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  • python cairoplot store previous readings..

    - by krisdigitx
    hi, i am using cairoplot, to make graphs, however the file from where i am reading the data is growing huge and its taking a long time to process the graph is there any real-time way to produce cairo graph, or at least store the previous readings..like rrd. -krisdigitx

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  • Exposing boost::scoped_ptr in boost::python

    - by Rupert Jones
    Hello, I am getting a compile error, saying that the copy constructor of the scoped_ptr is private with the following code snippet: class a {}; struct s { boost::scoped_ptr<a> p; }; BOOST_PYTHON_MODULE( module ) { class_<s>( "s" ); } This example works with a shared_ptr though. It would be nice, if anyone knows the answer. Thanks

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  • Python - pickling fails for numpy.void objects

    - by I82Much
    >>> idmapfile = open("idmap", mode="w") >>> pickle.dump(idMap, idmapfile) >>> idmapfile.close() >>> idmapfile = open("idmap") >>> unpickled = pickle.load(idmapfile) >>> unpickled == idMap False idMap[1] {1537: (552, 1, 1537, 17.793827056884766, 3), 1540: (4220, 1, 1540, 19.31205940246582, 3), 1544: (592, 1, 1544, 18.129131317138672, 3), 1675: (529, 1, 1675, 18.347782135009766, 3), 1550: (4048, 1, 1550, 19.31205940246582, 3), 1424: (1528, 1, 1424, 19.744396209716797, 3), 1681: (1265, 1, 1681, 19.596025466918945, 3), 1560: (3457, 1, 1560, 20.530569076538086, 3), 1690: (477, 1, 1690, 17.395542144775391, 3), 1691: (554, 1, 1691, 13.446117401123047, 3), 1436: (3010, 1, 1436, 19.596025466918945, 3), 1434: (3183, 1, 1434, 19.744396209716797, 3), 1441: (3570, 1, 1441, 20.589576721191406, 3), 1435: (476, 1, 1435, 19.640911102294922, 3), 1444: (527, 1, 1444, 17.98480224609375, 3), 1478: (1897, 1, 1478, 19.596025466918945, 3), 1575: (614, 1, 1575, 19.371648788452148, 3), 1586: (2189, 1, 1586, 19.31205940246582, 3), 1716: (3470, 1, 1716, 19.158674240112305, 3), 1590: (2278, 1, 1590, 19.596025466918945, 3), 1463: (991, 1, 1463, 19.31205940246582, 3), 1594: (1890, 1, 1594, 19.596025466918945, 3), 1467: (1087, 1, 1467, 19.31205940246582, 3), 1596: (3759, 1, 1596, 19.744396209716797, 3), 1602: (3011, 1, 1602, 20.530569076538086, 3), 1547: (490, 1, 1547, 17.994071960449219, 3), 1605: (658, 1, 1605, 19.31205940246582, 3), 1606: (1794, 1, 1606, 16.964881896972656, 3), 1719: (1826, 1, 1719, 19.596025466918945, 3), 1617: (583, 1, 1617, 11.894925117492676, 3), 1492: (3441, 1, 1492, 20.500667572021484, 3), 1622: (3215, 1, 1622, 19.31205940246582, 3), 1628: (2761, 1, 1628, 19.744396209716797, 3), 1502: (1563, 1, 1502, 19.596025466918945, 3), 1632: (1108, 1, 1632, 15.457141876220703, 3), 1468: (3779, 1, 1468, 19.596025466918945, 3), 1642: (3970, 1, 1642, 19.744396209716797, 3), 1518: (612, 1, 1518, 18.570245742797852, 3), 1647: (854, 1, 1647, 16.964881896972656, 3), 1650: (2099, 1, 1650, 20.439058303833008, 3), 