{"id":19220999,"url":"https://github.com/midnighter/conifer-analysis","last_synced_at":"2025-11-14T02:03:39.773Z","repository":{"id":62564462,"uuid":"466259531","full_name":"Midnighter/conifer-analysis","owner":"Midnighter","description":"Post-process conifer output for downstream statistical analysis.","archived":false,"fork":false,"pushed_at":"2022-03-04T21:05:17.000Z","size":36,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-02-05T11:35:20.965Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Midnighter.png","metadata":{"files":{"readme":"README.rst","changelog":"CHANGELOG.rst","contributing":".github/CONTRIBUTING.rst","funding":null,"license":"LICENSE","code_of_conduct":".github/CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2022-03-04T20:19:56.000Z","updated_at":"2024-08-23T18:39:18.000Z","dependencies_parsed_at":"2022-11-03T16:45:41.266Z","dependency_job_id":null,"html_url":"https://github.com/Midnighter/conifer-analysis","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Midnighter%2Fconifer-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Midnighter%2Fconifer-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Midnighter%2Fconifer-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Midnighter%2Fconifer-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Midnighter","download_url":"https://codeload.github.com/Midnighter/conifer-analysis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240295198,"owners_count":19778852,"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":"2024-11-09T14:39:40.569Z","updated_at":"2025-11-14T02:03:39.659Z","avatar_url":"https://github.com/Midnighter.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"=============================\nConifer Analysis\n=============================\n\n.. image:: https://img.shields.io/pypi/v/conifer-analysis.svg\n   :target: https://pypi.org/project/conifer-analysis/\n   :alt: Current PyPI Version\n\n.. image:: https://img.shields.io/pypi/pyversions/conifer-analysis.svg\n   :target: https://pypi.org/project/conifer-analysis/\n   :alt: Supported Python Versions\n\n.. image:: https://img.shields.io/pypi/l/conifer-analysis.svg\n   :target: https://www.apache.org/licenses/LICENSE-2.0\n   :alt: Apache Software License Version 2.0\n\n.. image:: https://img.shields.io/badge/Contributor%20Covenant-v2.0%20adopted-ff69b4.svg\n   :target: .github/CODE_OF_CONDUCT.md\n   :alt: Code of Conduct\n\n.. image:: https://github.com/Midnighter/conifer-analysis/workflows/CI-CD/badge.svg\n   :target: https://github.com/Midnighter/conifer-analysis/workflows/CI-CD\n   :alt: GitHub Actions\n\n.. image:: https://codecov.io/gh/Midnighter/conifer-analysis/branch/master/graph/badge.svg\n   :target: https://codecov.io/gh/Midnighter/conifer-analysis\n   :alt: Codecov\n\n.. image:: https://img.shields.io/badge/code%20style-black-000000.svg\n   :target: https://github.com/ambv/black\n   :alt: Code Style Black\n\n.. image:: https://readthedocs.org/projects/conifer-analysis/badge/?version=latest\n   :target: https://conifer-analysis.readthedocs.io/en/latest/?badge=latest\n   :alt: Documentation Status\n\n.. summary-start\n\nPost-process conifer output for downstream statistical analysis.\n\n``conifer-analysis`` uses `dask \u003chttps://dask.org/\u003e`_ in order to analyze\n`conifer \u003chttps://github.com/Ivarz/Conifer\u003e`_ results in a distributed and\nout-of-memory fashion. This can be helpful when processing many such results.\n\nExample\n=======\n\nSay that you have a bunch of ``conifer`` results in a directory. You can\ngenerate a histogram of the confidence values per file (sample) and per taxa\nusing the provided pipeline ``confidence_hist``. Even when you work locally, it\ncan be helpful to explicitly create a distributed client controlling the number\nof workers.\n\n.. code-block:: python\n\n    from dask.distributed import Client\n    from conifer_analysis import confidence_hist\n\n    client = Client(n_workers=8)\n\nYou can then visit the `default dashboard \u003chttp://127.0.0.1:8787/status\u003e`_ in\nyour browser to observe tasks live.  Next, we run the pipeline which returns a\n``pandas.DataFrame``.\n\n.. code-block:: python\n\n    hist = confidence_hist(\"data/*.tsv\")\n    hist.info()\n\nAs an example of the returned shape:\n\n.. code-block:: console\n\n    \u003cclass 'pandas.core.frame.DataFrame'\u003e\n    RangeIndex: 7700 entries, 0 to 7699\n    Data columns (total 8 columns):\n     #   Column       Non-Null Count  Dtype\n    ---  ------       --------------  -----\n     0   path         7700 non-null   category\n     1   name         7700 non-null   category\n     2   taxonomy_id  7700 non-null   category\n     3   bin          7700 non-null   interval[float64, right]\n     4   midpoints    7700 non-null   float64\n     5   read1_hist   7700 non-null   int64\n     6   read2_hist   7700 non-null   int64\n     7   avg_hist     7700 non-null   int64\n    dtypes: category(3), float64(1), int64(3), interval(1)\n    memory usage: 385.3 KB\n\n\nInstall\n=======\n\nIt's as simple as:\n\n.. code-block:: console\n\n    pip install conifer-analysis\n\nIf you want to observe tasks in the dask dashboard, you will need additional\ndependencies.\n\n.. code-block:: console\n\n    pip install conifer-analysis[dashboard]\n\nCopyright\n=========\n\n* Copyright © 2022, Moritz E. Beber.\n* Free software distributed under the `Apache Software License 2.0\n  \u003chttps://www.apache.org/licenses/LICENSE-2.0\u003e`_.\n\n.. summary-end\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmidnighter%2Fconifer-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmidnighter%2Fconifer-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmidnighter%2Fconifer-analysis/lists"}