Search Results

Search found 13776 results on 552 pages for 'python appengine'.

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

Page 377/552 | < Previous Page | 373 374 375 376 377 378 379 380 381 382 383 384  | Next Page >

  • 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.

    Read the article

  • PostgreSQL pgdb driver raises "can't rollback" exception

    - by David Parunakian
    Hello, for some reason I'm experiencing the Operational Error with "can't rollback" message when I attempt to roll back my transaction in the following context: try: cursors[instance].execute("lock revision, app, timeout IN SHARE MODE") cursors[instance].execute("insert into app (type, active, active_revision, contents, z) values ('session', true, %s, %s, 0) returning id", (cRevision, sessionId)) sAppId = cursors[instance].fetchone()[0] cursors[instance].execute("insert into revision (app_id, type) values (%s, 'active')", (sAppId,)) cursors[instance].execute("insert into timeout (app_id, last_seen) values (%s, now())", (sAppId,)) connections[instance].commit() except pgdb.DatabaseError, e: connections[instance].rollback() return "{status: 'error', errno:4, errmsg: \"%s\"}"%(str(e).replace('\"', '\\"').replace('\n', '\\n').replace('\r', '\\r')) The driver in use is PGDB. What is fundamentally wrong here?

    Read the article

  • Extract points within a shape from a raster

    - by user308827
    Hi, I have a raster file (basically 2D array) with close to a million points. I am trying to extract a circle from the raster (and all the points that lie within the circle. Using ArcGIS is exceedingly slow for this. Can anyone suggest any image processing library that is both easy to learn and powerful and quick enough for something like this? Thanks!

    Read the article

  • Is there a way to control how pytest-xdist runs tests in parallel?

    - by superselector
    I have the following directory layout: runner.py lib/ tests/ testsuite1/ testsuite1.py testsuite2/ testsuite2.py testsuite3/ testsuite3.py testsuite4/ testsuite4.py The format of testsuite*.py modules is as follows: import pytest class testsomething: def setup_class(self): ''' do some setup ''' # Do some setup stuff here def teardown_class(self): '''' do some teardown''' # Do some teardown stuff here def test1(self): # Do some test1 related stuff def test2(self): # Do some test2 related stuff .... .... .... def test40(self): # Do some test40 related stuff if __name__=='__main()__' pytest.main(args=[os.path.abspath(__file__)]) The problem I have is that I would like to execute the 'testsuites' in parallel i.e. I want testsuite1, testsuite2, testsuite3 and testsuite4 to start execution in parallel but individual tests within the testsuites need to be executed serially. When I use the 'xdist' plugin from py.test and kick off the tests using 'py.test -n 4', py.test is gathering all the tests and randomly load balancing the tests among 4 workers. This leads to the 'setup_class' method to be executed every time of each test within a 'testsuitex.py' module (which defeats my purpose. I want setup_class to be executed only once per class and tests executed serially there after). Essentially what I want the execution to look like is: worker1: executes all tests in testsuite1.py serially worker2: executes all tests in testsuite2.py serially worker3: executes all tests in testsuite3.py serially worker4: executes all tests in testsuite4.py serially while worker1, worker2, worker3 and worker4 are all executed in parallel. Is there a way to achieve this in 'pytest-xidst' framework? The only option that I can think of is to kick off different processes to execute each test suite individually within runner.py: def test_execute_func(testsuite_path): subprocess.process('py.test %s' % testsuite_path) if __name__=='__main__': #Gather all the testsuite names for each testsuite: multiprocessing.Process(test_execute_func,(testsuite_path,))

