{"id":13699939,"url":"https://github.com/quantmind/dynts","last_synced_at":"2026-01-10T12:04:18.412Z","repository":{"id":57424875,"uuid":"904809","full_name":"quantmind/dynts","owner":"quantmind","description":"Python package for timeseries analysis and manipulation","archived":true,"fork":false,"pushed_at":"2016-11-02T13:02:48.000Z","size":1189,"stargazers_count":86,"open_issues_count":7,"forks_count":19,"subscribers_count":10,"default_branch":"master","last_synced_at":"2025-04-17T12:07:20.964Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"http://packages.python.org/dynts/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/quantmind.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2010-09-12T08:57:42.000Z","updated_at":"2024-12-27T15:21:32.000Z","dependencies_parsed_at":"2022-09-23T16:13:43.648Z","dependency_job_id":null,"html_url":"https://github.com/quantmind/dynts","commit_stats":null,"previous_names":[],"tags_count":11,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/quantmind%2Fdynts","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/quantmind%2Fdynts/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/quantmind%2Fdynts/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/quantmind%2Fdynts/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/quantmind","download_url":"https://codeload.github.com/quantmind/dynts/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252382806,"owners_count":21739216,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-08-02T20:00:46.183Z","updated_at":"2025-05-04T18:33:52.554Z","avatar_url":"https://github.com/quantmind.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":["Time Series","时间序列分析"],"readme":"A statistic package for python with enphasis on timeseries analysis.\r\nBuilt around numpy_, it provides several back-end timeseries classes including R-based objects via rpy2_.\r\nIt is shipped with a domain specific language for timeseries analysis\r\nand manipulation built on to of ply_.\r\n\r\n|\r\n\r\n:Badges: |license|  |pyversions| |status| |pypiversion|\r\n:Master CI: |master-build| |coverage-master|\r\n:Documentation: http://quantmind.github.io/dynts/\r\n:Dowloads: http://pypi.python.org/pypi/dynts/\r\n:Source: http://github.com/quantmind/dynts\r\n:Platforms: Linux, OSX, Windows. Python 3.5 and above\r\n:Keywords: timeseries, quantitative, finance, statistics, numpy, R, web\r\n\r\n|\r\n\r\n.. contents::\r\n    :local:\r\n\r\n\r\nTimeseries\r\n========================\r\n\r\nTo create a timeseries object directly::\r\n\r\n\t\u003e\u003e\u003e from dynts import timeseries\r\n\t\u003e\u003e\u003e ts = timeseries('test')\r\n\t\u003e\u003e\u003e ts.type\r\n\t'numpy'\r\n\t\u003e\u003e\u003e ts.name\r\n\t'test'\r\n\t\u003e\u003e\u003e ts\r\n\tTimeSeries:numpy:test\r\n\t\u003e\u003e\u003e str(ts)\r\n\t'test'\r\n\r\n\r\nDSL\r\n=======\r\nThe package comes with a Domain-Specific-Language (DSL_) dedicated\r\nto timeserie analysis and manipulation.\r\nThis is a simple multiplication::\r\n\r\n\t\u003e\u003e\u003e from dynts import api\r\n\t\u003e\u003e\u003e e = api.parse('2*GOOG')\r\n\t\u003e\u003e\u003e e\r\n\t2.0 * goog\r\n\t\u003e\u003e\u003e len(e)\r\n\t2\r\n\t\u003e\u003e\u003e list(e)\r\n\t[2.0, goog]\r\n\t\u003e\u003e\u003e ts = api.evaluate(e).unwind()\r\n\t\u003e\u003e\u003e ts\r\n\tTimeSeries:numpy:2.0 * goog\r\n\t\u003e\u003e\u003e len(ts)\r\n\t251\r\n\r\n\r\nRequirements\r\n=====================\r\nThere are few requirements that must be met:\r\n\r\n* python_ 2.6 up to python 3.3.\r\n* numpy_ version 1.5.1 or higher for arrays and matrices.\r\n* ply_ version 3.3 or higher, the building block of the DSL_.\r\n* ccy_ for date and currency manipulation.\r\n\r\nR backend\r\n===============================\r\nDepending on the back-end used, additional dependencies need to be met.\r\nFor example, there are back-ends depending on the following R packages:\r\n\r\n* rpy2_ if an R_ TimeSeries back-end is used (default).