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  • Any way to set or overwrite the __line__ and __file__ metadata?

    - by charles.merriam
    I'm writing some code that needs to change function signatures. Right now, I'm using Simionato's FunctionMaker class, which uses the (hacky) inspect module, and does a compile. Unfortunately, this still loses the line and file metadata. Does anyone know: If it is possible to overwrite these values in some odd way? If hacking up a class with a complex getattribute() to intercept the values and also try to make the class looks like a function is any more possible than a moose with a flying nun hat? Is there an alternative to the (hacky) inspect module? PEP 362 is dead dead dead? I know decorators and cPickle users fight with this. What other situations is the read only metadata in people's way? I appreciate any insights. Thank you.

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  • numpy array mapping and take average

    - by user566653
    Dear all, I have three array value = np.array ([1, 3, 3, 5, 5, 7, 3]) index = np.array ([1, 1, 3, 3, 6, 6, 6]) data = np.array ([1, 2, 3, 4, 5, 6]) and want to take average for item of "value" by array "index", and assign a new array with value of "data", such as [2, nan, 4, nan, nan, 5] first value is the average of 1st and 2nd of "value" second value is nan because there is not any key in "index" third value is the average of 3rd and 4th of "value" ... Thanks for your help!!! Regards, Roy

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  • Transferring binary file from web server to client

    - by Yan Cheng CHEOK
    Usually, when I want to transfer a web server text file to client, here is what I did import cgi print "Content-Type: text/plain" print "Content-Disposition: attachment; filename=TEST.txt" print filename = "C:\\TEST.TXT" f = open(filename, 'r') for line in f: print line Works very fine for ANSI file. However, say, I have a binary file a.exe (This file is in web server secret path, and user shall not have direct access to that directory path). I wish to use the similar method to transfer. How I can do so? What content-type I should use? Using print seems to have corrupted content received at client side. What is the correct method?

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  • UnicodeDecodeError when redirecting to file

    - by zedoo
    Hi, I run this snippet twice, in the ubuntu terminal, (encoding set to utf-8) once with ./test.py and then with ./test.py >out.txt: uni = u"\u001A\u0BC3\u1451\U0001D10C" print uni Without redirection it prints garbage. With redirection I get a UnicodeDecodeError. Can someone explain why I get the error only in the second case, or even better give a detailed explanation of what's going on behind the curtain in both cases?

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  • Exposing a "dumbed-down", read-only instance of a Model in GAE

    - by Blixt
    Does anyone know a clever way, in Google App Engine, to return a wrapped Model instance that only exposes a few of the original properties, and does not allow saving the instance back to the datastore? I'm not looking for ways of actually enforcing these rules, obviously it'll still be possible to change the instance by digging through its __dict__ etc. I just want a way to avoid accidental exposure/changing of data. My initial thought was to do this (I want to do this for a public version of a User model): class ReadOnlyUser(db.Model): display_name = db.StringProperty() @classmethod def kind(cls): return 'User' def put(self): raise SomeError() Unfortunately, GAE maps the kind to a class early on, so if I do ReadOnlyUser.get_by_id(1) I will actually get a User instance back, not a ReadOnlyUser instance.

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  • Saving a Django form with a Many2Many field with through table

    - by PhilGo20
    So I have this model with multiple Many2Many relationship. 2 of those (EventCategorizing and EventLocation are through tables/intermediary models) class Event(models.Model): """ Event information for Way-finding and Navigator application""" categories = models.ManyToManyField('EventCategorizing', null=True, blank=True, help_text="categories associated with the location") #categories associated with the location images = models.ManyToManyField(KMSImageP, null=True, blank=True) #images related to the event creator = models.ForeignKey(User, verbose_name=_('creator'), related_name="%(class)s_created") locations = models.ManyToManyField('EventLocation', null=True, blank=True) In my view, I first need to save the creator as the request user, so I use the commit=False parameter to get the form values. if event_form.is_valid(): event = event_form.save(commit=False) #we save the request user as the creator event.creator = request.user event.save() event = event_form.save_m2m() event.save() I get the following error: *** TypeError: 'EventCategorizing' instance expected I can manually add the M2M relationship to my "event" instance, but I am sure there is a simpler way. Am I missing on something ?

