³ò Je|Mc @sZdZddkZddklZyddklZWn)ej odefd„ƒYZnXdefd„ƒYZ d efd „ƒYZ d efd „ƒYZ d efd„ƒYZ d„Z d„Zd„Zd„Zeed„Zdddd„Zd„Zd„Zd„Zdd„Zd„ZedjoddkZeiƒndS(sÒContainer objects, and helpers for lists and dicts. This would have been called this "collections" except that Python 2 can't import a top-level module that's the same name as a module in the current package. iÿÿÿÿN(tNotGiven(t defaultdictRcBsYeZdZd d„Zd„Zd„Zd„Zd„Zd„Z d„Z d„Z RS( s¹Backport of Python 2.5's ``defaultdict``. From the Python Cookbook. Written by Jason Kirtland. http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/523034 cOsN|dj o!t|dƒ otdƒ‚nti|||Ž||_dS(Nt__call__sfirst argument must be callable(tNonethasattrt TypeErrortdictt__init__tdefault_factory(tselfRtatkw((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyRs  cCs;yti||ƒSWn tj o|i|ƒSnXdS(N(Rt __getitem__tKeyErrort __missing__(R tkey((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR scCs8|idjot|ƒ‚n|iƒ||<}|S(N(RRR (R Rtvalue((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR!scCsH|idjo tƒ}n |if}t|ƒ|dd|iƒfS(N(RRttuplettypetitems(R targs((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyt __reduce__&s  cCs |iƒS(N(t__copy__(R ((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pytcopy,scCst|ƒ|i|ƒS(N(RR(R ((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR.scCs1ddk}t|ƒ|i|i|iƒƒƒS(Niÿÿÿÿ(RRRtdeepcopyR(R tmemoR((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyt __deepcopy__0s cCsd|iti|ƒfS(Nsdefaultdict(%s, %s)(RRt__repr__(R ((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR4s N( t__name__t __module__t__doc__RRR RRRRRR(((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyRs       t DumbObjectcBseZdZd„ZRS(sA container for arbitrary attributes. Usage:: >>> do = DumbObject(a=1, b=2) >>> do.b 2 Alternatives to this class include ``collections.namedtuple`` in Python 2.6, and ``formencode.declarative.Declarative`` in Ian Bicking's FormEncode package. Both alternatives offer more featues, but ``DumbObject`` shines in its simplicity and lack of dependencies. cKs|ii|ƒdS(N(t__dict__tupdate(R R ((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyRGs(RRRR(((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR8stCountercBsJeZdZd„Zd„Zdd„Zd„Zd„Ze eƒZRS(sâI count the number of occurrences of each value registered with me. Call the instance to register a value. The result is available as the ``.result`` attribute. Example:: >>> counter = Counter() >>> counter("foo") >>> counter("bar") >>> counter("foo") >>> sorted(counter.result.items()) [('bar', 1), ('foo', 2)] >> counter.result {'foo': 2, 'bar': 1} To see the most frequently-occurring items in order:: >>> counter.get_popular(1) [(2, 'foo')] >>> counter.get_popular() [(2, 'foo'), (1, 'bar')] Or if you prefer the list in item order:: >>> counter.get_sorted_items() [('bar', 1), ('foo', 2)] cCsttƒ|_d|_dS(Ni(Rtinttresultttotal(R ((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyRhscCs&|i|cd7<|id7_dS(s"Register an item with the counter.iN(R$R%(R titem((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyRlscCsfg}|iiƒD]}||d|dfq~}|idd„ƒ|o || Sn|SdS(sÈReturn the results as as a list of ``(count, item)`` pairs, with the most frequently occurring items first. If ``max_items`` is provided, return no more than that many items. iiRcSsti|d|dfS(ii(tsystmaxint(tx((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pytxsN(R$t iteritemstsort(R t max_itemst_[1]R)tdata((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyt get_popularqs 8 cCs|iiƒ}|iƒ|S(sOReturn the result as a list of ``(item, count)`` pairs sorted by item. (R$RR,(R R/((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pytget_sorted_items~s cCs(|ƒ}x|D]}||ƒqW|S(s Build a Counter from an iterable in one step. This is the same as adding each item individually. :: >>> counter = Counter.correlate(["A", "B", "A"]) >>> counter.result["A"] 2 >>> counter.result["B"] 1 ((tclass_titerabletcountertelm((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyt correlate…s N( RRRRRRR0R1R6t classmethod(((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR"Ks    t AccumulatorcBs5eZdZd„Zd„Zd„ZeeƒZRS(sÈAccumulate a dict of all values for each key. Call the instance to register a value. The result is available as the ``.result`` attribute. Example:: >>> bowling_scores = Accumulator() >>> bowling_scores("Fred", 0) >>> bowling_scores("Barney", 10) >>> bowling_scores("Fred", 1) >>> bowling_scores("Barney", 9) >>> sorted(bowling_scores.result.items()) [('Barney', [10, 9]), ('Fred', [0, 1])] >> bowling_scores.result {'Fred': [0, 1], 'Barney': [10, 9]} The values are stored in the order