1651: (540, 1, 1651, 18.552841186523438, 3), 1653: (613, 1, 1653, 19.237197875976563, 3), 1532: (537, 1, 1532, 18.885730743408203, 3)} >>> unpickled[1] {1537: (64880, 1638, 56700, -1.0808743559293829e+18, 152), 1540: (64904, 1638, 0, 0.0, 0), 1544: (54472, 1490, 0, 0.0, 0), 1675: (6464, 1509, 0, 0.0, 0), 1550: (43592, 1510, 0, 0.0, 0), 1424: (43616, 1510, 0, 0.0, 0), 1681: (0, 0, 0, 0.0, 0), 1560: (400, 152, 400, 2.1299736657737219e-43, 0), 1690: (408, 152, 408, 2.7201111331839077e+26, 34), 1435: (424, 152, 61512, 1.0122952080313192e-39, 0), 1436: (400, 152, 400, 20.250289916992188, 3), 1434: (424, 152, 62080, 1.0122952080313192e-39, 0), 1441: (400, 152, 400, 12.250144958496094, 3), 1691: (424, 152, 42608, 15.813941955566406, 3), 1444: (400, 152, 400, 19.625289916992187, 3), 1606: (424, 152, 42432, 5.2947192852601414e-22, 41), 1575: (400, 152, 400, 6.2537390010262572e-36, 0), 1586: (424, 152, 42488, 1.0122601755697111e-39, 0), 1716: (400, 152, 400, 6.2537390010262572e-36, 0), 1590: (424, 152, 64144, 1.0126357235581501e-39, 0), 1463: (400, 152, 400, 6.2537390010262572e-36, 0), 1594: (424, 152, 32672, 17.002994537353516, 3), 1467: (400, 152, 400, 19.750289916992187, 3), 1596: (424, 152, 7176, 1.0124003054161436e-39, 0), 1602: (400, 152, 400, 18.500289916992188, 3), 1547: (424, 152, 7000, 1.0124003054161436e-39, 0), 1605: (400, 152, 400, 20.500289916992188, 3), 1478: (424, 152, 42256, -6.0222748507426518e+30, 222), 1719: (400, 152, 400, 6.2537390010262572e-36, 0), 1617: (424, 152, 16472, 1.0124283313854301e-39, 0), 1492: (400, 152, 400, 6.2537390010262572e-36, 0), 1622: (424, 152, 35304, 1.0123190301052127e-39, 0), 1628: (400, 152, 400, 6.2537390010262572e-36, 0), 1502: (424, 152, 63152, 19.627988815307617, 3), 1632: (400, 152, 400, 19.375289916992188, 3), 1468: (424, 152, 38088, 1.0124213248931084e-39, 0), 1642: (400, 152, 400, 6.2537390010262572e-36, 0), 1518: (424, 152, 63896, 1.0127436235399031e-39, 0), 1647: (400, 152, 400, 6.2537390010262572e-36, 0), 1650: (424, 152, 53424, 16.752857208251953, 3), 1651: (400, 152, 400, 19.250289916992188, 3), 1653: (424, 152, 50624, 1.0126497365427934e-39, 0), 1532: (400, 152, 400, 6.2537390010262572e-36, 0)} The keys come out fine, the values are screwed up. I tried same thing loading file in binary mode; didn't fix the problem. Any idea what I'm doing wrong? Edit: Here's the code with binary. Note that the values are different in the unpickled object. >>> idmapfile = open("idmap", mode="wb") >>> pickle.dump(idMap, idmapfile) >>> idmapfile.close() >>> idmapfile = open("idmap", mode="rb") >>> unpickled = pickle.load(idmapfile) >>> unpickled==idMap False >>> unpickled[1] {1537: (12176, 2281, 56700, -1.0808743559293829e+18, 152), 1540: (0, 0, 15934, 2.7457842047810522e+26, 108), 1544: (400, 152, 400, 4.9518498821046956e+27, 53), 1675: (408, 152, 408, 2.7201111331839077e+26, 34), 1550: (456, 152, 456, -1.1349175514578289e+18, 152), 1424: (432, 152, 432, 4.5939047815653343e-40, 11), 1681: (408, 152, 408, 2.1299736657737219e-43, 