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  • "Function object is unsubscriptable" in basic integer to string mapping function

    - by IanWhalen
    I'm trying to write a function to return the word string of any number less than 1000. Everytime I run my code at the interactive prompt it appears to work without issue but when I try to import wordify and run it with a test number higher than 20 it fails as "TypeError: 'function' object is unsubscriptable". Based on the error message, it seems the issue is when it tries to index numString (for example trying to extract the number 4 out of the test case of n = 24) and the compiler thinks numString is a function instead of a string. since the first line of the function is me defining numString as a string of the variable n, I'm not really sure why that is. Any help in getting around this error, or even just help in explaining why I'm seeing it, would be awesome. def wordify(n): # Convert n to a string to parse out ones, tens and hundreds later. numString = str(n) # N less than 20 is hard-coded. if n < 21: return numToWordMap(n) # N between 21 and 99 parses ones and tens then concatenates. elif n < 100: onesNum = numString[-1] ones = numToWordMap(int(onesNum)) tensNum = numString[-2] tens = numToWordMap(int(tensNum)*10) return tens+ones else: # TODO pass def numToWordMap(num): mapping = { 0:"", 1:"one", 2:"two", 3:"three", 4:"four", 5:"five", 6:"six", 7:"seven", 8:"eight", 9:"nine", 10:"ten", 11:"eleven", 12:"twelve", 13:"thirteen", 14:"fourteen", 15:"fifteen", 16:"sixteen", 17:"seventeen", 18:"eighteen", 19:"nineteen", 20:"twenty", 30:"thirty", 40:"fourty", 50:"fifty", 60:"sixty", 70:"seventy", 80:"eighty", 90:"ninety", 100:"onehundred", 200:"twohundred", 300:"threehundred", 400:"fourhundred", 500:"fivehundred", 600:"sixhundred", 700:"sevenhundred", 800:"eighthundred", 900:"ninehundred", } return mapping[num] if __name__ == '__main__': pass

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  • Is there a performance gain from defining routes in app.yaml versus one large mapping in a WSGIAppli

    - by jgeewax
    Scenario 1 This involves using one "gateway" route in app.yaml and then choosing the RequestHandler in the WSGIApplication. app.yaml - url: /.* script: main.py main.py from google.appengine.ext import webapp class Page1(webapp.RequestHandler): def get(self): self.response.out.write("Page 1") class Page2(webapp.RequestHandler): def get(self): self.response.out.write("Page 2") application = webapp.WSGIApplication([ ('/page1/', Page1), ('/page2/', Page2), ], debug=True) def main(): wsgiref.handlers.CGIHandler().run(application) if __name__ == '__main__': main() Scenario 2: This involves defining two routes in app.yaml and then two separate scripts for each (page1.py and page2.py). app.yaml - url: /page1/ script: page1.py - url: /page2/ script: page2.py page1.py from google.appengine.ext import webapp class Page1(webapp.RequestHandler): def get(self): self.response.out.write("Page 1") application = webapp.WSGIApplication([ ('/page1/', Page1), ], debug=True) def main(): wsgiref.handlers.CGIHandler().run(application) if __name__ == '__main__': main() page2.py from google.appengine.ext import webapp class Page2(webapp.RequestHandler): def get(self): self.response.out.write("Page 2") application = webapp.WSGIApplication([ ('/page2/', Page2), ], debug=True) def main(): wsgiref.handlers.CGIHandler().run(application) if __name__ == '__main__': main() Question What are the benefits and drawbacks of each pattern? Is one much faster than the other?

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  • How to create and restore a backup from SqlAlchemy?

    - by swilliams
    I'm writing a Pylons app, and am trying to create a simple backup system where every table is serialized and tarred up into a single file for an administrator to download, and use to restore the app should something bad happen. I can serialize my table data just fine using the SqlAlchemy serializer, and I can deserialize it fine as well, but I can't figure out how to commit those changes back to the database. In order to serialize my data I am doing this: from myproject.model.meta import Session from sqlalchemy.ext.serializer import loads, dumps q = Session.query(MyTable) serialized_data = dumps(q.all()) In order to test things out, I go ahead and truncation MyTable, and then attempt to restore using serialized_data: from myproject.model import meta restore_q = loads(serialized_data, meta.metadata, Session) This doesn't seem to do anything... I've tried calling a Session.commit after the fact, individually walking through all the objects in restore_q and adding them, but nothing seems to work. What am I missing? Or is there a better way to do what I'm aiming for? I don't want to shell out and directly touch the database, since SqlAlchemy supports different database engines.

