Heuristic distribution of weighted items to bins (either a fixed number of bins or a fixed number of volume per bin). Data may be in form of list, dictionary, list of tuples or csv-file.

## Project description

This package contains greedy algorithms to solve two typical bin packing problems, (i) sorting items into a constant number of bins, (ii) sorting items into a low number of bins of constant size. Here’s a usage example

>>> import binpacking
>>>
>>> b = { 'a': 10, 'b': 10, 'c':11, 'd':1, 'e': 2,'f':7 }
>>> bins = binpacking.to_constant_bin_number(b,4) # 4 being the number of bins
>>> print("===== dict\n",b,"\n",bins)
===== dict
{'a': 10, 'b': 10, 'c': 11, 'd': 1, 'e': 2, 'f': 7}
[{'c': 11}, {'b': 10}, {'a': 10}, {'f': 7, 'e': 2, 'd': 1}]
>>>
>>> b = list(b.values())
>>> bins = binpacking.to_constant_volume(b,11) # 11 being the bin volume
>>> print("===== list\n",b,"\n",bins)
===== list
[10, 10, 11, 1, 2, 7]
[[11], [10], [10], [7, 2, 1]]

Consider you have a list of items, each carrying a weight w_i. Typical questions are

1. How can we distribute the items to a minimum number of bins N of equal volume V?

2. How can we distribute the items to exactly N bins where each carries items that sum up to approximately equal weight?

Problems like this can easily occur in modern computing. Assume you have to run computations where a lot of files of different sizes have to be loaded into the memory. However, you only have a machine with 8GB of RAM. How should you bind the files such that you have to run your program a minimum amount of times? This is equivalent to solving problem 1.

What about problem 2? Say you have to run a large number of computations. For each of the jobs you know the time it will probably take to finish. However, you only have a CPU with 4 cores. How should you distribute the jobs to the 4 cores such that they will all finish at approximately the same time?

The package provides the command line tool “binpacking” using which one can easily bin pack csv-files containing a column that can be identified with a weight. To see the usage enter

## Examples

In the repository’s directory

cd examples/
binpacking -f hamlet_word_count.csv -V 2000 -H -c count -l 10 -u 1000
binpacking -f hamlet_word_count.csv -N 4 -H -c count

in Python

import binpacking

b = { 'a': 10, 'b': 10, 'c':11, 'd':1, 'e': 2,'f':7 }
bins = binpacking.to_constant_bin_number(b,4)
print("===== dict\n",b,"\n",bins)

b = list(b.values())
bins = binpacking.to_constant_volume(b,11)
print("===== list\n",b,"\n",bins)

## Project details

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