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  • Setting up repoze.who with make_redirecting_plugin

    - by Timmy
    my file is: [plugin:form] use = repoze.who.plugins.form:make_redirecting_plugin login_form_url = /account/signin login_handler_path = /account/login logout_handler_path = /account/logout [identifiers] plugins = form;browser auth_tkt i created a form on /account/signin, but it doesnt find the identity? what has to be on the form?

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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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  • How do I relate two models/tables in Django based on non primary non unique keys?

    - by wizard
    I've got two tables that I need to relate on a single field po_num. The data is imported from another source so while I have a little bit of control over what the tables look like but I can't change them too much. What I want to do is relate these two models so I can look up one from the other based on the po_num fields. What I really need to do is join the two tables so I can do a where on a count of the related table. I would like to do filter for all Order objects that have 0 related EDI856 objects. I tried adding a foreign key to the Order model and specified the db_column and to_fields as po_num but django didn't like that the fact that Edi856.po_num wasn't unique. Here are the important fields of my current models that let me display but not filter for the data that I want. class Edi856(models.Model): po_num = models.CharField(max_length=90, db_index=True ) class Order(models.Model): po_num = models.CharField(max_length=90, db_index=True) def in_edi(self): '''Has the edi been processed?''' return Edi856.objects.filter(po_num = self.po_num).count() Thanks for taking the time to read about my problem. I'm not sure what to do from here.

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  • Estimating the boundary of arbitrarily distributed data

    - by Dave
    I have two dimensional discrete spatial data. I would like to make an approximation of the spatial boundaries of this data so that I can produce a plot with another dataset on top of it. Ideally, this would be an ordered set of (x,y) points that matplotlib can plot with the plt.Polygon() patch. My initial attempt is very inelegant: I place a fine grid over the data, and where data is found in a cell, a square matplotlib patch is created of that cell. The resolution of the boundary thus depends on the sampling frequency of the grid. Here is an example, where the grey region are the cells containing data, black where no data exists. OK, problem solved - why am I still here? Well.... I'd like a more "elegant" solution, or at least one that is faster (ie. I don't want to get on with "real" work, I'd like to have some fun with this!). The best way I can think of is a ray-tracing approach - eg: from xmin to xmax, at y=ymin, check if data boundary crossed in intervals dx y=ymin+dy, do 1 do 1-2, but now sample in y An alternative is defining a centre, and sampling in r-theta space - ie radial spokes in dtheta increments. Both would produce a set of (x,y) points, but then how do I order/link neighbouring points them to create the boundary? A nearest neighbour approach is not appropriate as, for example (to borrow from Geography), an isthmus (think of Panama connecting N&S America) could then close off and isolate regions. This also might not deal very well with the holes seen in the data, which I would like to represent as a different plt.Polygon. The solution perhaps comes from solving an area maximisation problem. For a set of points defining the data limits, what is the maximum contiguous area contained within those points To form the enclosed area, what are the neighbouring points for the nth point? How will the holes be treated in this scheme - is this erring into topology now? Apologies, much of this is me thinking out loud. I'd be grateful for some hints, suggestions or solutions. I suspect this is an oft-studied problem with many solution techniques, but I'm looking for something simple to code and quick to run... I guess everyone is, really! Cheers, David

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  • Distance between numpy arrays, columnwise

    - by Jaapsneep
    I have 2 arrays in 2D, where the column vectors are feature vectors. One array is of size F x A, the other of F x B, where A << B. As an example, for A = 2 and F = 3 (B can be anything): arr1 = np.array( [[1, 4], [2, 5], [3, 6]] ) arr2 = np.array( [[1, 4, 7, 10, ..], [2, 5, 8, 11, ..], [3, 6, 9, 12, ..]] ) I want to calculate the distance between arr1 and a fragment of arr2 that is of equal size (in this case, 3x2), for each possible fragment of arr2. The column vectors are independent of each other, so I believe I should calculate the distance between each column vector in arr1 and a collection of column vectors ranging from i to i + A from arr2 and take the sum of these distances (not sure though). Does numpy offer an efficient way of doing this, or will I have to take slices from the second array and, using another loop, calculate the distance between each column vector in arr1 and the corresponding column vector in the slice?