0), 1560: (376, 152, 376, 2.1299736657737219e-43, 0), 1690: (376, 152, 376, 2.1299736657737219e-43, 0), 1435: (376, 152, 376, 2.1299736657737219e-43, 0), 1436: (376, 152, 376, 2.1299736657737219e-43, 0), 1434: (376, 152, 376, 2.1299736657737219e-43, 0), 1441: (376, 152, 376, 2.1299736657737219e-43, 0), 1691: (376, 152, 376, 2.1299736657737219e-43, 0), 1444: (376, 152, 376, 2.1299736657737219e-43, 0), 1606: (25784, 2281, 376, -3.2883343074537754e+26, 34), 1575: (24240, 2281, 376, 2.1299736657737219e-43, 0), 1586: (24240, 2281, 376, 2.1299736657737219e-43, 0), 1716: (24240, 2281, 376, -3.0093091599657311e-35, 26), 1590: (24240, 2281, 376, 2.1299736657737219e-43, 0), 1463: (24240, 2281, 376, 2.1299736657737219e-43, 0), 1594: (24240, 2281, 376, -4123208450048.0, 196), 1467: (25784, 2281, 376, 2.1299736657737219e-43, 0), 1596: (25784, 2281, 376, 2.1299736657737219e-43, 0), 1602: (25784, 2281, 376, -5.9963281433905448e+26, 76), 1547: (25784, 2281, 376, -218106240.0, 139), 1605: (25784, 2281, 376, -3.7138649803377281e+27, 56), 1478: (376, 152, 376, 2.1299736657737219e-43, 0), 1719: (25784, 2281, 376, 2.1299736657737219e-43, 0), 1617: (25784, 2281, 376, -1.4411779941597184e+17, 237), 1492: (25784, 2281, 376, 2.8596493694487798e-30, 80), 1622: (25784, 2281, 376, 184686084096.0, 93), 1628: (1336, 152, 1336, 3.1691839245470052e+29, 179), 1502: (1272, 152, 1272, -5.2042207205116645e-17, 99), 1632: (1208, 152, 1208, 2.1299736657737219e-43, 0), 1468: (1144, 152, 1144, 2.1299736657737219e-43, 0), 1642: (1080, 152, 1080, 2.1299736657737219e-43, 0), 1518: (1016, 152, 1016, 4.0240902787680023e+35, 145), 1647: (952, 152, 952, -985172619034624.0, 237), 1650: (888, 152, 888, 12094787289088.0, 66), 1651: (824, 152, 824, 2.1299736657737219e-43, 0), 1653: (760, 152, 760, 0.00018310768064111471, 238), 1532: (696, 152, 696, 8.8978061885676389e+26, 125)} OK I've isolated the problem, but don't know why it's so. First, apparently what I'm pickling are not tuples (though they look like it), but instead numpy.void types. Here is a series to illustrate the problem. first = run0.detections[0] >>> first (1, 19, 1578, 82.637763977050781, 1) >>> type(first) <type 'numpy.void'> >>> firstTuple = tuple(first) >>> theFile = open("pickleTest", "w") >>> pickle.dump(first, theFile) >>> theTupleFile = open("pickleTupleTest", "w") >>> pickle.dump(firstTuple, theTupleFile) >>> theFile.close() >>> theTupleFile.close() >>> first (1, 19, 1578, 82.637763977050781, 1) >>> firstTuple (1, 19, 1578, 82.637764, 1) >>> theFile = open("pickleTest", "r") >>> theTupleFile = open("pickleTupleTest", "r") >>> unpickledTuple = pickle.load(theTupleFile) >>> unpickledVoid = pickle.load(theFile) >>> type(unpickledVoid) <type 'numpy.void'> >>> type(unpickledTuple) <type 'tuple'> >>> unpickledTuple (1, 19, 1578, 82.637764, 1) >>> unpickledTuple == firstTuple True >>> unpickledVoid == first False >>> unpickledVoid (7936, 1705, 56700, -1.0808743559293829e+18, 152) >>> first (1, 19, 1578, 82.637763977050781, 1)