\r\n* zoo_ and PerformanceAnlytics_ for the ``zoo`` back-end (currently the default one)\r\n* timeSeries_ for the ``rmetrics`` back-end\r\n\r\nInstalling rpy2_ on Linux is straightforward, on windows it requires the\r\n`python for windows`__ extension library.\r\n\r\nOptional Requirements\r\n===============================\r\n\r\n* cython_ for performance. The library is not strictly dependent on cython, however its usage\r\n  is highly recommended. If available several python modules will be replaced by more efficient compiled C code.\r\n* xlwt_ to create spreadsheet from timeseries.\r\n* matplotlib_ for plotting.\r\n* djpcms_ for the ``web.views`` module.\r\n\r\n__ http://sourceforge.net/projects/pywin32/files/\r\n\r\n\r\n.. _running-tests:\r\n\r\nRunning Tests\r\n=================\r\nThere are three types of tests available:\r\n\r\n* ``regression`` for unit and regression tests.\r\n* ``profile`` for analysing performance of different backends and impact of cython_.\r\n* ``bench`` same as ``profile`` but geared towards speed rather than profiling.\r\n\r\nFrom the distribution directory type::\r\n\r\n\tpython setup.py test\r\n\r\nThis will run by default the regression tests. To run a profile test\r\ntype::\r\n\r\n\tpython runtests.py -t profile \u003ctest-name\u003e\r\n\r\nwhere ``\u003ctest-name\u003e`` is the name of a profile test.\r\nTo obtain a list of available tests for each test type, run::\r\n\r\n\tpython setup.py test -l\r\n\r\nfor unit tests, or::\r\n\r\n\tpython runtests.py -t profile --list\r\n\r\nfor profile, or::\r\n\r\n\tpython runtests.py -t bench --list\r\n\r\nfrom benchmarks.\r\n\r\nIt is needed since during tests some data is fetched from google finance.\r\n\r\nTo access coverage of tests you need to install the coverage_ package and run the tests using::\r\n\r\n\tcoverage run runtests.py\r\n\r\nand to check out the coverage report::\r\n\r\n\tcoverage report -m\r\n\r\n\r\n\r\n.. |pypiversion| image:: https://badge.fury.io/py/dynts.svg\r\n    :target: https://pypi.python.org/pypi/dynts\r\n.. |pyversions| image:: https://img.shields.io/pypi/pyversions/dynts.svg\r\n  :target: https://pypi.python.org/pypi/dynts\r\n.. |license| image:: https://img.shields.io/pypi/l/dynts.svg\r\n  :target: https://pypi.python.org/pypi/dynts\r\n.. |status| image:: https://img.shields.io/pypi/status/dynts.svg\r\n  :target: https://pypi.python.org/pypi/dynts\r\n.. |master-build| image:: https://travis-ci.org/quantmind/dynts.svg?branch=master\r\n  :target: https://travis-ci.org/quantmind/dynts\r\n.. |coverage-master| image:: https://coveralls.io/repos/github/quantmind/dynts/badge.svg?branch=master\r\n  :target: https://coveralls.io/github/quantmind/dynts?branch=master\r\n.. _numpy: http://numpy.scipy.org/\r\n.. _ply: http://www.dabeaz.com/ply/\r\n.. _rpy2: http://rpy.sourceforge.net/rpy2.html\r\n.. _DSL: http://en.wikipedia.org/wiki/Domain-specific_language\r\n.. _R: http://www.r-project.org/\r\n.. _ccy: http://code.google.com/p/ccy/\r\n.. _zoo: http://cran.r-project.org/web/packages/zoo/index.html\r\n.. _PerformanceAnlytics: http://cran.r-project.org/web/packages/PerformanceAnalytics/index.html\r\n.. _timeSeries: http://cran.r-project.org/web/packages/timeSeries/index.html\r\n.. _Python: http://www.python.org/\r\n.. _xlwt: http://pypi.python.org/pypi/xlwt\r\n.. _matplotlib: http://matplotlib.sourceforge.net/\r\n.. _djpcms: http://djpcms.com\r\n.. _coverage: http://nedbatchelder.com/code/coverage/\r\n.. _cython: http://www.cython.org/\r\n.. _flot: http://code.google.com/p/flot/\r\n.. _Sparklines: http://www.omnipotent.net/jquery.sparkline/\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fquantmind%2Fdynts","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fquantmind%2Fdynts","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fquantmind%2Fdynts/lists"}