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  • Fastest way to find the closest point to a given point in 3D, in Python.

    - by Saebin
    So lets say I have 10,000 points in A and 10,000 points in B and want to find out the closest point in A for every B point. Currently, I simply loop through every point in B and A to find which one is closest in distance. ie. B = [(.5, 1, 1), (1, .1, 1), (1, 1, .2)] A = [(1, 1, .3), (1, 0, 1), (.4, 1, 1)] C = {} for bp in B: closestDist = -1 for ap in A: dist = sum(((bp[0]-ap[0])**2, (bp[1]-ap[1])**2, (bp[2]-ap[2])**2)) if(closestDist > dist or closestDist == -1): C[bp] = ap closestDist = dist print C However, I am sure there is a faster way to do this... any ideas?

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  • Should Python import statements always be at the top of a module?

    - by Adam J. Forster
    PEP 08 states: Imports are always put at the top of the file, just after any module comments and docstrings, and before module globals and constants. However if the class/method/function that I am importing is only used in rare cases, surely it is more efficient to do the import when it is needed? Isn't this: class SomeClass(object): def not_often_called(self) from datetime import datetime self.datetime = datetime.now() more efficient than this? from datetime import datetime class SomeClass(object): def not_often_called(self) self.datetime = datetime.now()

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  • How do i call a method by a string name using python?

    - by gath
    I have the following class; class myStringMethod(): def __init__(self): self.func_list= [('func1','print_func1()'),('func2','print_func2()')] def print_func1(self, name): print name def print_func2(self, name): print name def call_func_by_name(self): for func in self.func_list: getattr(self, func[1])('Func Name') if __name__=='__main__': strM = myStringMethod() strM.call_func_by_name() #Nothing prints out! No functions get called out, what am i missing? gath

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  • Handling extra newlines in csv files parsed with Python?

    - by rmihalyi
    I have a CSV file that contains extra newlines in some fields, e.g.: A, B, C, D, E, F 123, 456, tree , very, bla, indigo I tried the following: import csv catalog = csv.reader(open('test.csv', 'rU'), delimiter=",", dialect=csv.excel_tab) for row in catalog: print "Length: ", len(row), row and the result I got was this: Length: 6 ['A', ' B', ' C', ' D', ' E', ' F'] Length: 3 ['123', ' 456', ' tree'] Length: 4 [' ', ' very', ' bla', ' indigo'] Does anyone have any idea how I can quickly remove extraneous newlines? Thanks!

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  • In Python, how do I remove the "root" tag in an HTML snippet?

    - by Chung Wu
    Suppose I have an HTML snippet like this: <div> Hello <strong>There</strong> <div>I think <em>I am</em> feeing better!</div> <div>Don't you?</div> Yup! </div> What's the best/most robust way to remove the surrounding root element, so it looks like this: Hello <strong>There</strong> <div>I think <em>I am</em> feeing better!</div> <div>Don't you?</div> Yup! I've tried using lxml.html like this: lxml.html.fromstring(fragment_string).drop_tag() But that only gives me "Hello", which I guess makes sense. Any better ideas?

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  • How can I login to a website with Python?

    - by Shady
    How can I do it? I was trying to enter some specified link (with urllib), but to do it, I need to log in. I have this source from the site: <form id="login-form" action="auth/login" method="post"> <div> <!--label for="rememberme">Remember me</label><input type="checkbox" class="remember" checked="checked" name="remember me" /--> <label for="email" id="email-label" class="no-js">Email</label> <input id="email-email" type="text" name="handle" value="" autocomplete="off" /> <label for="combination" id="combo-label" class="no-js">Combination</label> <input id="password-clear" type="text" value="Combination" autocomplete="off" /> <input id="password-password" type="password" name="password" value="" autocomplete="off" /> <input id="sumbitLogin" class="signin" type="submit" value="Sign In" /> Is this possible?

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  • Python: why does this code take forever (infinite loop?)