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  • Can I avoid a threaded UDP socket in Python dropping data?

    - by 666craig
    First off, I'm new to Python and learning on the job, so be gentle! I'm trying to write a threaded Python app for Windows that reads data from a UDP socket (thread-1), writes it to file (thread-2), and displays the live data (thread-3) to a widget (gtk.Image using a gtk.gdk.pixbuf). I'm using queues for communicating data between threads. My problem is that if I start only threads 1 and 3 (so skip the file writing for now), it seems that I lose some data after the first few samples. After this drop it looks fine. Even by letting thread 1 complete before running thread 3, this apparent drop is still there. Apologies for the length of code snippet (I've removed the thread that writes to file), but I felt removing code would just prompt questions. Hope someone can shed some light :-) import socket import threading import Queue import numpy import gtk gtk.gdk.threads_init() import gtk.glade import pygtk class readFromUDPSocket(threading.Thread): def __init__(self, socketUDP, readDataQueue, packetSize, numScans): threading.Thread.__init__(self) self.socketUDP = socketUDP self.readDataQueue = readDataQueue self.packetSize = packetSize self.numScans = numScans def run(self): for scan in range(1, self.numScans + 1): buffer = self.socketUDP.recv(self.packetSize) self.readDataQueue.put(buffer) self.socketUDP.close() print 'myServer finished!' class displayWithGTK(threading.Thread): def __init__(self, displayDataQueue, image, viewArea): threading.Thread.__init__(self) self.displayDataQueue = displayDataQueue self.image = image self.viewWidth = viewArea[0] self.viewHeight = viewArea[1] self.displayData = numpy.zeros((self.viewHeight, self.viewWidth, 3), dtype=numpy.uint16) def run(self): scan = 0 try: while True: if not scan % self.viewWidth: scan = 0 buffer = self.displayDataQueue.get(timeout=0.1) self.displayData[:, scan, 0] = numpy.fromstring(buffer, dtype=numpy.uint16) self.displayData[:, scan, 1] = numpy.fromstring(buffer, dtype=numpy.uint16) self.displayData[:, scan, 2] = numpy.fromstring(buffer, dtype=numpy.uint16) gtk.gdk.threads_enter() self.myPixbuf = gtk.gdk.pixbuf_new_from_data(self.displayData.tostring(), gtk.gdk.COLORSPACE_RGB, False, 8, self.viewWidth, self.viewHeight, self.viewWidth * 3) self.image.set_from_pixbuf(self.myPixbuf) self.image.show() gtk.gdk.threads_leave() scan += 1 except Queue.Empty: print 'myDisplay finished!' pass def quitGUI(obj): print 'Currently active threads: %s' % threading.enumerate() gtk.main_quit() if __name__ == '__main__': # Create socket (IPv4 protocol, datagram (UDP)) and bind to address socketUDP = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) host = '192.168.1.5' port = 1024 socketUDP.bind((host, port)) # Data parameters samplesPerScan = 256 packetsPerSecond = 1200 packetSize = 512 duration = 1 # For now, set a fixed duration to log data numScans = int(packetsPerSecond * duration) # Create array to store data data = numpy.zeros((samplesPerScan, numScans), dtype=numpy.uint16) # Create queue for displaying from readDataQueue = Queue.Queue(numScans) # Build GUI from Glade XML file builder = gtk.Builder() builder.add_from_file('GroundVue.glade') window = builder.get_object('mainwindow') window.connect('destroy', quitGUI) view = builder.get_object('viewport') image = gtk.Image() view.add(image) viewArea = (1200, samplesPerScan) # Instantiate & start threads myServer = readFromUDPSocket(socketUDP, readDataQueue, packetSize, numScans) myDisplay = displayWithGTK(readDataQueue, image, viewArea) myServer.start() myDisplay.start() gtk.gdk.threads_enter() gtk.main() gtk.gdk.threads_leave() print 'gtk.main finished!'

