numpy


Namenumpy JSON
Version 1.13.0rc2 PyPI version JSON
download
home_pagehttp://www.numpy.org
SummaryNumPy: array processing for numbers, strings, records, and objects.
upload_time2017-05-18 21:13:14
maintainer
docs_urlNone
authorNumPy Developers
requires_python>=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*
licenseBSD
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
Coveralis test coverage No Coveralis.
            NumPy is a general-purpose array-processing package designed to
efficiently manipulate large multi-dimensional arrays of arbitrary
records without sacrificing too much speed for small multi-dimensional
arrays.  NumPy is built on the Numeric code base and adds features
introduced by numarray as well as an extended C-API and the ability to
create arrays of arbitrary type which also makes NumPy suitable for
interfacing with general-purpose data-base applications.

There are also basic facilities for discrete fourier transform,
basic linear algebra and random number generation.

All numpy wheels distributed from pypi are BSD licensed.

Windows wheels are linked against the ATLAS BLAS / LAPACK library, restricted
to SSE2 instructions, so may not give optimal linear algebra performance for
your machine. See http://docs.scipy.org/doc/numpy/user/install.html for
alternatives.




            

Raw data

            {
    "maintainer": "", 
    "docs_url": null, 
    "requires_python": ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*", 
    "maintainer_email": "", 
    "cheesecake_code_kwalitee_id": null, 
    "keywords": "", 
    "upload_time": "2017-05-18 21:13:14", 
    "author": "NumPy Developers", 
    "home_page": "http://www.numpy.org", 
    "download_url": "https://pypi.python.org/packages/45/4e/03b577ffa5ca9b369cb75c79ca411e7449488eea2481665b819de0b5f2c4/numpy-1.13.0rc2.zip", 
    "platform": "Windows", 
    "version": "1.13.0rc2", 
    "cheesecake_documentation_id": null, 
    "description": "NumPy is a general-purpose array-processing package designed to\nefficiently manipulate large multi-dimensional arrays of arbitrary\nrecords without sacrificing too much speed for small multi-dimensional\narrays.  NumPy is built on the Numeric code base and adds features\nintroduced by numarray as well as an extended C-API and the ability to\ncreate arrays of arbitrary type which also makes NumPy suitable for\ninterfacing with general-purpose data-base applications.\n\nThere are also basic facilities for discrete fourier transform,\nbasic linear algebra and random number generation.\n\nAll numpy wheels distributed from pypi are BSD licensed.\n\nWindows wheels are linked against the ATLAS BLAS / LAPACK library, restricted\nto SSE2 instructions, so may not give optimal linear algebra performance for\nyour machine. See http://docs.scipy.org/doc/numpy/user/install.html for\nalternatives.\n\n\n\n", 
    "lcname": "numpy", 
    "bugtrack_url": "", 
    "github": false, 
    "name": "numpy", 
    "license": "BSD", 
    "summary": "NumPy: array processing for numbers, strings, records, and objects.", 
    "split_keywords": [], 
    "author_email": "numpy-discussion@python.org", 
    "urls": [
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:38:28", 
            "comment_text": "", 
            "python_version": "cp27", 
            "url": "https://pypi.python.org/packages/37/44/1ce5399eeab824033c27482d517feefe8dbd65dfab426eae8e8c091803c9/numpy-1.13.0rc2-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "md5_digest": "1452d9b7f79345d9726ab4186a6b7944", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "37/44/1ce5399eeab824033c27482d517feefe8dbd65dfab426eae8e8c091803c9/numpy-1.13.0rc2-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "size": 4551979
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:24:26", 
            "comment_text": "", 
            "python_version": "cp27", 
            "url": "https://pypi.python.org/packages/38/33/1bc15016791ab66f26d70a9319081a2be3b97fdba5602fe72c173d06fd51/numpy-1.13.0rc2-cp27-cp27m-manylinux1_i686.whl", 
            "md5_digest": "49d0bec7cc8be06d938b73bb6029ca35", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp27-cp27m-manylinux1_i686.whl", 
            "packagetype": "bdist_wheel", 
            "path": "38/33/1bc15016791ab66f26d70a9319081a2be3b97fdba5602fe72c173d06fd51/numpy-1.13.0rc2-cp27-cp27m-manylinux1_i686.whl", 
            "size": 12594779
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:25:45", 
