Search Results

Search found 14486 results on 580 pages for 'python idle'.

Page 371/580 | < Previous Page | 367 368 369 370 371 372 373 374 375 376 377 378  | Next Page >

  • Find subset with K elements that are closest to eachother

    - by Nima
    Given an array of integers size N, how can you efficiently find a subset of size K with elements that are closest to each other? Let the closeness for a subset (x1,x2,x3,..xk) be defined as: 2 <= N <= 10^5 2 <= K <= N constraints: Array may contain duplicates and is not guaranteed to be sorted. My brute force solution is very slow for large N, and it doesn't check if there's more than 1 solution: N = input() K = input() assert 2 <= N <= 10**5 assert 2 <= K <= N a = [] for i in xrange(0, N): a.append(input()) a.sort() minimum = sys.maxint startindex = 0 for i in xrange(0,N-K+1): last = i + K tmp = 0 for j in xrange(i, last): for l in xrange(j+1, last): tmp += abs(a[j]-a[l]) if(tmp > minimum): break if(tmp < minimum): minimum = tmp startindex = i #end index = startindex + K? Examples: N = 7 K = 3 array = [10,100,300,200,1000,20,30] result = [10,20,30] N = 10 K = 4 array = [1,2,3,4,10,20,30,40,100,200] result = [1,2,3,4]

    Read the article

  • Is using os.path.abspath to validate an untrusted filename's location secure?

    - by mcmt
    I don't think I'm missing anything. Then again I'm kind of a newbie. def GET(self, filename): name = urllib.unquote(filename) full = path.abspath(path.join(STATIC_PATH, filename)) #Make sure request is not tricksy and tries to get out of #the directory, e.g. filename = "../.ssh/id_rsa". GET OUTTA HERE assert full[:len(STATIC_PATH)] == STATIC_PATH, "bad path" return open(full).read() Edit: I realize this will return the wrong HTTP error code if the file doesn't exist (at least under web.py). I will fix this.

    Read the article

  • 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.

    Read the article

  • Trouble with encoding and urllib

    - by Ockonal
    Hello, I'm loading web-page using urllib. Ther eis russian symbols, but page encoding is 'utf-8' 1 pageData = unicode(requestHandler.read()).decode('utf-8') UnicodeDecodeError: 'ascii' codec can't decode byte 0xd0 in position 262: ordinal not in range(128) 2 pageData = requestHandler.read() soupHandler = BeautifulSoup(pageData) print soupHandler.findAll(...) UnicodeEncodeError: 'ascii' codec can't encode characters in position 340-345: ordinal not in range(128)

    Read the article

  • Duplicate django query set?

    - by Piotr Czapla
    I have a simple django's query set like: qs = AModel.objects.exclude(state="F").order_by("order") I'd like to use it as follows: qs[0:3].update(state='F') expected = qs[3] # throws error here But last statement throws: "Cannot update a query once a slice has been taken." How can I duplicate the query set?

    Read the article

  • twisted reactor stops too early

    - by pygabriel
    I'm doing a batch script to connect to a tcp server and then exiting. My problem is that I can't stop the reactor, for example: cmd = raw_input("Command: ") # custom factory, the protocol just send a line reactor.connectTCP(HOST,PORT, CommandClientFactory(cmd) d = defer.Deferred() d.addCallback(lambda x: reactor.stop()) reactor.callWhenRunning(d.callback,None) reactor.run() In this code the reactor stops before that the tcp connection is done and the cmd is passed. How can I stop the reactor after that all the operation are finished?

    Read the article

  • Import boto from local library

    - by ensnare
    I'm trying to use boto as a downloaded library, rather than installing it globally on my machine. I'm able to import boto, but when I run boto.connect_dynamodb() I get an error: ImportError: No module named dynamodb.layer2 Here's my file structure: project/ project/ __init__.py libraries/ __init__.py flask/ boto/ views/ .... modules/ __init__.py db.py .... templates/ .... static/ .... runserver.py And the contents of the relevant files as follows: project/project/modules/db.py from project.libraries import boto conn = boto.connect_dynamodb( aws_access_key_id='<YOUR_AWS_KEY_ID>', aws_secret_access_key='<YOUR_AWS_SECRET_KEY>') What am I doing wrong? Thanks in advance.

