dispatch(self, request, *args, **kwargs): if request.POST: queryset = self.request.POST.dict() #clean here return HttpResponse(json.dumps(queryset), content_type="application/json") def get_context_data(self, **kwargs): context = super(EligibleRestaurantsListView, self).get_context_data(**kwargs) RestaurantFormSet = modelformset_factory( Restaurant,form=BaseRestaurantOpinionForm ) extra_context = { 'eligible_restaurants' : self.get_eligible_restaurants(), 'forms' : RestaurantFormSet(), } context.update(extra_context) return context Basically I'll be getting 3 voting buttons for each restaurant and then I want to read the votes. I was wondering from where/which clean function do I need to call to get something like: { ('3' : 'yes'), ('2' : 'no') } #{ 'restaurant_id' : 'vote' } This is my second/third question so tell me if I'm being unclear. Thanks.

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  • Matching strings

    - by Joy
    Write the function subStringMatchExact. This function takes two arguments: a target string, and a key string. It should return a tuple of the starting points of matches of the key string in the target string, when indexing starts at 0. Complete the definition for def subStringMatchExact(target,key): For example, subStringMatchExact("atgacatgcacaagtatgcat","atgc") would return the tuple (5, 15).

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  • has any tools easy to download or uploaed data from gae ..

    - by zjm1126
    i find this: http://aralbalkan.com/1784 but it is : Gaebar is an easy-to-use, standalone Django application that you can plug in to your existing Google App Engine Django or app-engine-patch-based Django applications on Google App Engine to give them datastore backup and restore functionality. my app is not based on django,so did you know any tools esay to do this . thanks

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  • Is django orm & templates thread safe?

    - by Piotr Czapla
    I'm using django orm and templates to create a background service that is ran as management command. Do you know if django is thread safe? I'd like to use threads to speed up processing. The processing is blocked by I/O not CPU so I don't care about performance hit caused by GIL.

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  • Setting up relations/mappings for a SQLAlchemy many-to-many database

    - by Brent Ramerth
    I'm new to SQLAlchemy and relational databases, and I'm trying to set up a model for an annotated lexicon. I want to support an arbitrary number of key-value annotations for the words which can be added or removed at runtime. Since there will be a lot of repetition in the names of the keys, I don't want to use this solution directly, although the code is similar. My design has word objects and property objects. The words and properties are stored in separate tables with a property_values table that links the two. Here's the code: from sqlalchemy import Column, Integer, String, Table, create_engine from sqlalchemy import MetaData, ForeignKey from sqlalchemy.orm import relation, mapper, sessionmaker from sqlalchemy.ext.declarative import declarative_base engine = create_engine('sqlite:///test.db', echo=True) meta = MetaData(bind=engine) property_values = Table('property_values', meta, Column('word_id', Integer, ForeignKey('words.id')), Column('property_id', Integer, ForeignKey('properties.id')), Column('value', String(20)) ) words = Table('words', meta, Column('id', Integer, primary_key=True), Column('name', String(20)), Column('freq', Integer) ) properties = Table('properties', meta, Column('id', Integer, primary_key=True), Column('name', String(20), nullable=False, unique=True) ) meta.create_all() class Word(object): def __init__(self, name, freq=1): self.name = name self.freq = freq class Property(object): def __init__(self, name): self.name = name mapper(Property, properties) Now I'd like to be able to do the following: Session = sessionmaker(bind=engine) s = Session() word = Word('foo', 42) word['bar'] = 'yes' # or word.bar = 'yes' ? s.add(word) s.commit() Ideally this should add 1|foo|42 to the words table, add 1|bar to the properties table, and add 1|1|yes to the property_values table. However, I don't have the right mappings and relations in place to make this happen. I get the sense from reading the documentation at http://www.sqlalchemy.org/docs/05/mappers.html#association-pattern that I want to use an association proxy or something of that sort here, but the syntax is unclear to me. I experimented with this: mapper(Word, words, properties={ 'properties': relation(Property, secondary=property_values) }) but this mapper only fills in the foreign key values, and I need to fill in the other value as well. Any assistance would be greatly appreciated.

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  • How to convert string "0671" or "0x45" into integer form with 0 and 0x in the beginning.