            "comment_text": "", 
            "python_version": "cp27", 
            "url": "https://pypi.python.org/packages/78/20/fc02cf312efc3465f9df2f31784ef1931652b301a6145b16158514a0f8ab/numpy-1.13.0rc2-cp27-cp27m-manylinux1_x86_64.whl", 
            "md5_digest": "82ec58322dbadbfab64bb7222479573d", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp27-cp27m-manylinux1_x86_64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "78/20/fc02cf312efc3465f9df2f31784ef1931652b301a6145b16158514a0f8ab/numpy-1.13.0rc2-cp27-cp27m-manylinux1_x86_64.whl", 
            "size": 16632373
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:26:45", 
            "comment_text": "", 
            "python_version": "cp27", 
            "url": "https://pypi.python.org/packages/3d/ea/f67697766225b755ae870050180b12890997845a1bf2b49985e03746da5b/numpy-1.13.0rc2-cp27-cp27mu-manylinux1_i686.whl", 
            "md5_digest": "5bf00d81e5762a1efba456d11cf559a3", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp27-cp27mu-manylinux1_i686.whl", 
            "packagetype": "bdist_wheel", 
            "path": "3d/ea/f67697766225b755ae870050180b12890997845a1bf2b49985e03746da5b/numpy-1.13.0rc2-cp27-cp27mu-manylinux1_i686.whl", 
            "size": 12593495
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:28:21", 
            "comment_text": "", 
            "python_version": "cp27", 
            "url": "https://pypi.python.org/packages/5d/92/dcb800ae2b7dc6b5206dccb363097dd7c0c4ddf057b0dc56fcedba9712e1/numpy-1.13.0rc2-cp27-cp27mu-manylinux1_x86_64.whl", 
            "md5_digest": "ab8ac1c26b3ee267ed091999b49a1cf1", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp27-cp27mu-manylinux1_x86_64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "5d/92/dcb800ae2b7dc6b5206dccb363097dd7c0c4ddf057b0dc56fcedba9712e1/numpy-1.13.0rc2-cp27-cp27mu-manylinux1_x86_64.whl", 
            "size": 16630553
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T21:07:45", 
            "comment_text": "", 
            "python_version": "cp27", 
            "url": "https://pypi.python.org/packages/9c/7f/f015798d596c948527d9098399682a9016f6aa1ac882120a309ffaa286b5/numpy-1.13.0rc2-cp27-none-win32.whl", 
            "md5_digest": "1bd920951186623e0dd8953728e1f993", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp27-none-win32.whl", 
            "packagetype": "bdist_wheel", 
            "path": "9c/7f/f015798d596c948527d9098399682a9016f6aa1ac882120a309ffaa286b5/numpy-1.13.0rc2-cp27-none-win32.whl", 
            "size": 6672643
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T21:08:20", 
            "comment_text": "", 
            "python_version": "cp27", 
            "url": "https://pypi.python.org/packages/73/62/c2caf3cdf090c837d0389bf0c25aadc1e84778b0d48ed53bc109a9adc8e3/numpy-1.13.0rc2-cp27-none-win_amd64.whl", 
            "md5_digest": "d7b1d84393717da3fecb8f35997c2907", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp27-none-win_amd64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "73/62/c2caf3cdf090c837d0389bf0c25aadc1e84778b0d48ed53bc109a9adc8e3/numpy-1.13.0rc2-cp27-none-win_amd64.whl", 
            "size": 7589523
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:39:52", 
            "comment_text": "", 
            "python_version": "cp34", 
            "url": "https://pypi.python.org/packages/e3/52/c2ab7821a8b1070eb3390bf3c5e858129381d59e50a3704583dc23a435b0/numpy-1.13.0rc2-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "md5_digest": "a2e745289af350356d9c6eb6e7794fc1", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "e3/52/c2ab7821a8b1070eb3390bf3c5e858129381d59e50a3704583dc23a435b0/numpy-1.13.0rc2-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "size": 4515904
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:29:22", 
            "comment_text": "", 
            "python_version": "cp34", 
            "url": "https://pypi.python.org/packages/bc/0f/466c72e62679357185536594e3ba401095efd008d46348d7957b856b9bb4/numpy-1.13.0rc2-cp34-cp34m-manylinux1_i686.whl", 
            "md5_digest": "084449d53d652765a3c6bf2ac4967334", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp34-cp34m-manylinux1_i686.whl", 
            "packagetype": "bdist_wheel", 
            "path": "bc/0f/466c72e62679357185536594e3ba401095efd008d46348d7957b856b9bb4/numpy-1.13.0rc2-cp34-cp34m-manylinux1_i686.whl", 
            "size": 12850103
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:30:51", 