    - by Rosarch
    I'm developing an app in Google App Engine. One of my methods is taking never completing, which makes me think it's caught in an infinite loop. I've stared at it, but can't figure it out. Disclaimer: I'm using http://code.google.com/p/gaeunitlink text to run my tests. Perhaps it's acting oddly? This is the problematic function: def _traverseForwards(course, c_levels): ''' Looks forwards in the dependency graph ''' result = {'nodes': [], 'arcs': []} if c_levels == 0: return result model_arc_tails_with_course = set(_getListArcTailsWithCourse(course)) q_arc_heads = DependencyArcHead.all() for model_arc_head in q_arc_heads: for model_arc_tail in model_arc_tails_with_course: if model_arc_tail.key() in model_arc_head.tails: result['nodes'].append(model_arc_head.sink) result['arcs'].append(_makeArc(course, model_arc_head.sink)) # rec_result = _traverseForwards(model_arc_head.sink, c_levels - 1) # _extendResult(result, rec_result) return result Originally, I thought it might be a recursion error, but I commented out the recursion and the problem persists. If this function is called with c_levels = 0, it runs fine. The models it references: class Course(db.Model): dept_code = db.StringProperty() number = db.IntegerProperty() title = db.StringProperty() raw_pre_reqs = db.StringProperty(multiline=True) original_description = db.StringProperty() def getPreReqs(self): return pickle.loads(str(self.raw_pre_reqs)) def __repr__(self): return "%s %s: %s" % (self.dept_code, self.number, self.title) class DependencyArcTail(db.Model): ''' A list of courses that is a pre-req for something else ''' courses = db.ListProperty(db.Key) def equals(self, arcTail): for this_course in self.courses: if not (this_course in arcTail.courses): return False for other_course in arcTail.courses: if not (other_course in self.courses): return False return True class DependencyArcHead(db.Model): ''' Maintains a course, and a list of tails with that course as their sink ''' sink = db.ReferenceProperty() tails = db.ListProperty(db.Key) Utility functions it references: def _makeArc(source, sink): return {'source': source, 'sink': sink} def _getListArcTailsWithCourse(course): ''' returns a LIST, not SET there may be duplicate entries ''' q_arc_heads = DependencyArcHead.all() result = [] for arc_head in q_arc_heads: for key_arc_tail in arc_head.tails: model_arc_tail = db.get(key_arc_tail) if course.key() in model_arc_tail.courses: result.append(model_arc_tail) return result Am I missing something pretty obvious here, or is GAEUnit acting up?

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  • Retrieving information with Python's urllib from a page that is done via __doPostBack()?

    - by Omar
    I'm trying to parse a page that has different sections that are loaded with a Javascript __doPostBack() function. An example of a link is: javascript:__doPostBack('ctl00$cphMain$ucOemSchPicker$dlSch$ctl03$btnSch','') As soon as this is clicked, the browser doesn't fetch a new URL but a section of webpage is updated to reflect new information. What would I pass into a urllib function to complete the operation?

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  • Is nothing truly ever deleted in git?

    - by allenskd
    I'm currently learning git, usually I'm a bit skeptic of VCS since I have a hard time getting used to them. I deleted a branch called "experimental" with some tmp files, I saw the files removed in my working directory so I scratched my head and wondered if this is normal, can I bring it back in case I need it again, etc. I found the SHA making the commit of the tmp files and recreated the branch with the provided sha and saw it again with all the files and their current content. Everything I do in the working directory can be reverted once I commit it? Might seem like a silly question to many people, but it kinda intrigues me so I want to know the limits

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  • Build a decision tree for classification of large amount data,using python?

    - by kaushik
    Hi,i am working for speech synthesis.In this i have a large number of pronunciation for each phone i.e alphabet and need to classify them according to few feature such as segment size(int) and alphabet itself(string) into a smaller set suitable for that particular context. For this purpose,i have decided to use decision tree for classification.the data to be parsed is in the S expression format.eg:((question)(LEFTNODE)(RIGHTNODE)). i hav idea for building decision tree for normal buit in type such as list..looking for suggestion for implementation for S expression.. kindly help.. Thanks in advance.. Note:this question may look similar to my prev post,srry if cant giv multiple post.already edited it many times so though of wirting new question instead of editing again

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  • Python instances and attributes: is this a bug or i got it totally wrong?

