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        "author": "Yahoo! JAPAN research",
        "author_email": "miwasaki@yahoo-corp.jp",
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        "description": "\n# python NGT\n\n[\u65e5\u672c\u8a9e](README-jp.md)\n\n## Install\nPython binding with pybind11 (ngtpy) is installed as follows.\n```\npip3 install ngt\n```\nIf you would like to use python binding with ctypes (ngt), additionally you have to install the NGT library according to the [README](../README.md#build).\n\nYou can install the python bindings with pybind11 and ctypes from source code. You **MUST** install the NGT library according to the [README](../README.md#build) before installing the python bindings as follows.\n```\npip3 install pybind11\npip3 install numpy\ncd NGT_ROOT/python\npython3 setup.py sdist\npip3 install dist/ngt-x.x.x.tar.gz\n```\nPlease note that the search speed of the ngtpy packages from PyPI is slower than that of the ngtpy that is built on your computer so that the package can be run on older CPUs.  \n\n## Documents\n\n[ngtpy (pybind11) reference](README-ngtpy.md)\n\n## Simple samples\n\n### ngtpy (pybind11)\n\nngtpy(pybind11) can reduce the processing times than ngt(ctypes). It is more effective especially for the short search time. \n\n```python\n  import ngtpy\n  import random\n\n  dim = 10\n  objects = []\n  for i in range(0, 100) :\n      vector = random.sample(range(100), dim)\n      objects.append(vector)\n\n  query = objects[0]\n\n  ngtpy.create(b\"tmp\", dim)\n  index = ngtpy.Index(b\"tmp\")\n  index.batch_insert(objects)\n  index.save()\n\n  result = index.search(query, 3)\n\n  for i, o in enumerate(result) :\n      print(str(i) + \": \" + str(o[0]) + \", \" + str(o[1]))\n      object = index.get_object(o[0])\n      print(object)\n```\n\nSee also [sample.py](sample/sample.py).\n\n### ngt (ctypes)\n\n```python\n  from ngt import base as ngt\n  import random\n\n  dim = 10\n  objects = []\n  for i in range(0, 100) :\n      vector = random.sample(range(100), dim)\n      objects.append(vector)\n\n  query = objects[0]\n  index = ngt.Index.create(b\"tmp\", dim)\n  index.insert(objects)\n  # You can also insert objects from a file like this.\n  # index.insert_from_tsv('list.tsv') \n\n  index.save()\n  # You can load saved the index like this.\n  # index = ngt.Index(b\"tmp\")\n\n  result = index.search(query, 3)\n\n  for i, o in enumerate(result) :\n      print(str(i) + \": \" + str(o.id) + \", \" + str(o.distance))\n      object = index.get_object(o.id)\n      print(object)\n```\n\n\n",
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        "license": "Apache License Version 2.0",
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