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  • Need a workaround to filter on related model and aggregated fields in Django

    - by parxier
    I opened a ticket for this problem. In a nutshell here is my model: class Plan(models.Model): cap = models.IntegerField() class Phone(models.Model): plan = models.ForeignKey(Plan, related_name='phones') class Call(models.Model): phone = models.ForeignKey(Phone, related_name='calls') cost = models.IntegerField() I want to run a query like this one: Phone.objects.annotate(total_cost=Sum('calls__cost')).filter(total_cost__gte=0.5*F('plan__cap')) Unfortunately Django generates bad SQL: SELECT "app_phone"."id", "app_phone"."plan_id", SUM("app_call"."cost") AS "total_cost" FROM "app_phone" INNER JOIN "app_plan" ON ("app_phone"."plan_id" = "app_plan"."id") LEFT OUTER JOIN "app_call" ON ("app_phone"."id" = "app_call"."phone_id") GROUP BY "app_phone"."id", "app_phone"."plan_id" HAVING SUM("app_call"."cost") >= 0.5 * "app_plan"."cap" and errors with: ProgrammingError: column "app_plan.cap" must appear in the GROUP BY clause or be used in an aggregate function LINE 1: ...."plan_id" HAVING SUM("app_call"."cost") >= 0.5 * "app_plan".... Is there any workaround apart from running raw SQL?

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  • SQLAlchemy introspection of ORM classes/objects

    - by Adam Batkin
    I am looking for a way to introspect SQLAlchemy ORM classes/entities to determine the types and other constraints (like maximum lengths) of an entity's properties. For example, if I have a declarative class: class User(Base): __tablename__ = "USER_TABLE" id = sa.Column(sa.types.Integer, primary_key=True) fullname = sa.Column(sa.types.String(100)) username = sa.Column(sa.types.String(20), nullable=False) password = sa.Column(sa.types.String(20), nullable=False) created_timestamp = sa.Column(sa.types.DateTime, nullable=False) I would want to be able to find out that the 'fullname' field should be a String with a maximum length of 100, and is nullable. And the 'created_timestamp' field is a DateTime and is not nullable.

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  • cx_Oracle and output variables

    - by Tim
    I'm trying to do this again an Oracle 10 database: cursor = connection.cursor() lOutput = cursor.var(cx_Oracle.STRING) cursor.execute(""" BEGIN %(out)s := 'N'; END;""", {'out' : lOutput}) print lOutput.value but I'm getting DatabaseError: ORA-01036: illegal variable name/number Is it possible to define PL/SQL blocks in cx_Oracle this way?

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  • SQLAlchemy Expression Language problem