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  • varargs in lambda functions in Python

    - by brain_damage
    Is it possible a lambda function to have variable number of arguments? For example, I want to write a metaclass, which creates a method for every method of some other class and this newly created method returns the opposite value of the original method and has the same number of arguments. And I want to do this with lambda function. How to pass the arguments? Is it possible? class Negate(type): def __new__(mcs, name, bases, _dict): extended_dict = _dict.copy() for (k, v) in _dict.items(): if hasattr(v, '__call__'): extended_dict["not_" + k] = lambda s, *args, **kw: not v(s, *args, **kw) return type.__new__(mcs, name, bases, extended_dict) class P(metaclass=Negate): def __init__(self, a): self.a = a def yes(self): return True def maybe(self, you_can_chose): return you_can_chose But the result is totally wrong: >>>p = P(0) >>>p.yes() True >>>p.not_yes() # should be False Traceback (most recent call last): File "<pyshell#150>", line 1, in <module> p.not_yes() File "C:\Users\Nona\Desktop\p10.py", line 51, in <lambda> extended_dict["not_" + k] = lambda s, *args, **kw: not v(s, *args, **kw) TypeError: __init__() takes exactly 2 positional arguments (1 given) >>>p.maybe(True) True >>>p.not_maybe(True) #should be False True

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  • Python string formatting too slow

    - by wich
    I use the following code to log a map, it is fast when it only contains zeroes, but as soon as there is actual data in the map it becomes unbearably slow... Is there any way to do this faster? log_file = open('testfile', 'w') for i, x in ((i, start + i * interval) for i in range(length)): log_file.write('%-5d %8.3f %13g %13g %13g %13g %13g %13g\n' % (i, x, map[0][i], map[1][i], map[2][i], map[3][i], map[4][i], map[5][i]))

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  • Python: Unpack arbitary length bits for database storage

    - by sberry2A
    I have a binary data format consisting of 18,000+ packed int64s, ints, shorts, bytes and chars. The data is packed to minimize it's size, so they don't always use byte sized chunks. For example, a number whose min and max value are 31, 32 respectively might be stored with a single bit where the actual value is bitvalue + min, so 0 is 31 and 1 is 32. I am looking for the most efficient way to unpack all of these for subsequent processing and database storage. Right now I am able to read any value by using either struct.unpack, or BitBuffer. I use struct.unpack for any data that starts on a bit where (bit-offset % 8 == 0 and data-length % 8 == 0) and I use BitBuffer for anything else. I know the offset and size of every packed piece of data, so what is going to be the fasted way to completely unpack them? Many thanks.

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  • strip spaces in python.

    - by Richard
    ok I know that this should be simple... anyways say: line = "$W5M5A,100527,142500,730301c44892fd1c,2,686.5 4,333.96,0,0,28.6,123,75,-0.4,1.4*49" I want to strip out the spaces. I thought you would just do this line = line.strip() but now line is still '$W5M5A,100527,142500,730301c44892fd1c,2,686.5 4,333.96,0,0,28.6,123,75,-0.4,1.4*49' instead of '$W5M5A,100527,142500,730301c44892fd1c,2,686.54,333.96,0,0,28.6,123,75,-0.4,1.4*49' any thoughts?

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  • Python RegExp exception

    - by Jasie
    How do I split on all nonalphanumeric characters, EXCEPT the apostrophe? re.split('\W+',text) works, but will also split on apostrophes. How do I add an exception to this rule? Thanks!

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  • Python recursion with list returns None

    - by newman
    def foo(a): a.append(1) if len(a) > 10: print a return a else: foo(a) Why this recursive function returns None (see transcript below)? I can't quite understand what I am doing wrong. In [263]: x = [] In [264]: y = foo(x) [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] In [265]: print y None

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  • Find last match with python regular expression

    - by SDD
    I wanto to match the last occurence of a simple pattern in a string, e.g. list = re.findall(r"\w+ AAAA \w+", "foo bar AAAA foo2 AAAA bar2) print "last match: ", list[len(list)-1] however, if the string is very long, a huge list of matches is generated. Is there a more direct way to match the second occurence of "AAAA" or should I use this workaround?