they're registered. Alternatives to this class include ``paste.util. multidict.MultiDict`` in Ian Bicking's Paste package. cCsttƒ|_dS(N(RtlistR$(R ((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR°scCs|i|i|ƒdS(sRegister a key-value pair.N(R$tappend(R RR((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR³scCs7|ƒ}x'|D]}||ƒ}|||ƒqW|S(sãCreate an Accumulator based on several related values. ``key`` is a function to calculate the key for each item, akin to ``list.sort(key=)``. This is the same as adding each item individually. ((R2R3Rt accumulatortvtk((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR6·s   (RRRRRR6R7(((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR8™s    tUniqueAccumulatorcBs eZdZd„Zd„ZRS(sËAccumulate a dict of unique values for each key. The values are stored in an unordered set. Call the instance to register a value. The result is available as the ``.result`` attribute. cCsttƒ|_dS(N(RtsetR$(R ((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyRÏscCs|i|i|ƒdS(sRegister a key-value pair.N(R$tadd(R RR((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyRÒs(RRRRR(((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyR>Æs cCsOtƒ}g}x9|D]1}||jo|i|ƒ|i|ƒqqW|S(sÔReturn a list of unique elements in the iterable, preserving the order. Usage:: >>> unique([None, "spam", 2, "spam", "A", "spam", "spam", "eggs", "spam"]) [None, 'spam', 2, 'A', 'eggs'] (R?R:R@(tittseentretR5((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pytunique×s   cCs)h}x|D]}||||> only_some_keys({"A": 1, "B": 2, "C": 3}, ["A", "C"]) >>> sorted(only_some_keys({"A": 1, "B": 2, "C": 3}, ["A", "C"]).items()) [('A', 1), ('C', 3)] ((tdictkeysRCR((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pytonly_some_keysçs cCsB|iƒ}x/|D]'}y ||=Wqtj oqXqW|S(s’Return a copy of the dict without the specified keys. :: >>> except_keys({"A": 1, "B": 2, "C": 3}, ["A", "C"]) {'B': 2} (RR (RERFRCR((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyt except_keys÷s   cCsŠx/|D]'}||jotd|ƒ‚qqWh}h}x?|iƒD]1\}}||jo|||> extract_keys({"From": "F", "To": "T", "Received", R"}, ["To", "From"]) ({"From": "F", "To": "T"}, {"Recived": "R"}) >>> regular, extra = extract_keys({"From": "F", "To": "T", "Received": "R"}, ["To", "From"]) >>> sorted(regular.keys()) ['From', 'To'] >>> sorted(extra.keys()) ['Received'] s!key %r is not in original mapping(R R(RERFR=tr1tr2R<((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyt extract_keyss   ccs•t|ƒ}xO|D]G}||jo||i|ƒfVq|tj o||fVqqW|o,x)|iƒD]\}}||fVqrWndS(sFLike ``dict.iteritems()`` but with a specified key order. Arguments: * ``dic`` is any mapping. * ``key_order`` is a list of keys. Items will be yielded in this order. * ``other_keys`` is a boolean. * ``default`` is a value returned if the key is not in the dict. This yields the items listed in ``key_order``. If a key does not exist in the dict, yield the default value if specified, otherwise skip the missing key. Afterwards, if ``other_keys`` is true, yield the remaining items in an arbitrary order. Usage:: >>> dic = {"To": "you", "From": "me", "Date": "2008/1/4", "Subject": "X"} >>> dic["received"] = "..." >>> order = ["From", "To", "Subject"] >>> list(ordered_items(dic, order, False)) [('From', 'me'), ('To', 'you'), ('Subject', 'X')] N(RtpopRR+(REt key_ordert other_keystdefaulttdRR((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyt ordered_items!s    c Cs¸g}|o&x#|D]}|i||ƒqWn|o+x(|D]}|i|i|ƒƒqAWn|oHxE|D])}||jo|i||ƒPqsqsWtd|ƒ‚n|S(scExtract values from a dict for unpacking into simple variables. ``d`` is a dict. ``required`` is a list of keys that must be in the dict. The corresponding values will be the first elements in the return list. Raise KeyError if any of the keys are missing. ``optional`` is a list of optional keys. The corresponding values will be appended to the return list, substititing None for missing keys. ``one_of`` is a list of alternative keys. Take the first key that exists and append its value to the list. Raise KeyError if none of the keys exist. This argument will append exactly one value if specified, or will do nothing if not specified. Example:: uid, action, limit, offset = get_many(request.params, required=['uid', 'action'], optional=['limit', 'offset']) Contributed by Shazow. snone of these keys found: %s(R:tgetR (RPtrequiredtoptionaltone_oftrR=((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pytget_manyBs"  cCs6x/|D]'}y ||=Wqtj oqXqWdS(såDelete several keys from a dict, ignoring those that don't exist. This modifies the dict in place. :: >>> d ={"A": 1, "B": 2, "C": 3} >>> del_quiet(d, ["A", "C"]) >>> d {'B': 