    Read the article

  • How to create instances of related models in Django

    - by sevennineteen
    I'm working on a CMSy app for which I've implemented a set of models which allow for creation of custom Template instances, made up of a number of Fields and tied to a specific Customer. The end-goal is that one or more templates with a set of custom fields can be defined through the Admin interface and associated to a customer, so that customer can then create content objects in the format prescribed by the template. I seem to have gotten this hooked up such that I can create any number of Template objects, but I'm struggling with how to create instances - actual content objects - in those templates. For example, I can define a template "Basic Page" for customer "Acme" which has the fields "Title" and "Body", but I haven't figured out how to create Basic Page instances where these fields can be filled in. Here are my (somewhat elided) models... class Customer(models.Model): ... class Field(models.Model): ... class Template(models.Model): label = models.CharField(max_length=255) clients = models.ManyToManyField(Customer, blank=True) fields = models.ManyToManyField(Field, blank=True) class ContentObject(models.Model): label = models.CharField(max_length=255) template = models.ForeignKey(Template) author = models.ForeignKey(User) customer = models.ForeignKey(Customer) mod_date = models.DateTimeField('Modified Date', editable=False) def __unicode__(self): return '%s (%s)' % (self.label, self.template) def save(self): self.mod_date = datetime.datetime.now() super(ContentObject, self).save() Thanks in advance for any advice!

    Read the article

  • How to make scipy.interpolate give a an extrapolated result beyond the input range?

    - by Salim Fadhley
    I'm trying to port a program which uses a hand-rolled interpolator (developed by a mathematitian colleage) over to use the interpolators provided by scipy. I'd like to use or wrap the scipy interpolator so that it has as close as possible behavior to the old interpolator. A key difference between the two functions is that in our original interpolator - if the input value is above or below the input range, our original interpolator will extrapolate the result. If you try this with the scipy interpolator it raises a ValueError. Consider this program as an example: import numpy as np from scipy import interpolate x = np.arange(0,10) y = np.exp(-x/3.0) f = interpolate.interp1d(x, y) print f(9) print f(11) # Causes ValueError, because it's greater than max(x) Is there a sensible way to make it so that instead of crashing, the final line will simply do a linear extrapolate, continuing the gradients defined by the first and last two pouints to infinity. Note, that in the real software I'm not actually using the exp function - that's here for illustration only!

    Read the article

  • Condition checking vs. Exception handling

    - by Aidas Bendoraitis
    When is exception handling more preferable than condition checking? There are many situations where I can choose using one or the other. For example, this is a summing function which uses a custom exception: # module mylibrary class WrongSummand(Exception): pass def sum_(a, b): """ returns the sum of two summands of the same type """ if type(a) != type(b): raise WrongSummand("given arguments are not of the same type") return a + b # module application using mylibrary from mylibrary import sum_, WrongSummand try: print sum_("A", 5) except WrongSummand: print "wrong arguments" And this is the same function, which avoids using exceptions # module mylibrary def sum_(a, b): """ returns the sum of two summands if they are both of the same type """ if type(a) == type(b): return a + b # module application using mylibrary from mylibrary import sum_ c = sum_("A", 5) if c is not None: print c else: print "wrong arguments" I think that using conditions is always more readable and manageable. Or am I wrong? What are the proper cases for defining APIs which raise exceptions and why?

    Read the article

  • How do I store multiple copies of the same field in Django?

    - by Alistair
    I'm storing OLAC metadata which describes linguistic resources. Many of the elements of the metadata are repeatable -- for example, a resource can have two languages, three authors and four dates associated with it. Is there any way of storing this in one model? It seems like overkill to define a model for each repeatable metadata element -- especially since the models will only have one field: it's value.

    Read the article

  • How to add a context processor from a Django app

    - by Edan Maor
    Say I'm writing a Django app, and all the templates in the app require a certain variable. The "classic" way to deal with this, afaik, is to write a context processor and add it to TEMPLATE_CONTEXT_PROCESSORS in the settings.py. My question is, is this the right way to do it, considering that apps are supposed to be "independent" from the actual project using them? In other words, when deploying that app to a new project, is there any way to avoid the project having to explicitly mess around with its settings?