    - by Torkel
    I'm trying to convert this to something sqlalchemy expression language compatible, I don't know if it's possible out of box and are hoping someone more experienced can help me along. The backend is PostgreSQL and if I can't make it as an expression I'll create a string instead. SELECT DISTINCT date_trunc('month', x.x) as date, COALESCE(b.res1, 0) AS res1, COALESCE(b.res2, 0) AS res2 FROM generate_series( date_trunc('year', now() - interval '1 years'), date_trunc('year', now() + interval '1 years'), interval '1 months' ) AS x LEFT OUTER JOIN( SELECT date_trunc('month', access_datetime) AS when, count(NULLIF(resource_id != 1, TRUE)) AS res1, count(NULLIF(resource_id != 2, TRUE)) AS res2 FROM tracking_entries GROUP BY date_trunc('month', access_datetime) ) AS b ON (date_trunc('month', x.x) = b.when) First of all I got a class TrackingEntry mapped to tracking_entries, the select statement within the outer joined can be converted to something like (pseudocode):: from sqlalchemy.sql import func, select from datetime import datetime, timedelta stmt = select([ func.date_trunc('month', TrackingEntry.resource_id).label('when'), func.count(func.nullif(TrackingEntry.resource_id != 1, True)).label('res1'), func.count(func.nullif(TrackingEntry.resource_id != 2, True)).label('res2') ], group_by=[func.date_trunc('month', TrackingEntry.access_datetime), ]) Considering the outer select statement I have no idea how to build it, my guess is something like: outer = select([ func.distinct(func.date_trunc('month', ?)).label('date'), func.coalesce(?.res1, 0).label('res1'), func.coalesce(?.res2, 0).label('res2') ], from_obj=[ func.generate_series( datetime.now(), datetime.now() + timedelta(days=365), timedelta(days=1) ).label(x) ]) Then I suppose I have to link those statements together without using foreign keys: outer.outerjoin(stmt???).??(func.date_trunc('month', ?.?), ?.when) Anyone got any suggestions or even better a solution?

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  • need help in site classification

    - by goh
    hi guys, I have to crawl the contents of several blogs. The problem is that I need to classify whether the blogs the authors are from a specific school and is talking about the school's stuff. May i know what's the best approach in doing the crawling or how should i go about the classification?

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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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  • Union on ValuesQuerySet in django

    - by Wuxab
    I've been searching for a way to take the union of querysets in django. From what I read you can use query1 | query2 to take the union... This doesn't seem to work when using values() though. I'd skip using values until after taking the union but I need to use annotate to take the sum of a field and filter on it and since there's no way to do "group by" I have to use values(). The other suggestions I read were to use Q objects but I can't think of a way that would work. Do I pretty much need to just use straight SQL or is there a django way of doing this? What I want is: q1 = mymodel.objects.filter(date__lt = '2010-06-11').values('field1','field2').annotate(volsum=Sum('volume')).exclude(volsum=0) q2 = mymodel.objects.values('field1','field2').annotate(volsum=Sum('volume')).exclude(volsum=0) query = q1|q2 But this doesn't work and as far as I know I need the "values" part because there's no other way for Sum to know how to act since it's a 15 column table.

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  • Getting child elements that are related to a parent in same table

    - by Madawar
    I have the following database schema class posts(Base): __tablename__ = 'xposts' id = Column(Integer, primary_key=True) class Comments(Base): __tablename__ = 'comments' id = Column(Integer, primary_key=True) comment_parent_id=Column(Integer,unique=True) #comment_id fetches comment of a comment ie the comment_parent_id comment_id=Column(Integer,default=None) comment_text=Column(String(200)) Values in database are 1 12 NULL Hello First comment 2 NULL 12 First Sub comment I want to fetch all Comments and sub comments of a post using sqlalchemy and have this so far qry=session.query(Comments).filter(Comments.comment_parent_id!=None) print qry.count() Is there a way i can fetch the all the subcomments of a comment in a query i have tried outerjoin on the same table(comments) and it seemed stupid and it failed.

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  • Unit testing authorization in a Pylons app fails; cookies aren't been correctly set or recorded