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  • Filter objects within two seconds of one another using SQLAlchemy

    - by Arrieta
    Hello: I have two tables with a column 'date'. One holds (name, date) and the other holds (date, p1, p2). Given a name, I want to use the date in table 1 to query p1 and p2 from table two; the match should happen if date in table one is within two seconds of date in table two. How can you accomplish this using SQLAlchemy? I've tried (unsuccessfully) to use the between operator and with a clause like: td = datetime.timedelta(seconds=2) q = session.query(table1, table2).filter(table1.name=='my_name').\ filter(between(table1.date, table2.date - td, table2.date + td)) Any thoughts?

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  • A faster alternative to Pandas `isin` function

    - by user3576212
    I have a very large data frame df that looks like: ID Value1 Value2 1345 3.2 332 1355 2.2 32 2346 1.0 11 3456 8.9 322 And I have a list that contains a subset of IDs ID_list. I need to have a subset of df for the ID contained in ID_list. Currently, I am using df_sub=df[df.ID.isin(ID_list)] to do it. But it takes a lot time. IDs contained in ID_list doesn't have any pattern, so it's not within certain range. (And I need to apply the same operation to many similar dataframes. I was wondering if there is any faster way to do this. Will it help a lot if make ID as the index? Thanks!

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  • Load image from string

    - by zaf
    Given a string containing jpeg image data, is it possible to load this directly in pygame? I've tried using StringIO but failed and I don't completely understand the 'file-like' object concept. Currently, as a workaround, I'm saving to disk and then loading an image the standard way: # imagestring contains a jpeg f=open('test.jpg','wb') f.write(imagestring) f.close() image=pygame.image.load('test.jpg') Any suggestions on improving this so that we avoid creating a temp file?

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  • Django context processor gets AnonymousUser

    - by myfreeweb
    instead of User. def myview(request): return render_to_response('tmpl.html', {'user': User.objects.get(id=1}) works fine and passes User to template. But def myview(request): return render_to_response('tmpl.html', {}, context_instance=RequestContext(request)) with a context processor def user(request): from django.contrib.auth.models import User return {'user': User.objects.get(id=1)} passes AnonymousUser, so I can't get the variables I need :( What's wrong?

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  • How do I use multiple settings file in Django with multiple sites on one server?

    - by William Bing Hua
    I have an ec2 instance running Ubuntu 14.04 and I want to host two sites from it. On my first site I have two settings file, production_settings.py and settings.py (for local development). I import the local settings into the production settings and override any settings with the production settings file. Since my production settings file is not the default settings.py name, I have to create an environment variable DJANGO_SETTINGS_MODULE='site1.production_settings' However because of this whenever I try to start my second site it says No module named site1.production_settings I am assuming that this is due to me setting the environment variable. Another problem is that I won't be able to use different settings file for different sites. How do I start use two different settings file for two different websites?

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  • add extra data to response object to render in template

    - by mp0int
    I ned to write a code sniplet that enables to disable connection to some parts of a site. Admin and the mainpage will be displayable, but user section (which uses ajax) will be displayed, but can not be used (vith a transparent div set over the page). Also there is a few pages which will be disabled. my logic is that, i write a middleware, def process_request(self, request): if ayar.tonline_kapali: url_parcalari = request.path.split('/') if url_parcalari[0] not in settings.BAGIMSIZ_URLLER: if not request.is_ajax(): return render_to_response('bakim_modu.html') else: return None that code let me to display a "site closed" message for the urls not in BAGIMSIZ_URLLER (which contains urls that will be accessible) But i do not figure out how can i solve the problem about ajax pages... i need to set a header or something to the response and need to check it in the template.

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  • Fast image coordinate lookup in Numpy

    - by victor
    I've got a big numpy array full of coordinates (about 400): [[102, 234], [304, 104], .... ] And a numpy 2d array my_map of size 800x800. What's the fastest way to look up the coordinates given in that array? I tried things like paletting as described in this post: http://opencvpython.blogspot.com/2012/06/fast-array-manipulation-in-numpy.html but couldn't get it to work. I was also thinking about turning each coordinate into a linear index of the map and then piping it straight into my_map like so: my_map[linearized_coords] but I couldn't get vectorize to properly translate the coordinates into a linear fashion. Any ideas?

