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  • In Python, are there builtin functions for elementwise boolean operators over boolean lists?

    - by bshanks
    For example, if you have n lists of bools of the same length, then elementwise boolean AND should return another list of that length that has True in those positions where all the input lists have True, and False everywhere else. It's pretty easy to write, i just would prefer to use a builtin if one exists (for the sake of standardization/readability). Here's an implementation of elementwise AND: def eAnd(*args): return [all(tuple) for tuple in zip(*args)] example usage: >>> eAnd([True, False, True, False, True], [True, True, False, False, True], [True, True, False, False, True]) [True, False, False, False, True] thx

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  • I'm doing a lot of lists and dictionary sorting...and this is causing memory errors in Python websit

    - by alex
    I retrieved data from the log table in my database. Then I started finding unique users, comparing/sorting lists, etc. In the end I got down to this. stats = {'2010-03-19': {'date': '2010-03-19', 'unique_users': 312, 'queries': 1465}, '2010-03-18': {'date': '2010-03-18', 'unique_users': 329, 'queries': 1659}, '2010-03-17': {'date': '2010-03-17', 'unique_users': 379, 'queries': 1845}, '2010-03-16': {'date': '2010-03-16', 'unique_users': 434, 'queries': 2336}, '2010-03-15': {'date': '2010-03-15', 'unique_users': 390, 'queries': 2138}, '2010-03-14': {'date': '2010-03-14', 'unique_users': 460, 'queries': 2221}, '2010-03-13': {'date': '2010-03-13', 'unique_users': 507, 'queries': 2242}, '2010-03-12': {'date': '2010-03-12', 'unique_users': 629, 'queries': 3523}, '2010-03-11': {'date': '2010-03-11', 'unique_users': 811, 'queries': 4274}, '2010-03-10': {'date': '2010-03-10', 'unique_users': 171, 'queries': 1297}, '2010-03-26': {'date': '2010-03-26', 'unique_users': 299, 'queries': 1617}, '2010-03-27': {'date': '2010-03-27', 'unique_users': 323, 'queries': 1310}, '2010-03-24': {'date': '2010-03-24', 'unique_users': 352, 'queries': 2112}, '2010-03-25': {'date': '2010-03-25', 'unique_users': 330, 'queries': 1290}, '2010-03-22': {'date': '2010-03-22', 'unique_users': 329, 'queries': 1798}, '2010-03-23': {'date': '2010-03-23', 'unique_users': 329, 'queries': 1857}, '2010-03-20': {'date': '2010-03-20', 'unique_users': 368, 'queries': 1693}, '2010-03-21': {'date': '2010-03-21', 'unique_users': 329, 'queries': 1511}, '2010-03-29': {'date': '2010-03-29', 'unique_users': 325, 'queries': 1718}, '2010-03-28': {'date': '2010-03-28', 'unique_users': 340, 'queries': 1815}, '2010-03-30': {'date': '2010-03-30', 'unique_users': 329, 'queries': 1891}} It's not a big dictionary. But when I try to do one last thing...it craps out on me. for k, v in stats: mylist.append(v) too many values to unpack What the heck does that mean??? TOO MANY VALUES TO UNPACK.

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  • Use a foreign key mapping to get data from the other table using Python and SQLAlchemy.

    - by Az
    Hmm, the title was harder to formulate than I thought. Basically, I've got these simple classes mapped to tables, using SQLAlchemy. I know they're missing a few items but those aren't essential for highlighting the problem. class Customer(object): def __init__(self, uid, name, email): self.uid = uid self.name = name self.email = email def __repr__(self): return str(self) def __str__(self): return "Cust: %s, Name: %s (Email: %s)" %(self.uid, self.name, self.email) The above is basically a simple customer with an id, name and an email address. class Order(object): def __init__(self, item_id, item_name, customer): self.item_id = item_id self.item_name = item_name self.customer = None def __repr__(self): return str(self) def __str__(self): return "Item ID %s: %s, has been ordered by customer no. %s" %(self.item_id, self.item_name, self.customer) This is the Orders class that just holds the order information: an id, a name and a reference to a customer. It's initialised to None to indicate that this item doesn't have a customer yet. The code's job will assign the item a customer. The following code maps these classes to respective database tables. # SQLAlchemy database transmutation engine = create_engine('sqlite:///:memory:', echo=False) metadata = MetaData() customers_table = Table('customers', metadata, Column('uid', Integer, primary_key=True), Column('name', String), Column('email', String) ) orders_table = Table('orders', metadata, Column('item_id', Integer, primary_key=True), Column('item_name', String), Column('customer', Integer, ForeignKey('customers.uid')) ) metadata.create_all(engine) mapper(Customer, customers_table) mapper(Orders, orders_table) Now if I do something like: for order in session.query(Order): print order I can get a list of orders in this form: Item ID 1001: MX4000 Laser Mouse, has been ordered by customer no. 12 What I want to do is find out customer 12's name and email address (which is why I used the ForeignKey into the Customer table). How would I go about it?

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  • Python: (sampling with replacement): efficient algorithm to extract the set of DISSIMILAR 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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  • 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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  • 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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  • What is the best way to do Bit Field manipulation in Python?

    - by ZebZiggle
    I'm reading some MPEG Transport Stream protocol over UDP and it has some funky bitfields in it (length 13 for example). I'm using the "struct" library to do the broad unpacking, but is there a simple way to say "Grab the next 13 bits" rather than have to hand-tweak the bit manipulation? I'd like something like the way C does bit fields (without having to revert to C). Suggestions?

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  • How do I find difference between times in different timezones in Python?