    Read the article

  • Execute function without sending 'self' to it

    - by Sergey
    Is that possible to define a function without referencing to self this way? def myfunc(var_a,var_b) But so that it could also get sender data, like if I defined it like this: def myfunc(self, var_a,var_b) That self is always the same so it looks a little redundant here always to run a function this way: myfunc(self,'data_a','data_b'). Then I would like to get its data in the function like this sender.fields. UPDATE: Here is some code to understand better what I mean. The class below is used to show a page based on Jinja2 templates engine for users to sign up. class SignupHandler(webapp.RequestHandler): def get(self, *args, **kwargs): utils.render_template(self, 'signup.html') And this code below is a render_template that I created as wrapper to Jinja2 functions to use it more conveniently in my project: def render_template(response, template_name, vars=dict(), is_string=False): template_dirs = [os.path.join(root(), 'templates')] logging.info(template_dirs[0]) env = Environment(loader=FileSystemLoader(template_dirs)) try: template = env.get_template(template_name) except TemplateNotFound: raise TemplateNotFound(template_name) content = template.render(vars) if is_string: return content else: response.response.out.write(content) As I use this function render_template very often in my project and usually the same way, just with different template files, I wondered if there was a way to get rid of having to call it like I do it now, with self as the first argument but still having access to that object.

    Read the article

  • How can I draw a log-normalized imshow plot with a colorbar representing the raw data in matplotlib

    - by Adam Fraser
    I'm using matplotlib to plot log-normalized images but I would like the original raw image data to be represented in the colorbar rather than the [0-1] interval. I get the feeling there's a more matplotlib'y way of doing this by using some sort of normalization object and not transforming the data beforehand... in any case, there could be negative values in the raw image. import matplotlib.pyplot as plt import numpy as np def log_transform(im): '''returns log(image) scaled to the interval [0,1]''' try: (min, max) = (im[im > 0].min(), im.max()) if (max > min) and (max > 0): return (np.log(im.clip(min, max)) - np.log(min)) / (np.log(max) - np.log(min)) except: pass return im a = np.ones((100,100)) for i in range(100): a[i] = i f = plt.figure() ax = f.add_subplot(111) res = ax.imshow(log_transform(a)) # the colorbar drawn shows [0-1], but I want to see [0-99] cb = f.colorbar(res) I've tried using cb.set_array, but that didn't appear to do anything, and cb.set_clim, but that rescales the colors completely. Thanks in advance for any help :)

    Read the article

  • Serve external template in Django

    - by AlexeyMK
    Hey, I want to do something like return render_to_response("http://docs.google.com/View?id=bla", args) and serve an external page with django arguments. Django doesn't like this (it looks for templates in very particular places). What's the easiest way make this work? Right now I'm thinking to use urllib to save the page to somewhere locally on my server and then serve with the templates pointing to there. Note: I'm not looking for anything particularly scalable here, I realize my proposal above is a little dirty.

    Read the article

  • Scrapy Not Returning Additonal Info from Scraped Link in Item via Request Callback

    - by zoonosis
    Basically the code below scrapes the first 5 items of a table. One of the fields is another href and clicking on that href provides more info which I want to collect and add to the original item. So parse is supposed to pass the semi populated item to parse_next_page which then scrapes the next bit and should return the completed item back to parse Running the code below only returns the info collected in parse If I change the return items to return request I get a completed item with all 3 "things" but I only get 1 of the rows, not all 5. Im sure its something simple, I just can't see it. class ThingSpider(BaseSpider): name = "thing" allowed_domains = ["somepage.com"] start_urls = [ "http://www.somepage.com" ] def parse(self, response): hxs = HtmlXPathSelector(response) items = [] for x in range (1,6): item = ScrapyItem() str_selector = '//tr[@name="row{0}"]'.format(x) item['thing1'] = hxs.select(str_selector")]/a/text()').extract() item['thing2'] = hxs.select(str_selector")]/a/@href').extract() print 'hello' request = Request("www.nextpage.com", callback=self.parse_next_page,meta={'item':item}) print 'hello2' request.meta['item'] = item items.append(item) return items def parse_next_page(self, response): print 'stuff' hxs = HtmlXPathSelector(response) item = response.meta['item'] item['thing3'] = hxs.select('//div/ul/li[1]/span[2]/text()').extract() return item

    Read the article

  • 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.

    Read the article

  • mod_wsgi daemon mode vs threaded fastcgi

    - by t0ster
    Can someone explain the difference between apache mod_wsgi in daemon mode and django fastcgi in threaded mode. They both use threads for concurrency I think. Supposing that I'm using nginx as front end to apache mod_wsgi. UPDATE: I'm comparing django built in fastcgi(./manage.py method=threaded maxchildren=15) and mod_wsgi in 'daemon' mode(WSGIDaemonProcess example threads=15). They both use threads and acquire GIL, am I right?

    Read the article

< Previous Page | 367 368 369 370 371 372 373 374 375 376 377 378  | Next Page >