    - by Mirko Rossini
    Suppose you have something like this: class intlist: def __init__(self,l = []): self.l = l def add(self,a): self.l.append(a) def appender(a): obj = intlist() obj.add(a) print obj.l if __name__ == "__main__": for i in range(5): appender(i) A function creates an instance of intlist and calls on this fresh instance the method append on the instance attribute l. How comes the output of this code is: [0] [0, 1] [0, 1, 2] [0, 1, 2, 3] [0, 1, 2, 3, 4] ? If i switch obj = intlist() with obj = intlist(l=[]) I get the desired output [0] [1] [2] [3] [4] Why this happens? Thanks

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  • Python: (sampling with replacement): efficient algorithm to extract the set of UNIQUE N-tuples from a set

    - by Homunculus Reticulli
    I have a set of items, from which I want to select DISSIMILAR tuples (more on the definition of dissimilar touples later). The set could contain potentially several thousand items, although typically, it would contain only a few hundreds. I am trying to write a generic algorithm that will allow me to select N items to form an N-tuple, from the original set. The new set of selected N-tuples should be DISSIMILAR. A N-tuple A is said to be DISSIMILAR to another N-tuple B if and only if: Every pair (2-tuple) that occurs in A DOES NOT appear in B Note: For this algorithm, A 2-tuple (pair) is considered SIMILAR/IDENTICAL if it contains the same elements, i.e. (x,y) is considered the same as (y,x). This is a (possible variation on the) classic Urn Problem. A trivial (pseudocode) implementation of this algorithm would be something along the lines of def fetch_unique_tuples(original_set, tuple_size): while True: # randomly select [tuple_size] items from the set to create first set # create a key or hash from the N elements and store in a set # store selected N-tuple in a container if end_condition_met: break I don't think this is the most efficient way of doing this - and though I am no algorithm theorist, I suspect that the time for this algorithm to run is NOT O(n) - in fact, its probably more likely to be O(n!). I am wondering if there is a more efficient way of implementing such an algo, and preferably, reducing the time to O(n). Actually, as Mark Byers pointed out there is a second variable m, which is the size of the number of elements being selected. This (i.e. m) will typically be between 2 and 5. Regarding examples, here would be a typical (albeit shortened) example: original_list = ['CAGG', 'CTTC', 'ACCT', 'TGCA', 'CCTG', 'CAAA', 'TGCC', 'ACTT', 'TAAT', 'CTTG', 'CGGC', 'GGCC', 'TCCT', 'ATCC', 'ACAG', 'TGAA', 'TTTG', 'ACAA', 'TGTC', 'TGGA', 'CTGC', 'GCTC', 'AGGA', 'TGCT', 'GCGC', 'GCGG', 'AAAG', 'GCTG', 'GCCG', 'ACCA', 'CTCC', 'CACG', 'CATA', 'GGGA', 'CGAG', 'CCCC', 'GGTG', 'AAGT', 'CCAC', 'AACA', 'AATA', 'CGAC', 'GGAA', 'TACC', 'AGTT', 'GTGG', 'CGCA', 'GGGG', 'GAGA', 'AGCC', 'ACCG', 'CCAT', 'AGAC', 'GGGT', 'CAGC', 'GATG', 'TTCG'] Select 3-tuples from the original list should produce a list (or set) similar to: [('CAGG', 'CTTC', 'ACCT') ('CAGG', 'TGCA', 'CCTG') ('CAGG', 'CAAA', 'TGCC') ('CAGG', 'ACTT', 'ACCT') ('CAGG', 'CTTG', 'CGGC') .... ('CTTC', 'TGCA', 'CAAA') ] [[Edit]] Actually, in constructing the example output, I have realized that the earlier definition I gave for UNIQUENESS was incorrect. I have updated my definition and have introduced a new metric of DISSIMILARITY instead, as a result of this finding.

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  • What is the funniest bug you've ever experienced?

    - by friol
    I remember testing a geographical data normalizer written in Java that had concurrency problems. So, when you tried to normalize a city (say "Rome") and another guy did that too (say "New york"), you would get the other guy's data normalized ("NEW YORK") instead of your query. What's the bug that mostly made you smile in your career?

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  • Python - Is there a better/efficient way to find a node in tree?

    - by Sej P
    I have a node data structure defined as below and was not sure the find_matching_node method is pythonic or efficient. I am not well versed with generators but think there might be better solution using them. Any ideas? class HierarchyNode(): def __init__(self, nodeId): self.nodeId = nodeId self.children = {} # opted for dictionary to help reduce lookup time def addOrGetChild(self, childNode): return self.children.setdefault(childNode.nodeId,childNode) def find_matching_node(self, node): ''' look for the node in the immediate children of the current node. if not found recursively look for it in the children nodes until gone through all nodes ''' matching_node = self.children.get(node.nodeId) if matching_node: return matching_node else: for child in self.children.itervalues(): matching_node = child.find_matching_node(node) if matching_node: return matching_node return None

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