    - by Ian Stevens
    I'm having an issue running unit tests for authorization in a Pylons app. It appears as though certain cookies set in the test case may not be correctly written or parsed. Cookies work fine when hitting the app with a browser. Here is my test case inside a paste-generated TestController: def test_good_login(self): r = self.app.post('/dologin', params={'login': self.user['username'], 'password': self.password}) r = r.follow() # Should only be one redirect to root assert 'http://localhost/' == r.request.url assert 'Dashboard' in r This is supposed to test that a login of an existing account forwards the user to the dashboard page. Instead, what happens is that the user is redirected back to the login. The first POST works, sets the user in the session and returns cookies. Although those cookies are sent in the follow request, they don't seem to be correctly parsed. I start by setting a breakpoint at the beginning of the above method and see what the login response returns: > nosetests --pdb --pdb-failure -s foo.tests.functional.test_account:TestMainController.test_good_login Running setup_config() from foo.websetup > /Users/istevens/dev/foo/foo/tests/functional/test_account.py(33)test_good_login() -> r = self.app.post('/dologin', params={'login': self.user['username'], 'password': self.password}) (Pdb) n > /Users/istevens/dev/foo/foo/tests/functional/test_account.py(34)test_good_login() -> r = r.follow() # Should only be one redirect to root (Pdb) p r.cookies_set {'auth_tkt': '"4c898eb72f7ad38551eb11e1936303374bd871934bd871833d19ad8a79000000!"'} (Pdb) p r.request.environ['REMOTE_USER'] '4bd871833d19ad8a79000000' (Pdb) p r.headers['Location'] 'http://localhost/?__logins=0' A session appears to be created and a cookie sent back. The browser is redirected to the root, not the login, which also indicates a successful login. If I step past the follow(), I get: > /Users/istevens/dev/foo/foo/tests/functional/test_account.py(35)test_good_login() -> assert 'http://localhost/' == r.request.url (Pdb) p r.request.headers {'Host': 'localhost:80', 'Cookie': 'auth_tkt=""\\"4c898eb72f7ad38551eb11e1936303374bd871934bd871833d19ad8a79000000!\\"""; '} (Pdb) p r.request.environ['REMOTE_USER'] *** KeyError: KeyError('REMOTE_USER',) (Pdb) p r.request.environ['HTTP_COOKIE'] 'auth_tkt=""\\"4c898eb72f7ad38551eb11e1936303374bd871934bd871833d19ad8a79000000!\\"""; ' (Pdb) p r.request.cookies {'auth_tkt': ''} (Pdb) p r <302 Found text/html location: http://localhost/login?__logins=1&came_from=http%3A%2F%2Flocalhost%2F body='302 Found...y. '/149> This indicates to me that the cookie was passed in on the request, although with dubious escaping. The environ appears to be without the session created on the prior request. The cookie has been copied to the environ from the headers, but the cookies in the request seems incorrectly set. Lastly, the user is redirected to the login page, indicating that the user isn't logged in. Authorization in the app is done via repoze.who and repoze.who.plugins.ldap with repoze.who_friendlyform performing the challenge. I'm using the stock tests.TestController created by paste: class TestController(TestCase): def __init__(self, *args, **kwargs): if pylons.test.pylonsapp: wsgiapp = pylons.test.pylonsapp else: wsgiapp = loadapp('config:%s' % config['__file__']) self.app = TestApp(wsgiapp) url._push_object(URLGenerator(config['routes.map'], environ)) TestCase.__init__(self, *args, **kwargs) That's a webtest.TestApp, by the way. The encoding of the cookie is done in webtest.TestApp using Cookie: >>> from Cookie import _quote >>> _quote('"84533cf9f661f97239208fb844a09a6d4bd8552d4bd8550c3d19ad8339000000!"') '"\\"84533cf9f661f97239208fb844a09a6d4bd8552d4bd8550c3d19ad8339000000!\\""' I trust that that's correct. My guess is that something on the response side is incorrectly parsing the cookie data into cookies in the server-side request. But what? Any ideas?

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  • What can I use the Google App Engine for?

    - by Sergio Boombastic
    This question possibly doesn't belong here. We'll see how the answers pan out, if this doesn't belong here please move it to where it belongs. I'm following the getting started guide for Google App Engine, and I'm seeing what it can and can't do. Basically, I'm seeing it's very similar to an MVC pattern. You create your model, then create a View that uses that Model to display information. Not only that, but it uses a controller of some kind in this fashion: application = webapp.WSGIApplication( [('/', MainPage)], debug=True) My question is, why would you use this Google App Engine if it's the same as using a number of other MVC frameworks? Is the only benefit you gain the load balancing being handled by Google automagically? What is a good example of something you would need the App Engine for? I'm trying to learn, so thanks for the discussion.

