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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def calcDistMatchArr(matchArr, tKey, mKey):
 """Calculate the euclidean distance of all array positions in "matchArr". :param matchArr: a dictionary of ``numpy.arrays`` containing at least two entries that are treated as cartesian coordinates. :param tKey: #TODO: docstring :param mKey: #TODO: docstring :returns: #TODO: docstring } """

    #Calculate all sorted list of all eucledian feature distances
    matchArrSize = listvalues(matchArr)[0].size

    distInfo = {'posPairs': list(), 'eucDist': list()}
    _matrix = numpy.swapaxes(numpy.array([matchArr[tKey], matchArr[mKey]]), 0, 1)

    for pos1 in range(matchArrSize-1):
        for pos2 in range(pos1+1, matchArrSize):
            distInfo['posPairs'].append((pos1, pos2))
    distInfo['posPairs'] = numpy.array(distInfo['posPairs'])
    distInfo['eucDist'] = scipy.spatial.distance.pdist(_matrix)

    distSort = numpy.argsort(distInfo['eucDist'])
    for key in list(viewkeys(distInfo)):
        distInfo[key] = distInfo[key][distSort]

    return distInfo