    - by Harshit Sharma
    I wanted to make my own encryption algorithm and decryption algorithm , encryption algorithm works fine and converts ascii value of the characters into alternate hexadecimal and octal representations. But when I tried decryption, problem occured as it return int('0671') = 671, as 0671 is string type in the following code. Is there a method to convert "ox56" into integer form?????? NOTE: Following string is alternate octal and hexa of ascii value of char. ///////////////DECRYPTION/////// l="01630x7401620x6901560x67" f=len(l) k=0 d=0 x=[] for i in range(0,f,4): g=l[i:i+4] print g k=k+1 if(k%2==0): p=g print p else: p=int(g) print p

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  • Right way to return proxy model instance from a base model instance in Django ?

    - by sotangochips
    Say I have models: class Animal(models.Model): type = models.CharField(max_length=255) class Dog(Animal): def make_sound(self): print "Woof!" class Meta: proxy = True class Cat(Animal): def make_sound(self): print "Meow!" class Meta: proxy = True Let's say I want to do: animals = Animal.objects.all() for animal in animals: animal.make_sound() I want to get back a series of Woofs and Meows. Clearly, I could just define a make_sound in the original model that forks based on animal_type, but then every time I add a new animal type (imagine they're in different apps), I'd have to go in and edit that make_sound function. I'd rather just define proxy models and have them define the behavior themselves. From what I can tell, there's no way of returning mixed Cat or Dog instances, but I figured maybe I could define a "get_proxy_model" method on the main class that returns a cat or a dog model. Surely you could do this, and pass something like the primary key and then just do Cat.objects.get(pk = passed_in_primary_key). But that'd mean doing an extra query for data you already have which seems redundant. Is there any way to turn an animal into a cat or a dog instance in an efficient way? What's the right way to do what I want to achieve?

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  • sqlite3 'database is locked' won't go away with retries

    - by Azarias
    I have a sqlite3 database that is accessed by a few threads (3-4). I am aware of the general limitations of sqlite3 with regards to concurrency as stated http://www.sqlite.org/faq.html#q6 , but I am convinced that is not the problem. All of the threads both read and write from this database. Whenever I do a write, I have the following construct: try: Cursor.execute(q, params) Connection.commit() except sqlite3.IntegrityError: Notify except sqlite3.OperationalError: print sys.exc_info() print("DATABASE LOCKED; sleeping for 3 seconds and trying again") time.sleep(3) Retry On some runs, I won't even hit this block, but when I do, it never comes out of it (keeps retrying, but I keep getting the 'database is locked' error from exc_info. If I understand the reader/writer lock usage correctly, some amount of waiting should help with the contention. What this sounds like is deadlock, but I do not use any transactions in my code, and every SELECT or INSERT is simply a one off. Some threads, however, keep the same connection when they do their operation (which includes a mix of SELECTS and INSERTS and other modifiers). I would appericiate it if you could shade a light on this, and also ways around fixing it (besides using a different database engine.)

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  • Creating a custom widget using django for use on external sites

    - by ajt
    I have a new site that I am putting together and part of it has statistics for the site's users. I would like to create a widget that others can use on another website by invoking javascript that reads data from my server and shows that statistics for a given user, but I am having a hard time finding specific tutorials that covers this in django. I have seen the link at Alex Maradon's site [0], but it looks to me like that is passing html back to the widget and I am having a hard time figuring out how to do this using something like xml. Are there any django apps for doing this or does anyone know of good how-tos? [0] http://alexmarandon.com/articles/web_widget_jquery/

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  • How to separate comma separeted data from csv file?

    - by Rahul
    I have opened a csv file and I want to sort each string which is comma separeted and are in same line: ex:: file : name,sal,dept tom,10000,it o/p :: each string in string variable I have a file which is already open, so I can not use "open" API, I have to use "csv.reader" which have to read one line at a time.

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  • Rearranging a sequence

    - by sarah
    I'm have trouble rearranging sequences so the amount of letters in the given original sequence are the same in the random generated sequences. For example: If i have a string 'AAAC' I need that string rearranged randomly so the amount of A's and C's are the same.

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  • methods of metaclasses on class instances.