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  • How to set a __str__ method for all ctype Structure classes?

    - by Reuben Thomas
    [Since asking this question, I've found: http://www.cs.unc.edu/~gb/blog/2007/02/11/ctypes-tricks/ which gives a good answer.] I just wrote a __str__ method for a ctype-generated Structure class 'foo' thus: def foo_to_str(self): s = [] for i in foo._fields_: s.append('{}: {}'.format(i[0], foo.\_\_getattribute__(self, i[0]))) return '\n'.join(s) foo.\_\_str__ = foo_to_str But this is a fairly natural way to produce a __str__ method for any Structure class. How can I add this method directly to the Structure class, so that all Structure classes generated by ctypes get it? (I am using the h2xml and xml2py scripts to auto-generate ctypes code, and this offers no obvious way to change the names of the classes output, so simply subclassing Structure, Union &c. and adding my __str__ method there would involve post-processing the output of xml2py.)

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  • Application closes on Nokia E71 when using urllib.urlopen

    - by sammr
    Hello, Im running the following code on my Nokia E71. But after the text input, the program closes abruptly. I have a GPRS connection on my phone,but i still seem to be having some problem with urllib.urlopen The code is as follows : import appuifw,urllib amountInDollars = appuifw.query(u"Enter amount in Dollars","text") data=urllib.urlopen("http://www.google.com").read() appuifw.note(u"Hey","info") Any way to fix this problem ? Thank You

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  • Trie Backtracking in Recursion

    - by Darksky
    I am building a tree for a spell checker with suggestions. Each node contains a key (a letter) and a value (array of letters down that path). So assume the following sub-trie in my big trie: W / \ a e | | k k | | is word--> e e | ... This is just a subpath of a sub-trie. W is a node and a and e are two nodes in its value array etc... At each node, I check if the next letter in the word is a value of the node. I am trying to support mistyped vowels for now. So 'weke' will yield 'wake' as a suggestion. Here's my searchWord function in my trie: def searchWord(self, word, path=""): if len(word) > 0: key = word[0] word = word[1:] if self.values.has_key(key): path = path + key nextNode = self.values[key] return nextNode.searchWord(word, path) else: # check here if key is a vowel. If it is, check for other vowel substitutes else: if self.isWord: return path # this is the word found else: return None Given 'weke', at the end when word is of length zero and path is 'weke', my code will hit the second big else block. weke is not marked as a word and so it will return with None. This will return out of searchWord with None. To avoid this, at each stack unwind or recursion backtrack, I need to check if a letter is a vowel and if it is, do the checking again. I changed the if self.values.has_key(key) loop to the following: if self.values.has_key(key): path = path + key nextNode = self.values[key] ret = nextNode.searchWord(word, path) if ret == None: # check if key == vowel and replace path # return nextNode.searchWord(... return ret What am I doing wrong here? What can I do when backtracking to achieve what I'm trying to do?

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  • Assigning a material in Blender with a script

    - by Narcolapser
    Question: How do you assign a material with a script to an object in blender? Info: I have this script to import a proprietary model type of mine that is basically a star map with object consisting of a single vertex. in order to make them look like stars and be visible they are all going to have a halo material assigned to them. I'm figuring out how to make this material and give it the values just fine, but I can't seem to get it to assign. I tried the most obvious thing which was: objectName.setMaterial(materialName) but that did nothing. and when i would take an object that had a material and call the getMaterial function on it, it would return nothing. there is something I'm missing here, can some one shed some light on it? Thanks. ~TA

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  • any faster alternative??

    - by kaushik
    cost=0 for i in range(12): cost=cost+math.pow(float(float(q[i])-float(w[i])),2) cost=(math.sqrt(cost)) Any faster alternative to this? i am need to improve my entire code so trying to improve each statements performance. thanking u

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