2} N(R (RERFR((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyt del_quietks  cCs{h}d}xh|D]`}y||}Wn5tj o)d}||f}t||ƒ‚nX|||<|d7}qW|S(sbCorrelate several dicts under one superdict. If you have several dicts each with a 'name' key, this puts them in a container dict keyed by name. :: >>> d1 = {"name": "Fred", "age": 41} >>> d2 = {"name": "Barney", "age": 31} >>> flintstones = correlate_dicts([d1, d2], "name") >>> sorted(flintstones.keys()) ['Barney', 'Fred'] >>> flintstones["Fred"]["age"] 41 If you're having trouble spelling this method correctly, remember: "relate" has one 'l'. The 'r' is doubled because it occurs after a prefix. Thus "correlate". is''dicts' element %d contains no key '%s'i(R (tdictsRRCtiRPtmy_keytmsgttup((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pytcorrelate_dicts}s  cCsŒh}d}xy|D]q}yt||ƒ}WnAtj o5d}t|ƒi||f}t||ƒ‚nX|||<|d7}qW|S(s»Correlate several objects under one dict. If you have several objects each with a 'name' attribute, this puts them in a dict keyed by name. :: >>> class Flintstone(DumbObject): ... pass ... >>> fred = Flintstone(name="Fred", age=41) >>> barney = Flintstone(name="Barney", age=31) >>> flintstones = correlate_objects([fred, barney], "name") >>> sorted(flintstones.keys()) ['Barney', 'Fred'] >>> flintstones["Barney"].age 31 If you're having trouble spelling this method correctly, remember: "relate" has one 'l'. The 'r' is doubled because it occurs after a prefix. Thus "correlate". is7'%s' object at 'objects[%d]' contains no attribute '%s'i(tgetattrtAttributeErrorRR(tobjectstattrRCRZtobjR[R\R]((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pytcorrelate_objects s cCs|djotdƒ‚n|diƒ}|djoŠg}xytdt|ƒ|ƒD]_}||||!}t|ƒ}||jo"|g||} |i| ƒn|i|ƒqYW|SnÆ|djo¬t|ƒ} t| |ƒ\} } | o| d7} ng} t| ƒD]}| |g|q~ }x=t|ƒD]/\}}t|| ƒ\}}|||| % for row in table: % for cell in row: ${cell} % endfor cell % endfor row In a horizontal table, each row is filled before going on to the next row. This is the same as dividing the list into chunks:: >>> distribute([1, 2, 3, 4, 5, 6, 7, 8], 3, "H") [[1, 2, 3], [4, 5, 6], [7, 8, None]] In a vertical table, the first element of each sublist is filled before going on to the second element. This is useful for displaying an alphabetical list in columns, or when the entire column will be placed in a single with a
between each element:: >>> food = ["apple", "banana", "carrot", "daikon", "egg", "fish", "gelato", "honey"] >>> table = distribute(food, 3, "V", "") >>> table [['apple', 'daikon', 'gelato'], ['banana', 'egg', 'honey'], ['carrot', 'fish', '']] >>> for row in table: ... for item in row: ... print "%-9s" % item, ... print "." # To show where the line ends. ... apple daikon gelato . banana egg honey . carrot fish . Alternatives to this function include a NumPy matrix of objects. isarg 'columns' must be >= 1itHtVs,arg ``direction`` must start with 'H' or 'V'N(t ValueErrortuppertrangetlentextendR:tdivmodt enumerate(tlistcolumnst directiontfilltdirttableRZtrowtrow_lentextraR%trowst remainderR.R)R5tcol((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyt distributeÅs4A      . cCsl|pgSng}xPtt|dƒƒD]8}g}|D]}|||q=~}|i|ƒq,W|S(s>Turn a list of lists sideways, making columns into rows and vice-versa. ``array`` must be rectangular; i.e., all elements must be the same length. Otherwise the behavior is undefined: you may get ``IndexError`` or missing items. Examples:: >>> transpose([["A", "B", "C"], ["D", "E", "F"]]) [['A', 'D'], ['B', 'E'], ['C', 'F']] >>> transpose([["A", "B"], ["C", "D"], ["E", "F"]]) [['A', 'C', 'E'], ['B', 'D', 'F']] >>> transpose([]) [] Here's a pictoral view of the first example:: A B C => A D D E F B E C F This can be used to turn an HTML table into a group of div columns. An HTML table is row major: it consists of several rows, each containing several cells. But a
layout consists of only one row, each containing an entire subarray. The
s have style "float:left", which makes them appear horizonally. The items within each
are placed in their own
's or separatad by
, which makes them appear vertically. The point is that an HTML table is row major (``array[0]`` is the first row), while a group of div columns is column major (``array[0]`` is the first column). ``transpose()`` can be used to switch between the two. i(RiRjR:(tarrayRCtcR.RtRy((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyt transpose"s!%t__main__(RR'twebhelpers.miscRt collectionsRt ImportErrorRtobjectRR"R8R>RDRGRHRKtTrueRQRRWRXR^RdRzR}Rtdoctestttestmod(((se/afs/athena.mit.edu/user/x/a/xavid/Public/bazki/lib/WebHelpers-1.2-py2.5.egg/webhelpers/containers.pyss0 )N-    !)  # % ] +