    - by Stefano Borini
    I was wondering what happens to methods declared on a metaclass. I expected that if you declare a method on a metaclass, it will end up being a classmethod, however, the behavior is different. Example >>> class A(object): ... @classmethod ... def foo(cls): ... print "foo" ... >>> a=A() >>> a.foo() foo >>> A.foo() foo However, if I try to define a metaclass and give it a method foo, it seems to work the same for the class, not for the instance. >>> class Meta(type): ... def foo(self): ... print "foo" ... >>> class A(object): ... __metaclass__=Meta ... def __init__(self): ... print "hello" ... >>> >>> a=A() hello >>> A.foo() foo >>> a.foo() Traceback (most recent call last): File "<stdin>", line 1, in <module> AttributeError: 'A' object has no attribute 'foo' What's going on here exactly ? edit: bumping the question

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  • Extend argparse to write set names in the help text for optional argument choices and define those sets once at the end

    - by Kent
    Example of the problem If I have a list of valid option strings which is shared between several arguments, the list is written in multiple places in the help string. Making it harder to read: def main(): elements = ['a', 'b', 'c', 'd', 'e', 'f'] parser = argparse.ArgumentParser() parser.add_argument( '-i', nargs='*', choices=elements, default=elements, help='Space separated list of case sensitive element names.') parser.add_argument( '-e', nargs='*', choices=elements, default=[], help='Space separated list of case sensitive element names to ' 'exclude from processing') parser.parse_args() When running the above function with the command line argument --help it shows: usage: arguments.py [-h] [-i [{a,b,c,d,e,f} [{a,b,c,d,e,f} ...]]] [-e [{a,b,c,d,e,f} [{a,b,c,d,e,f} ...]]] optional arguments: -h, --help show this help message and exit -i [{a,b,c,d,e,f} [{a,b,c,d,e,f} ...]] Space separated list of case sensitive element names. -e [{a,b,c,d,e,f} [{a,b,c,d,e,f} ...]] Space separated list of case sensitive element names to exclude from processing What would be nice It would be nice if one could define an option list name, and in the help output write the option list name in multiple places and define it last of all. In theory it would work like this: def main_optionlist(): elements = ['a', 'b', 'c', 'd', 'e', 'f'] # Two instances of OptionList are equal if and only if they # have the same name (ALFA in this case) ol = OptionList('ALFA', elements) parser = argparse.ArgumentParser() parser.add_argument( '-i', nargs='*', choices=ol, default=ol, help='Space separated list of case sensitive element names.') parser.add_argument( '-e', nargs='*', choices=ol, default=[], help='Space separated list of case sensitive element names to ' 'exclude from processing') parser.parse_args() And when running the above function with the command line argument --help it would show something similar to: usage: arguments.py [-h] [-i [ALFA [ALFA ...]]] [-e [ALFA [ALFA ...]]] optional arguments: -h, --help show this help message and exit -i [ALFA [ALFA ...]] Space separated list of case sensitive element names. -e [ALFA [ALFA ...]] Space separated list of case sensitive element names to exclude from processing sets in optional arguments: ALFA {a,b,c,d,e,f} Question I need to: Replace the {'l', 'i', 's', 't', 's'} shown with the option name, in the optional arguments. At the end of the help text show a section explaining which elements each option name consists of. So I ask: Is this possible using argparse? Which classes would I have to inherit from and which methods would I need to override? I have tried looking at the source for argparse, but as this modification feels pretty advanced I don´t know how to get going.

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  • Non standard interaction among two tables to avoid very large merge

    - by riko
    Suppose I have two tables A and B. Table A has a multi-level index (a, b) and one column (ts). b determines univocally ts. A = pd.DataFrame( [('a', 'x', 4), ('a', 'y', 6), ('a', 'z', 5), ('b', 'x', 4), ('b', 'z', 5), ('c', 'y', 6)], columns=['a', 'b', 'ts']).set_index(['a', 'b']) AA = A.reset_index() Table B is another one-column (ts) table with non-unique index (a). The ts's are sorted "inside" each group, i.e., B.ix[x] is sorted for each x. Moreover, there is always a value in B.ix[x] that is greater than or equal to the values in A. B = pd.DataFrame( dict(a=list('aaaaabbcccccc'), ts=[1, 2, 4, 5, 7, 7, 8, 1, 2, 4, 5, 8, 9])).set_index('a') The semantics in this is that B contains observations of occurrences of an event of type indicated by the index. I would like to find from B the timestamp of the first occurrence of each event type after the timestamp specified in A for each value of b. In other words, I would like to get a table with the same shape of A, that instead of ts contains the "minimum value occurring after ts" as specified by table B. So, my goal would be: C: ('a', 'x') 4 ('a', 'y') 7 ('a', 'z') 5 ('b', 'x') 7 ('b', 'z') 7 ('c', 'y') 8 I have some working code, but is terribly slow. C = AA.apply(lambda row: ( row[0], row[1], B.ix[row[0]].irow(np.searchsorted(B.ts[row[0]], row[2]))), axis=1).set_index(['a', 'b']) Profiling shows the culprit is obviously B.ix[row[0]].irow(np.searchsorted(B.ts[row[0]], row[2]))). However, standard solutions using merge/join would take too much RAM in the long run. Consider that now I have 1000 a's, assume constant the average number of b's per a (probably 100-200), and consider that the number of observations per a is probably in the order of 300. In production I will have 1000 more a's. 1,000,000 x 200 x 300 = 60,000,000,000 rows may be a bit too much to keep in RAM, especially considering that the data I need is perfectly described by a C like the one I discussed above. How would I improve the performance?