    Read the article

  • 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

    Read the article

  • Deterministic key serialization

    - by Mike Boers
    I'm writing a mapping class which uses SQLite as the storage backend. I am currently allowing only basestring keys but it would be nice if I could use a couple more types hopefully up to anything that is hashable (ie. same requirements as the builtin dict). To that end I would like to derive a deterministic serialization scheme. Ideally, I would like to know if any implementation/protocol combination of pickle is deterministic for hashable objects (e.g. can only use cPickle with protocol 0). I noticed that pickle and cPickle do not match: >>> import pickle >>> import cPickle >>> def dumps(x): ... print repr(pickle.dumps(x)) ... print repr(cPickle.dumps(x)) ... >>> dumps(1) 'I1\n.' 'I1\n.' >>> dumps('hello') "S'hello'\np0\n." "S'hello'\np1\n." >>> dumps((1, 2, 'hello')) "(I1\nI2\nS'hello'\np0\ntp1\n." "(I1\nI2\nS'hello'\np1\ntp2\n." Another option is to use repr to dump and ast.literal_eval to load. This would only be valid for builtin hashable types. I have written a function to determine if a given key would survive this process (it is rather conservative on the types it allows): def is_reprable_key(key): return type(key) in (int, str, unicode) or (type(key) == tuple and all( is_reprable_key(x) for x in key)) The question for this method is if repr itself is deterministic for the types that I have allowed here. I believe this would not survive the 2/3 version barrier due to the change in str/unicode literals. This also would not work for integers where 2**32 - 1 < x < 2**64 jumping between 32 and 64 bit platforms. Are there any other conditions (ie. do strings serialize differently under different conditions)? (If this all fails miserably then I can store the hash of the key along with the pickle of both the key and value, then iterate across rows that have a matching hash looking for one that unpickles to the expected key, but that really does complicate a few other things and I would rather not do it.) Any insights?

    Read the article

  • Scrape zipcode table for different urls based on county

    - by Dr.Venkman
    I used lxml and ran into a wall as my new computer wont install lxml and the code doesnt work. I know this is simple - maybe some one can help with a beautiful soup script. this is my code: import codecs import lxml as lh from selenium import webdriver import time import re results = [] city = [ 'amador'] state = [ 'CA'] for state in states: for city in citys: browser = webdriver.Firefox() link2 = 'http://www.getzips.com/cgi-bin/ziplook.exe?What=3&County='+ city +'&State=' + state + '&Submit=Look+It+Up' browser.get(link2) bcontent = browser.page_source zipcode = bcontent[bcontent.find('<td width="15%"'):bcontent.find('<p>')+0] if len(zipcode) > 0: print zipcode else: print 'none' browser.quit() Thanks for the help

    Read the article

  • Get particular row as series from pandas dataframe

    - by Pratyush
    How do we get a particular filtered row as series? Example dataframe: >>> df = pd.DataFrame({'date': [20130101, 20130101, 20130102], 'location': ['a', 'a', 'c']}) >>> df date location 0 20130101 a 1 20130101 a 2 20130102 c I need to select the row where location is c as a series. I tried: row = df[df["location"] == "c"].head(1) # gives a dataframe row = df.ix[df["location"] == "c"] # also gives a dataframe with single row In either cases I can't the row as series.

    Read the article

  • gae error : Error: Server Error, how to debug it .

    - by zjm1126
    when i upload my project to google-app-engine , it show this : Error: Server Error The server encountered an error and could not complete your request. If the problem persists, please report your problem and mention this error message and the query that caused it. why ? how can i debug this error ? thanks

    Read the article

  • How to write data by dynamic parameter name

    - by Maxim Welikobratov
    I need to be able to write data to datastore of google-app-engine for some known entity. But I don't want write assignment code for each parameter of the entity. I meen, I don't want do like this val_1 = self.request.get('prop_1') val_2 = self.request.get('prop_2') ... val_N = self.request.get('prop_N') item.prop_1 = val_1 item.prop_2 = val_2 ... item.prop_N = val_N item.put() instead, I want to do something like this args = self.request.arguments() for prop_name in args: item.set(prop_name, self.request.get(prop_name)) item.put() dose anybody know how to do this trick?

    Read the article

  • Sqlalchemy layout with WSGI application

    - by TheDude
    I'm working on writing a small WSGI application using Bottle and SqlAlchemy and am confused on how the "layout" of my application should be in terms of SqlAlchemy. My confusion is with creating engines and sessions. My understanding is that I should only create one engine with the 'create_engine' method. Should I be creating an engine instance in the global namespace in some sort of singleton pattern and creating sessions based off of it? How have you done this in your projects? Any insight would be appreciated. The examples in the documentation dont seem to make this entirely clear (unless I'm missing something obvious). Any thoughts?

