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  • fastest way to search through this data object? (python)

    - by victor
    I have a data object that looks like this: { 'node-16': { 'tags': ['cuda'], 'localNodes': [ { 'name': 'nC', 'consumesFrom': ['nA', 'nB'], 'classType': 'VectorAdder.VectorAdder' }, { 'name': 'nB', 'consumesFrom': None, 'classType': 'RandomVector' } ] }, 'node-17': { 'tags': ['boring'], 'localNodes': [ { 'name': 'nA', 'consumesFrom': None, 'classType': 'RandomVector' } ] } } Notice that node nA is a producer for nC. What's the fastest way to find out if a given localNode is a producer for another localnode in the data structure (and not within the same list)? For example, I would like to know that nA (node-17) produces for nC (exists on node-16). But I don't need to know that nB produces for nC, since they exist in the same localNodes list.

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  • How to optimize this Python code?

    - by RandomVector
    def maxVote(nLabels): count = {} maxList = [] maxCount = 0 for nLabel in nLabels: if nLabel in count: count[nLabel] += 1 else: count[nLabel] = 1 #Check if the count is max if count[nLabel] > maxCount: maxCount = count[nLabel] maxList = [nLabel,] elif count[nLabel]==maxCount: maxList.append(nLabel) return random.choice(maxList) nLabels contains a list of integers. The above function returns the integer with highest frequency, if more than one have same frequency then a randomly selected integer from them is returned. E.g. maxVote([1,3,4,5,5,5,3,12,11]) is 5

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  • How to share a dictionary between multiple processes in python without locking

    - by RandomVector
    I need to share a huge dictionary (around 1 gb in size) between multiple processs, however since all processes will always read from it. I dont need locking. Is there any way to share a dictionary without locking? The multiprocessing module in python provides an Array class which allows sharing without locking by setting lock=false however There is no such option for Dictionary provided by manager in multiprocessing module.

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  • How can i optimize this python code

    - by RandomVector
    def maxVote(nLabels): count = {} maxList = [] maxCount = 0 for nLabel in nLabels: if nLabel in count: count[nLabel] += 1 else: count[nLabel] = 1 #Check if the count is max if count[nLabel] > maxCount: maxCount = count[nLabel] maxList = [nLabel,] elif count[nLabel]==maxCount: maxList.append(nLabel) return random.choice(maxList) nLabels contains a list of integers. The above function returns the integer with highest frequency, if more than one have same frequency then a randomly selected integer from them is returned. E.g. maxVote([1,3,4,5,5,5,3,12,11]) is 5

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