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  • In plain English, what are Django generic views?

    - by allyourcode
    The first two paragraphs of this page explain that generic views are supposed to make my life easier, less monotonous, and make me more attractive to women (I made up that last one): http://docs.djangoproject.com/en/dev/topics/generic-views/#topics-generic-views I'm all for improving my life, but what do generic views actually do? It seems like lots of buzzwords are being thrown around, which confuse more than they explain. Are generic views similar to scaffolding in Ruby on Rails? The last bullet point in the intro seems to indicate this. Is that an accurate statement?

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  • Efficiently generate a 16-character, alphanumeric string

    - by ensnare
    I'm looking for a very quick way to generate an alphanumeric unique id for a primary key in a table. Would something like this work? def genKey(): hash = hashlib.md5(RANDOM_NUMBER).digest().encode("base64") alnum_hash = re.sub(r'[^a-zA-Z0-9]', "", hash) return alnum_hash[:16] What would be a good way to generate random numbers? If I base it on microtime, I have to account for the possibility of several calls of genKey() at the same time from different instances. Or is there a better way to do all this? Thanks.

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  • pyramid traversal resource url no attribute __name__

    - by Santana
    So I have: resources.py: def _add(obj, name, parent): obj.__name__ = name obj.__parent__ = parent return obj class Root(object): __parent__ = __name__ = None def __init__(self, request): super(Root, self).__init__() self.request = request self.collection = request.db.post def __getitem__(self, key): if u'profile' in key: return Profile(self.request) class Profile(dict): def __init__(self, request): super(Profile, self).__init__() self.__name__ = u'profile' self.__parent__ = Root self.collection = request.db.posts def __getitem__(self, name): post = Dummy(self.collection.find_one(dict(username=name))) return _add(post, name, self) and I'm using MongoDB and pyramid_mongodb views.py: @view_config(context = Profile, renderer = 'templates/mytemplate.pt') def test_view(request): return {} and in mytemplate.pt: <p tal:repeat='item request.context'> ${item} </p> I can echo what's in the database (I'm using mongodb), but when I provided a URL for each item using resource_url() <p tal:repeat='item request.context'> <a href='${request.resource_url(item)}'>${item}</a> </p> I got an error: 'dict' object has no attribute '__name__', can someone help me?

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  • Iterate with binary structure over numpy array to get cell sums

    - by Curlew
    In the package scipy there is the function to define a binary structure (such as a taxicab (2,1) or a chessboard (2,2)). import numpy from scipy import ndimage a = numpy.zeros((6,6), dtype=numpy.int) a[1:5, 1:5] = 1;a[3,3] = 0 ; a[2,2] = 2 s = ndimage.generate_binary_structure(2,2) # Binary structure #.... Calculate Sum of result_array = numpy.zeros_like(a) What i want is to iterate over all cells of this array with the given structure s. Then i want to append a function to the current cell value indexed in a empty array (example function sum), which uses the values of all cells in the binary structure. For example: array([[0, 0, 0, 0, 0, 0], [0, 1, 1, 1, 1, 0], [0, 1, 2, 1, 1, 0], [0, 1, 1, 0, 1, 0], [0, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0]]) # The array a. The value in cell 1,2 is currently one. Given the structure s and an example function such as sum the value in the resulting array (result_array) becomes 7 (or 6 if the current cell value is excluded). Someone got an idea?

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  • Making all variables accessible to namespace

    - by Gökhan Sever
    Hello, Say I have a simple function: def myfunc(): a = 4.2 b = 5.5 ... many similar variables ... I use this function one time only and I am wondering what is the easiest way to make all the variables inside the function accessible to my main name-space. Do I have to declare global for each item? or any other suggested methods? Thanks.

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