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  • do the Python libraries have a natural dependence on the global namespace?

    - by msw
    I first ran into this when trying to determine the relative performance of two generators: t = timeit.repeat('g.get()', setup='g = my_generator()') So I dug into the timeit module and found that the setup and statement are evaluated with their own private, initially empty namespaces so naturally the binding of g never becomes accessible to the g.get() statement. The obvious solution is to wrap them into a class, thus adding to the global namespace. I bumped into this again when attempting, in another project, to use the multiprocessing module to divide a task among workers. I even bundled everything nicely into a class but unfortunately the call pool.apply_async(runmc, arg) fails with a PicklingError because buried inside the work object that runmc instantiates is (effectively) an assignment: self.predicate = lambda x, y: x > y so the whole object can't be (understandably) pickled and whereas: def foo(x, y): return x > y pickle.dumps(foo) is fine, the sequence bar = lambda x, y: x > y yields True from callable(bar) and from type(bar), but it Can't pickle <function <lambda> at 0xb759b764>: it's not found as __main__.<lambda>. I've given only code fragments because I can easily fix these cases by merely pulling them out into module or object level defs. The bug here appears to be in my understanding of the semantics of namespace use in general. If the nature of the language requires that I create more def statements I'll happily do so; I fear that I'm missing an essential concept though. Why is there such a strong reliance on the global namespace? Or, what am I failing to understand? Namespaces are one honking great idea -- let's do more of those!

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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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  • 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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  • Parallel processing from a command queue on Linux (bash, python, ruby... whatever)

    - by mlambie
    I have a list/queue of 200 commands that I need to run in a shell on a Linux server. I only want to have a maximum of 10 processes running (from the queue) at once. Some processes will take a few seconds to complete, other processes will take much longer. When a process finishes I want the next command to be "popped" from the queue and executed. Does anyone have code to solve this problem? Further elaboration: There's 200 pieces of work that need to be done, in a queue of some sort. I want to have at most 10 pieces of work going on at once. When a thread finishes a piece of work it should ask the queue for the next piece of work. If there's no more work in the queue, the thread should die. When all the threads have died it means all the work has been done. The actual problem I'm trying to solve is using imapsync to synchronize 200 mailboxes from an old mail server to a new mail server. Some users have large mailboxes and take a long time tto sync, others have very small mailboxes and sync quickly.

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  • Why does Python sometimes upgrade a string to unicode and sometimes not?

    - by samtregar
    I'm confused. Consider this code working the way I expect: >>> foo = u'Émilie and Juañ are turncoats.' >>> bar = "foo is %s" % foo >>> bar u'foo is \xc3\x89milie and Jua\xc3\xb1 are turncoats.' And this code not at all working the way I expect: >>> try: ... raise Exception(foo) ... except Exception as e: ... foo2 = e ... >>> bar = "foo2 is %s" % foo2 ------------------------------------------------------------ Traceback (most recent call last): File "<ipython console>", line 1, in <module> UnicodeEncodeError: 'ascii' codec can't encode characters in position 0-1: ordinal not in range(128) Can someone explain what's going on here? Why does it matter whether the unicode data is in a plain unicode string or stored in an Exception object? And why does this fix it: >>> bar = u"foo2 is %s" % foo2 >>> bar u'foo2 is \xc3\x89milie and Jua\xc3\xb1 are turncoats.' I am quite confused! Thanks for the help! UPDATE: My coding buddy Randall has added to my confusion in an attempt to help me! Send in the reinforcements to explain how this is supposed to make sense: >>> class A: ... def __str__(self): return "string" ... def __unicode__(self): return "unicode" ... >>> "%s %s" % (u'niño', A()) u'ni\xc3\xb1o unicode' >>> "%s %s" % (A(), u'niño') u'string ni\xc3\xb1o' Note that the order of the arguments here determines which method is called!

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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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  • 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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  • 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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  • 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 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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  • Python doctests / sphinx : style guide, how to use those and have a readable code ?

    - by Sébastien Piquemal
    Hi ! I love doctests, it is the only testing framwork I use, because it is so quick to write, and because used with sphinx it makes such great documentations with almost no effort... However, very often, I end-up doing things like this : """ Descriptions ============= bla bla bla ... >>> test 1 bla bla bla + tests tests tests * 200 lines = poor readability of the actual code """ What I mean is that I put all my tests with documentation explanations on the top of the module, so you have to scroll stupidly to find the actual code, and this is quite ugly (in my opinion). However, I think that the doctests should still stay in the module, because you should be able to read them while reading the source code. So here comes my question : sphinx/doctests lovers, how do you organize your doctests, such as the code readability doesn't suffer ?

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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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  • Python: When passing variables between methods, is it necessary to assign it a new name?

    - by Anthony
    I'm thinking that the answer is probably 'no' if the program is small and there are a lot of methods, but what about in a larger program? If I am going to be using one variable in multiple methods throughout the program, is it smarter to: Come up with a different phrasing for each method (to eliminate naming conflicts). Use the same name for each method (to eliminate confusion) Just use a global variable (to eliminate both) This is more of a stylistic question than anything else. What naming convention do YOU use when passing variables?

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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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