            "comment_text": "", 
            "python_version": "cp34", 
            "url": "https://pypi.python.org/packages/74/30/a558dc55e2941fd6963c1cc02d4d8eec2f0e2db5e38e115224a2932fc973/numpy-1.13.0rc2-cp34-cp34m-manylinux1_x86_64.whl", 
            "md5_digest": "1246cc8391b9e6b7f23c14eb38213bbe", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp34-cp34m-manylinux1_x86_64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "74/30/a558dc55e2941fd6963c1cc02d4d8eec2f0e2db5e38e115224a2932fc973/numpy-1.13.0rc2-cp34-cp34m-manylinux1_x86_64.whl", 
            "size": 16920617
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T21:08:54", 
            "comment_text": "", 
            "python_version": "cp34", 
            "url": "https://pypi.python.org/packages/64/b3/3e9a4772417dc5dd3536b499d52589f5afa898cf031044bab14a32ca8295/numpy-1.13.0rc2-cp34-none-win32.whl", 
            "md5_digest": "9cd076733a1827c5818a79620767ab07", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp34-none-win32.whl", 
            "packagetype": "bdist_wheel", 
            "path": "64/b3/3e9a4772417dc5dd3536b499d52589f5afa898cf031044bab14a32ca8295/numpy-1.13.0rc2-cp34-none-win32.whl", 
            "size": 6682952
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T21:09:28", 
            "comment_text": "", 
            "python_version": "cp34", 
            "url": "https://pypi.python.org/packages/c0/32/46a9823767723590a64b6d444c0ef28e7fe9e69ef8afbbe77b249550a6f2/numpy-1.13.0rc2-cp34-none-win_amd64.whl", 
            "md5_digest": "0918a3ff968d4cdb2665810510ef5bd7", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp34-none-win_amd64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "c0/32/46a9823767723590a64b6d444c0ef28e7fe9e69ef8afbbe77b249550a6f2/numpy-1.13.0rc2-cp34-none-win_amd64.whl", 
            "size": 7580577
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:40:31", 
            "comment_text": "", 
            "python_version": "cp35", 
            "url": "https://pypi.python.org/packages/5e/9b/da5757389735de77923943ab6cb294a8e3a31cbdd613a348ab9a1fdf477a/numpy-1.13.0rc2-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "md5_digest": "decc46e13bde8212432ab74f015faf83", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "5e/9b/da5757389735de77923943ab6cb294a8e3a31cbdd613a348ab9a1fdf477a/numpy-1.13.0rc2-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "size": 4517177
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:31:49", 
            "comment_text": "", 
            "python_version": "cp35", 
            "url": "https://pypi.python.org/packages/87/4f/eb0771dffc7ab320dc04220f56641c1fd0e1a314940f9ccc272b7c3290fe/numpy-1.13.0rc2-cp35-cp35m-manylinux1_i686.whl", 
            "md5_digest": "9350c2f65499d218c9576ca411e07b3c", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp35-cp35m-manylinux1_i686.whl", 
            "packagetype": "bdist_wheel", 
            "path": "87/4f/eb0771dffc7ab320dc04220f56641c1fd0e1a314940f9ccc272b7c3290fe/numpy-1.13.0rc2-cp35-cp35m-manylinux1_i686.whl", 
            "size": 12827239
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:33:30", 
            "comment_text": "", 
            "python_version": "cp35", 
            "url": "https://pypi.python.org/packages/9f/0b/4d30085363a94b09d69c2d5ce0fd6a4c500f4093c792699f2b183554e734/numpy-1.13.0rc2-cp35-cp35m-manylinux1_x86_64.whl", 
            "md5_digest": "e30ac720d9838cd461e23cf7a1cc974c", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp35-cp35m-manylinux1_x86_64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "9f/0b/4d30085363a94b09d69c2d5ce0fd6a4c500f4093c792699f2b183554e734/numpy-1.13.0rc2-cp35-cp35m-manylinux1_x86_64.whl", 
            "size": 16880587
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T21:09:56", 
            "comment_text": "", 
            "python_version": "cp35", 
            "url": "https://pypi.python.org/packages/dd/15/bd344bfaf11cd5ce15f6e1ca4e103cbebd1caaa4f089735b82b1516cee06/numpy-1.13.0rc2-cp35-none-win32.whl", 
            "md5_digest": "aeac6dfd59d946386dcf2b4bc01a240a", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp35-none-win32.whl", 
            "packagetype": "bdist_wheel", 
            "path": "dd/15/bd344bfaf11cd5ce15f6e1ca4e103cbebd1caaa4f089735b82b1516cee06/numpy-1.13.0rc2-cp35-none-win32.whl", 
            "size": 6807033
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T21:10:30", 