    Read the article

  • Infinite loop when adding a row to a list in a class in python3

    - by Margaret
    I have a script which contains two classes. (I'm obviously deleting a lot of stuff that I don't believe is relevant to the error I'm dealing with.) The eventual task is to create a decision tree, as I mentioned in this question. Unfortunately, I'm getting an infinite loop, and I'm having difficulty identifying why. I've identified the line of code that's going haywire, but I would have thought the iterator and the list I'm adding to would be different objects. Is there some side effect of list's .append functionality that I'm not aware of? Or am I making some other blindingly obvious mistake? class Dataset: individuals = [] #Becomes a list of dictionaries, in which each dictionary is a row from the CSV with the headers as keys def field_set(self): #Returns a list of the fields in individuals[] that can be used to split the data (i.e. have more than one value amongst the individuals def classified(self, predicted_value): #Returns True if all the individuals have the same value for predicted_value def fields_exhausted(self, predicted_value): #Returns True if all the individuals are identical except for predicted_value def lowest_entropy_value(self, predicted_value): #Returns the field that will reduce <a href="http://en.wikipedia.org/wiki/Entropy_%28information_theory%29">entropy</a> the most def __init__(self, individuals=[]): and class Node: ds = Dataset() #The data that is associated with this Node links = [] #List of Nodes, the offspring Nodes of this node level = 0 #Tree depth of this Node split_value = '' #Field used to split out this Node from the parent node node_value = '' #Value used to split out this Node from the parent Node def split_dataset(self, split_value): fields = [] #List of options for split_value amongst the individuals datasets = {} #Dictionary of Datasets, each one with a value from fields[] as its key for field in self.ds.field_set()[split_value]: #Populates the keys of fields[] fields.append(field) datasets[field] = Dataset() for i in self.ds.individuals: #Adds individuals to the datasets.dataset that matches their result for split_value datasets[i[split_value]].individuals.append(i) #<---Causes an infinite loop on the second hit for field in fields: #Creates subnodes from each of the datasets.Dataset options self.add_subnode(datasets[field],split_value,field) def add_subnode(self, dataset, split_value='', node_value=''): def __init__(self, level, dataset=Dataset()): My initialisation code is currently: if __name__ == '__main__': filename = (sys.argv[1]) #Takes in a CSV file predicted_value = "# class" #Identifies the field from the CSV file that should be predicted base_dataset = parse_csv(filename) #Turns the CSV file into a list of lists parsed_dataset = individual_list(base_dataset) #Turns the list of lists into a list of dictionaries root = Node(0, Dataset(parsed_dataset)) #Creates a root node, passing it the full dataset root.split_dataset(root.ds.lowest_entropy_value(predicted_value)) #Performs the first split, creating multiple subnodes n = root.links[0] n.split_dataset(n.ds.lowest_entropy_value(predicted_value)) #Attempts to split the first subnode.

    Read the article

  • 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?

    Read the article

  • Incremement Page Hit Count in Django

    - by Andrew C
    I have a table with an IntegerField (hit_count), and when a page is visited (ie. http://site/page/3) I want record id 3 'hit_count' column in the database to increment by 1. The query should be like: update table set hit_count = hit_count + 1 where id=3 Can I do this with the standard Django Model conventions? Or should I just write the query by hand? I'm starting a new project, so I am trying to avoid hacks. We'll see how long this lasts! Thanks!

    Read the article

  • converting a treebank of vertical trees to s-expressions

    - by Andreas
    I need to preprocess a treebank corpus of sentences with parse trees. The input format is a vertical representation of trees, like so: S =NP ==(DT +def) the == (N +ani) man =VP ==V walks ...and I need it like: (S (NP (DT the) (N man)) (VP (V walks))) I have code that almost does it, but not quite. There's always a missing paren somewhere. Should I use a proper parser, maybe a CFG? The current code is at http://github.com/andreasvc/eodop/blob/master/arbobanko.py The code also contains real examples from the treebank.

    Read the article

  • Is multi-level polymorphism possible in SQLAlchemy?