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  • (Python) Converting a dictionary to a list?

    - by Daria Egelhoff
    So I have this dictionary: ScoreDict = {"Blue": {'R1': 89, 'R2': 80}, "Brown": {'R1': 61, 'R2': 77}, "Purple": {'R1': 60, 'R2': 98}, "Green": {'R1': 74, 'R2': 91}, "Red": {'R1': 87, 'Lon': 74}} Is there any way how I can convert this dictionary into a list like this: ScoreList = [['Blue', 89, 80], ['Brown', 61, 77], ['Purple', 60, 98], ['Green', 74, 91], ['Red', 87, 74]] I'm not too familiar with dictionaries, so I really need some help here. Thanks in advance!

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  • PYTHON: Look for match in a nested list

    - by elfuego1
    Hello everybody, I have two nested lists of different sizes: A = [[1, 7, 3, 5], [5, 5, 14, 10]] B = [[1, 17, 3, 5], [1487, 34, 14, 74], [1487, 34, 3, 87], [141, 25, 14, 10]] I'd like to gather all nested lists from list B if A[2:4] == B[2:4] and put it into list L: L = [[1, 17, 3, 5], [141, 25, 14, 10]] Would you help me with this?

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  • python - from matrix to dictionary in single line

    - by Sanich
    matrix is a list of lists. I've to return a dictionary of the form {i:(l1[i],l2[i],...,lm[i])} Where the key i is matched with a tuple the i'th elements from each list. Say matrix=[[1,2,3,4],[9,8,7,6],[4,8,2,6]] so the line: >>> dict([(i,tuple(matrix[k][i] for k in xrange(len(matrix)))) for i in xrange(len(matrix[0]))]) does the job pretty well and outputs: {0: (1, 9, 4), 1: (2, 8, 8), 2: (3, 7, 2), 3: (4, 6, 6)} but fails if the matrix is empty: matrix=[]. The output should be: {} How can i deal with this?

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  • Python - Compress Ascii String

    - by n0idea
    I'm looking for a way to compress an ascii-based string, any help? I need also need to decompress it. I tried zlib but with no help. What can I do to compress the string into lesser length? code: def compress(request): if request.POST: data = request.POST.get('input') if is_ascii(data): result = zlib.compress(data) return render_to_response('index.html', {'result': result, 'input':data}, context_instance = RequestContext(request)) else: result = "Error, the string is not ascii-based" return render_to_response('index.html', {'result':result}, context_instance = RequestContext(request)) else: return render_to_response('index.html', {}, context_instance = RequestContext(request))

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  • Custom keys for Google App Engine models (Python)

    - by Cameron
    First off, I'm relatively new to Google App Engine, so I'm probably doing something silly. Say I've got a model Foo: class Foo(db.Model): name = db.StringProperty() I want to use name as a unique key for every Foo object. How is this done? When I want to get a specific Foo object, I currently query the datastore for all Foo objects with the target unique name, but queries are slow (plus it's a pain to ensure that name is unique when each new Foo is created). There's got to be a better way to do this! Thanks.

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  • Implement loops for python 3

    - by Alex
    Implement this loop: total up the product of the numbers from 1 to x. Implement this loop: total up the product of the numbers from a to b. Implement this loop: total up the sum of the numbers from a to b. Implement this loop: total up the sum of the numbers from 1 to x. Implement this loop: count the number of characters in a string s. i'm very lost on implementing loops these are just some examples that i am having trouble with-- if someone could help me understand how to do them that would be awesome

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  • Using __str__ representation for printing objects in containers in Python

    - by BobDobbs
    I've noticed that when an instance with an overloaded str method is passed to the print() function as an argument, it prints as intended. However, when passing a container that contains one of those instances to print(), it uses the repr method instead. That is to say, print(x) displays the correct string representation of x, and print(x, y) works correctly, but print([x]) or print((x, y)) prints the repr representation instead. First off, why does this happen? Secondly, is there a way to correct that behavior of print() in this circumstance?

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