            "comment_text": "", 
            "python_version": "cp35", 
            "url": "https://pypi.python.org/packages/23/3a/d397c6cca10729c808ccb49f5e52979322f387b7fcbe676941294757ffd2/numpy-1.13.0rc2-cp35-none-win_amd64.whl", 
            "md5_digest": "212cbe4262a4f41f155f4581b724f4f5", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp35-none-win_amd64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "23/3a/d397c6cca10729c808ccb49f5e52979322f387b7fcbe676941294757ffd2/numpy-1.13.0rc2-cp35-none-win_amd64.whl", 
            "size": 7757913
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:40:53", 
            "comment_text": "", 
            "python_version": "cp36", 
            "url": "https://pypi.python.org/packages/16/40/54417adb730c0c4e6eac8b1ae458faf387fc9a7a8569efce000740e576fe/numpy-1.13.0rc2-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "md5_digest": "a9a104503e72ee9ad9d5ab34693e6c1c", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "16/40/54417adb730c0c4e6eac8b1ae458faf387fc9a7a8569efce000740e576fe/numpy-1.13.0rc2-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", 
            "size": 4544108
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:34:54", 
            "comment_text": "", 
            "python_version": "cp36", 
            "url": "https://pypi.python.org/packages/28/05/3fa1eda9301082fa2f454bcc3775761a4af5f4c8f2a50b013a19aa33304e/numpy-1.13.0rc2-cp36-cp36m-manylinux1_i686.whl", 
            "md5_digest": "518cac61989ae8ad5a9c1867120b31d1", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp36-cp36m-manylinux1_i686.whl", 
            "packagetype": "bdist_wheel", 
            "path": "28/05/3fa1eda9301082fa2f454bcc3775761a4af5f4c8f2a50b013a19aa33304e/numpy-1.13.0rc2-cp36-cp36m-manylinux1_i686.whl", 
            "size": 12906730
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T20:37:16", 
            "comment_text": "", 
            "python_version": "cp36", 
            "url": "https://pypi.python.org/packages/98/39/b4b0be5e8438f819dc9af14a44c3bd73e5453b343d4c0c1ca6530100abec/numpy-1.13.0rc2-cp36-cp36m-manylinux1_x86_64.whl", 
            "md5_digest": "fd726119ce09ff5175714d237b2dc7fa", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp36-cp36m-manylinux1_x86_64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "98/39/b4b0be5e8438f819dc9af14a44c3bd73e5453b343d4c0c1ca6530100abec/numpy-1.13.0rc2-cp36-cp36m-manylinux1_x86_64.whl", 
            "size": 16973512
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T21:11:29", 
            "comment_text": "", 
            "python_version": "cp36", 
            "url": "https://pypi.python.org/packages/cb/b9/d4719b7eb26f92ba6dbedced794b218617e7b4686a1939b2c1f756e90e99/numpy-1.13.0rc2-cp36-none-win32.whl", 
            "md5_digest": "6a83d8c02b6202ec71d87e4ed349c8b4", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp36-none-win32.whl", 
            "packagetype": "bdist_wheel", 
            "path": "cb/b9/d4719b7eb26f92ba6dbedced794b218617e7b4686a1939b2c1f756e90e99/numpy-1.13.0rc2-cp36-none-win32.whl", 
            "size": 6816673
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T21:12:05", 
            "comment_text": "", 
            "python_version": "cp36", 
            "url": "https://pypi.python.org/packages/ec/61/ec66ebb2cfa3479374ea9f3db54601cf608dd65bc95e861650b35124acce/numpy-1.13.0rc2-cp36-none-win_amd64.whl", 
            "md5_digest": "4686607e85bd7cb58a381ae16a6155b0", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2-cp36-none-win_amd64.whl", 
            "packagetype": "bdist_wheel", 
            "path": "ec/61/ec66ebb2cfa3479374ea9f3db54601cf608dd65bc95e861650b35124acce/numpy-1.13.0rc2-cp36-none-win_amd64.whl", 
            "size": 7767448
        }, 
        {
            "has_sig": true, 
            "upload_time": "2017-05-18T21:13:14", 
            "comment_text": "", 
            "python_version": "source", 
            "url": "https://pypi.python.org/packages/45/4e/03b577ffa5ca9b369cb75c79ca411e7449488eea2481665b819de0b5f2c4/numpy-1.13.0rc2.zip", 
            "md5_digest": "7a43a7fcc309a3d6a1829471dde053fd", 
            "downloads": 0, 
            "filename": "numpy-1.13.0rc2.zip", 
            "packagetype": "sdist", 
            "path": "45/4e/03b577ffa5ca9b369cb75c79ca411e7449488eea2481665b819de0b5f2c4/numpy-1.13.0rc2.zip", 
            "size": 5016574
        }
    ], 
    "_id": null, 
    "cheesecake_installability_id": null
}