    - by Jace
    Is it possible to have multi-level polymorphism in SQLAlchemy? Here's an example: class Entity(Base): __tablename__ = 'entities' id = Column(Integer, primary_key=True) created_at = Column(DateTime, default=datetime.utcnow, nullable=False) entity_type = Column(Unicode(20), nullable=False) __mapper_args__ = {'polymorphic_on': entity_type} class File(Entity): __tablename__ = 'files' id = Column(None, ForeignKey('entities.id'), primary_key=True) filepath = Column(Unicode(255), nullable=False) file_type = Column(Unicode(20), nullable=False) __mapper_args__ = {'polymorphic_identity': u'file', 'polymorphic_on': file_type) class Image(File): __mapper_args__ = {'polymorphic_identity': u'image'} __tablename__ = 'images' id = Column(None, ForeignKey('files.id'), primary_key=True) width = Column(Integer) height = Column(Integer) When I call Base.metadata.create_all(), SQLAlchemy raises the following error: NotImplementedError: Can't generate DDL for the null type IntegrityError: (IntegrityError) entities.entity_type may not be NULL. This error goes away if I remove the Image model and the polymorphic_on key in File. What gives? (Edited: the exception raised was wrong.)

    Read the article

  • 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

    Read the article

  • 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.)

    Read the article

  • Qt/PyQt dialog with togglable fullscreen mode - problem on Windows

    - by Guard
    I have a dialog created in PyQt. It's purpose and functionality don't matter. The init is: class MyDialog(QWidget, ui_module.Ui_Dialog): def __init__(self, parent=None): super(MyDialog, self).__init__(parent) self.setupUi(self) self.installEventFilter(self) self.setWindowFlags(Qt.Dialog | Qt.WindowTitleHint) self.showMaximized() Then I have event filtering method: def eventFilter(self, obj, event): if event.type() == QEvent.KeyPress: key = event.key() if key == Qt.Key_F11: if self.isFullScreen(): self.setWindowFlags(self._flags) if self._state == 'm': self.showMaximized() else: self.showNormal() self.setGeometry(self._geometry) else: self._state = 'm' if self.isMaximized() else 'n' self._flags = self.windowFlags() self._geometry = self.geometry() self.setWindowFlags(Qt.Tool | Qt.FramelessWindowHint) self.showFullScreen() return True elif key == Qt.Key_Escape: self.close() return QWidget.eventFilter(self, obj, event) As can be seen, Esc is used for dialog hiding, and F11 is used for toggling full-screen. In addition, if the user changed the dialog mode from the initial maximized to normal and possibly moved the dialog, it's state and position are restored after exiting the full-screen. Finally, the dialog is created on the MainWindow action triggered: d = MyDialog(self) d.show() It works fine on Linux (Ubuntu Lucid), but quite strange on Windows 7: if I go to the full-screen from the maximized mode, I can't exit full-screen (on F11 dialog disappears and appears in full-screen mode again). If I change the dialog's mode to Normal (by double-clicking its title), then go to full-screen and then return back, the dialog is shown in the normal mode, in the correct position, but without the title line. Most probably the reason for both cases is the same - the setWindowFlags doesn't work. But why? Is it also possible that it is the bug in the recent PyQt version? On Ubuntu I have 4.6.x from apt, and on Windows - the latest installer from the riverbank site.

    Read the article

  • SQLAlchemy: who is in charge of the "session"? ( and how to unit-test with sessions )

    - by Nick Perkins
    I need some guidance on how to use session objects with SQLAlchemy, and how to organize Unit Tests of my mapped objects. What I would like to able to do is something like this: thing = BigThing() # mapped object child = thing.new_child() # create and return a related object thing.save() # will also save the child object In order to achieve this, I was thinking of having the BigThing actually add itself ( and it's children ) to the database -- but maybe this not a good idea? One reason to add objects as soon as possible is Automatic id values that are assigned by the database -- the sooner they are available, the fewer problems there are ( right? ) What is the best way to manage session objects? Who is in charge of the session? Should it be created only when required? or saved for a long time? What about Unit Tests for my mapped objects?...how should the session be handled? Is it ever OK to have mapped objects just automatically add themselves to a database? or is that going to lead to trouble?

    Read the article

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

< Previous Page | 373 374 375 376 377 378 379 380 381 382 383 384  | Next Page >