    - by JasonA
    Hi All, I am trying to calculate difference(in seconds) between two date/times formatted as following: 2010-05-11 17:07:33 UTC 2010-05-11 17:07:33 EDT time1 = '2010-05-11 17:07:33 UTC' time2 = '2010-05-11 17:07:33 EDT' delta = time.mktime(time.strptime(time1,"%Y-%m-%d %H:%M:%S %Z"))-\ time.mktime(time.strptime(time2, "%Y-%m-%d %H:%M:%S %Z")) The problem I got is EDT is not recognized, the specific error is "ValueError: time data '2010-05-11 17:07:33 EDT' does not match format '%Y-%m-%d %H:%M:%S %Z'" Thanks,

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  • Geometry library for python (or C++) for CAD-like operations?

    - by gct
    I'm trying to put together a simple program that will let me visualize a series of consecutive cuts on a wood panel using a router with a particular cutting head. I'm trying to find a decent geometry library that will give me a shortcut through the CAD-like stuff. Specifically, I'd like to be able to define a rectangular solid (the wood panel) and then define a bit profile shape, and take cuts through the rectangular solid (sometimes on a straight line, sometimes on a circular arc). Does anyone know of anything that will do this?

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  • How do I translate a ISO 8601 datetime string into a Python datetime object?

    - by Andrey Fedorov
    I'm getting a datetime string in a format like "2009-05-28T16:15:00" (this is ISO 8601, I believe) one hack-ish option seems to be to parse the string using time.strptime and passing the first 6 elements of the touple into the datetime constructor, like: datetime.datetime(*time.strptime("2007-03-04T21:08:12", "%Y-%m-%dT%H:%M:%S")[:6]) I haven't been able to find a "cleaner" way of doing this, is there one?

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  • What's the non brute force way to filter a Python dictionary?

    - by Thierry Lam
    I can filter the following dictionary like: data = { 1: {'name': 'stackoverflow', 'traffic': 'high'}, 2: {'name': 'serverfault', 'traffic': 'low'}, 3: {'name': 'superuser', 'traffic': 'low'}, 4: {'name': 'mathoverflow', 'traffic': 'low'}, } traffic = 'low' for k, v in data.items(): if v['traffic'] == traffic: print k, v Is there an alternate way to do the above filtering?

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  • why can't I use "&&" in python to mean 'and'?

    - by Sergio Tapia
    Here's my code: # F. front_back # Consider dividing a string into two halves. # If the length is even, the front and back halves are the same length. # If the length is odd, we'll say that the extra char goes in the front half. # e.g. 'abcde', the front half is 'abc', the back half 'de'. # Given 2 strings, a and b, return a string of the form # a-front + b-front + a-back + b-back def front_back(a, b): # +++your code here+++ if len(a) % 2 == 0 && len(b) % 2 == 0: return a[:(len(a)/2)] + b[:(len(b)/2)] + a[(len(a)/2):] + b[(len(b)/2):] else: #todo! Not yet done. :P return I'm getting an error in the IF conditional. What am I doing wrong?

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  • Should I be using abstract methods in this Python scenario?

    - by sfjedi
    I'm not sure my approach is good design and I'm hoping I can get a tip. I'm thinking somewhere along the lines of an abstract method, but in this case I want the method to be optional. This is how I'm doing it now... from pymel.core import * class A(object): def __init__(self, *args, **kwargs): if callable(self.createDrivers): self._drivers = self.createDrivers(*args, **kwargs) select(self._drivers) class B(A): def createDrivers(self, *args, **kwargs): c1 = circle(sweep=270)[0] c2 = circle(sweep=180)[0] return c1, c2 b = B() In the above example, I'm just creating 2 circle arcs in PyMEL for Maya, but I fully intend on creating more subclasses that may or may not have a createDrivers method at all! So I want it to be optional and I'm wondering if my approach is—well, if my approach could be improved?

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  • How to replace&add the dataframe element by another dataframe in Python Pandas?

    - by bigbug
    Suppose I have two data frame 'df_a' & 'df_b' , both have the same index structure and columns, but some of the inside data elements are different: >>> df_a sales cogs STK_ID QT 000876 1 100 100 2 100 100 3 100 100 4 100 100 5 100 100 6 100 100 7 100 100 >>> df_b sales cogs STK_ID QT 000876 5 50 50 6 50 50 7 50 50 8 50 50 9 50 50 10 50 50 And now I want to replace the element of df_a by element of df_b which have the same (index, column) coordinate, and attach df_b's elements whose (index, column) coordinate beyond the scope of df_a . Just like add a patch 'df_b' to 'df_a' : >>> df_c = patch(df_a,df_b) sales cogs STK_ID QT 000876 1 100 100 2 100 100 3 100 100 4 100 100 5 50 50 6 50 50 7 50 50 8 50 50 9 50 50 10 50 50 How to write the 'patch(df_a,df_b)' function ?

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  • How to read back and print text with newlines from a Python (Django) string with HTML?

    - by user1801486
    If someone types in a phrase, such as: I see you driving round town with the girl I love, and I’m like: haiku. (no blank lines between each line, but the text is written on three separate lines) into a text box on a web page, and then presses a button which is then stored in a database via Django, and that string is read back and printed on a page, how can I get it to print on an HTML page with the newlines still in the text? So instead of it being printed back as: I see you driving round town with the girl I love, and I’m like: haiku. It would print as: I see you driving round town with the girl I love, and I’m like: haiku. I know that if I use: (textarea)soAndSo.body(/textarea), this preserves the newlines that were in the file when the user typed it up originally. How can I get this same effect, but without having to use textarea boxes?

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