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  • How to use R-Tree for plotting large number of map markers on google maps

    - by Eeyore
    After searching SO and multiple articles I haven't found a solution to my problem. What I am trying to achieve is to load 20,000 markers on Google Maps. R-Tree seems like a good approach but it's only helpful when searching for points within the visible part of the map. When the map is zoomed out it will return all of the points and...crash the browser. There is also the problem with dragging the map and at the end of dragging re-running the query. I would like to know how I can use R-Tree and be able to achieve the all of the above.

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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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • How to catch YouTube embed code and turn into URL

    - by Jonathan Vanasco
    I need to strip YouTube embed codes down to their URL only. This is the exact opposite of all but one question on StackOverflow. Most people want to turn the URL into an embed code. This question addresses the usage patttern I want, but is tied to a specific embed code's regex ( Strip YouTube Embed Code Down to URL Only ) I'm not familiar with how YouTube has offered embeds over the years - or how the sizes differ. According to their current site, there are 2 possible embed templates and a variety of options. If that's it, I can handle a regex myself -- but I was hoping someone had more knowledge they could share, so I could write a proper regex pattern that matches them all and not run into endless edge-cases. The full use case scenario : user enters content in web based wysiwig editor backend cleans out youtube & other embed codes; reformats approved embeds into an internal format as the text is all converted to markdown. on display, appropriate current template/code display for youtube or other 3rd party site is generated At a previous company, our tech-team devised a plan where YouTube videos were embedded by listing the URL only. That worked great , but it was in a CMS where everyone was trained. I'm trying to create a similar storage, but for user-generated-content.

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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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  • How can I load a sql "dump" file into sql alchemy

    - by JudoWill
    I have a large sql dump file ... with multiple CREATE TABLE and INSERT INTO statements. Is there any way to load these all into a SQLAlchemy sqlite database at once. I plan to use the introspected ORM from sqlsoup after I've created the tables. However, when I use the engine.execute() method it complains: sqlite3.Warning: You can only execute one statement at a time. Is there a way to work around this issue. Perhaps splitting the file with a regexp or some kind of parser, but I don't know enough SQL to get all of the cases for the regexp. Any help would be greatly appreciated. Will EDIT: Since this seems important ... The dump file was created with a MySQL database and so it has quite a few commands/syntax that sqlite3 does not understand correctly.

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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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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  • 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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