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  • Lucene: Fastest way to return the document occurance of a phrase?

    - by dont say the kid's name
    Hi Guys, I am trying to use Lucene (actually PyLucene!) to find out how many documents contain my exact phrase. My code currently looks like this... but it runs rather slow. Does anyone know a faster way to return document counts? phraseList = ["some phrase 1", "some phrase 2"] #etc, a list of phrases... countsearcher = IndexSearcher(SimpleFSDirectory(File(STORE_DIR)), True) analyzer = StandardAnalyzer(Version.LUCENE_CURRENT) for phrase in phraseList: query = QueryParser(Version.LUCENE_CURRENT, "contents", analyzer).parse("\"" + phrase + "\"") scoreDocs = countsearcher.search(query, 200).scoreDocs print "count is: " + str(len(scoreDocs))

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  • Loading datasets from datastore and merge into single dictionary. Resource problem.

    - by fredrik
    Hi, I have a productdatabase that contains products, parts and labels for each part based on langcodes. The problem I'm having and haven't got around is a huge amount of resource used to get the different datasets and merging them into a dict to suit my needs. The products in the database are based on a number of parts that is of a certain type (ie. color, size). And each part has a label for each language. I created 4 different models for this. Products, ProductParts, ProductPartTypes and ProductPartLabels. I've narrowed it down to about 10 lines of code that seams to generate the problem. As of currently I have 3 Products, 3 Types, 3 parts for each type, and 2 languages. And the request takes a wooping 5500ms to generate. for product in productData: productDict = {} typeDict = {} productDict['productName'] = product.name cache_key = 'productparts_%s' % (slugify(product.key())) partData = memcache.get(cache_key) if not partData: for type in typeData: typeDict[type.typeId] = { 'default' : '', 'optional' : [] } ## Start of problem lines ## for defaultPart in product.defaultPartsData: for label in labelsForLangCode: if label.key() in defaultPart.partLabelList: typeDict[defaultPart.type.typeId]['default'] = label.partLangLabel for optionalPart in product.optionalPartsData: for label in labelsForLangCode: if label.key() in optionalPart.partLabelList: typeDict[optionalPart.type.typeId]['optional'].append(label.partLangLabel) ## end problem lines ## memcache.add(cache_key, typeDict, 500) partData = memcache.get(cache_key) productDict['parts'] = partData productList.append(productDict) I guess the problem lies in the number of for loops is too many and have to iterate over the same data over and over again. labelForLangCode get all labels from ProductPartLabels that match the current langCode. All parts for a product is stored in a db.ListProperty(db.key). The same goes for all labels for a part. The reason I need the some what complex dict is that I want to display all data for a product with it's default parts and show a selector for the optional one. The defaultPartsData and optionaPartsData are properties in the Product Model that looks like this: @property def defaultPartsData(self): return ProductParts.gql('WHERE __key__ IN :key', key = self.defaultParts) @property def optionalPartsData(self): return ProductParts.gql('WHERE __key__ IN :key', key = self.optionalParts) When the completed dict is in the memcache it works smoothly, but isn't the memcache reset if the application goes in to hibernation? Also I would like to show the page for first time user(memcache empty) with out the enormous delay. Also as I said above, this is only a small amount of parts/product. What will the result be when it's 30 products with 100 parts. Is one solution to create a scheduled task to cache it in the memcache every hour? It this efficient? I know this is alot to take in, but I'm stuck. I've been at this for about 12 hours straight. And can't figure out a solution. ..fredrik

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  • Weird callback execution order in Twisted?

    - by SlashV
    Consider the following code: from twisted.internet.defer import Deferred d1 = Deferred() d2 = Deferred() def f1(result): print 'f1', def f2(result): print 'f2', def f3(result): print 'f3', def fd(result): return d2 d1.addCallback(f1) d1.addCallback(fd) d1.addCallback(f3) #/BLOCK==== d2.addCallback(f2) d1.callback(None) #=======BLOCK/ d2.callback(None) This outputs what I would expect: f1 f2 f3 However when I swap the order of the statements in BLOCK to #/BLOCK==== d1.callback(None) d2.addCallback(f2) #=======BLOCK/ i.e. Fire d1 before adding the callback to d2, I get: f1 f3 f2 I don't see why the time of firing of the deferreds should influence the callback execution order. Is this an issue with Twisted or does this make sense in some way?

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