{ "info": { "author": "Yang Fang", "author_email": "yangfangscu@gmail.com", "bugtrack_url": null, "classifiers": [], "description": "PhySpeTree: automatically reconstructing phylogenetic species tree\n==============================================================================\n\n|PyPI version| |Docs| |License|\n\n**PhySpeTree is implemented in Python language (supports Python2.7+ and Python3+), designed for Linux systems.**\n\n**Documents**: `PhySpeTree documentation `_.\n\n.. contents:: :local:\n\n\nIntroduction\n------------------------------------------------------------------------------\nUnderstanding phylogenetic relationships between different species is crucial for evolutionary studies. Reconstructing the\nphylogenetic species tree, a branching diagram, is particularly useful in inferring evolutionary relationships. For example,\nthe tree-of-life provides a remarkable view of organizing principles of the biological world. So, the exact species tree to\nbe reconstructed is necessary, but the process of reconstructing the species or gene tree is very tedious.\n\nHere, we developed an easy-to-use package named PhySpeTree that is convenient to reconstruct species trees by one command line.\nTwo independent pipelines were included by using the most adopted small subunit ribosomal RNA (SSU rRNA) and concatenated highly\nconserved proteins (HCP), respectively. A distinct advantage is that users only need to input species names and PhySpeTree\nautomatically downloads and analyzes sequences of SSU rRNA or HCP from about 4,000 organisms.\n\nPhySpeTree workflow\n------------------------------------------------------------------------------\n\n.. image:: https://raw.githubusercontent.com/yangfangs/physpetools/master/docs/docs/img/PhySpeTree_work_follow.png\n\n\nPhySpeTree workflow includes the following steps:\n\n- \u2460 Automatic tree reconstruction.\n\n- \u2461 Processing user-defined fasta files for unannotated organisms.\n\n- \u2462 Reconstructing species trees with unannotated organisms.\n\n\nFeatures\n--------------------------------------------------------------------------------\n- Inputs only include species names.\n\n- One command line to build trees.\n\n- HCP and SSU rRNA methods.\n\n- Combine trees.\n\n- View trees with iTOL.\n\n- Versatile software with adjustable parameters.\n\n\nInstall\n-------------------------------------------------------------------------------\n\n1. PyPI\n\n.. code-block:: console\n\n\t$ pip install PhySpeTree\n\n\nor `download PhySpeTree `_ and install:\n\n.. code-block:: console\n\n $ pip install PhySpeTree-*.tar.gz\n\n\nTo upgrade to latest version:\n\n.. code-block:: console\n\n $ pip install --upgrade PhySpeTree\n\n2. GitHub\n\n.. code-block:: console\n\n $ git clone git@github.com:yangfangs/physpetools.git\n $ cd physpetools\n $ python setup.py install\n\nor `download `_ and install:\n\n.. code-block:: console\n\n $ pip install physpetools-*.tar.gz\n\n\n\nUsage\n-------------------------------------------------------------------------------\n\nautobuild\n^^^^^^^^^^^^^^^^^^^^\n\nThe input of `autobuild` module is a TXT file containing abbreviated species names, for example `organism example list `_.\n\nUse **autobuild** in command line like this:\n\n.. code-block:: console\n\n $ PhySpeTree -i organism_example_list.txt [options]*\n\n\nautobuild options\n#####################\n\n-h\n Print help message and exits.\n\n-i\n Input a TXT file containing abbreviated species names.\n\n-o\n A directory to store outputs. The default is \"Outdata\".\n\n-t\n Number of processing threads (CPUs). The default is 1.\n\n-e\n FASTA format files to extend the tree with the --ehcp or --esrna option.\n\n--hcp\n\n HCP (highly conserved protein) method (default).\n\n--ehcp\n\n HCP method with extended HCP sequences.\n\n--srna\n\n SSU method.\n\n--esrna\n\n SSU rRNA method with extended SSU rRNA sequences.\n\n\nAdvance options\n#####################\n\nAdvanced options of internal software called in PhySpeTree can be set. These options are ``enclosed in single quotes and start with a space``.\n\nHere is an example of setting RAxML advanced options by `--raxml_p`:\n\n.. code-block:: console\n\n $ PhySpeTree autobuild -i organism_example_list.txt -o test --srna --raxml --raxml_p ' -f a -m GTRGAMMA -p 12345 -x 12345 -# 100 -n T1'\n\n--muscle\n Multiple sequence alignment by MUSCLE (default).\n\n\n--muscle_p\n Set Muscle advance parameters. The default is ``-maxiter 100``, please see\n `MUSCLE Manual `_.\n\n -maxiter\n maximum number of iterations to run is set 100.\n\n--clustalw\n Multiple sequence alignment by clustalw2.\n\n--clustalw_p\n Set clustalw2 advance parameters. Here use clustalw default parameters,\n please see `Clustalw Help `_.\n\n--mafft\n Multiple sequence alignment by mafft.\n\n--mafft_p\n Set mafft advance parameters. Here use mafft default parameters,\n please see `mafft algorithms `_.\n\n--gblocks\n Trim by Gblocks.(default)\n\n--gblocks_p\n Set Gblocks advance parameters,\n please see `Gblocks documentation `_.\n\n -t\n Choice type of sequence(default).\n\n -e\n Generic File Extension. PhySpeTree set default is \"-gbl1\".\n\n--trimal\n Trim by trimal.\n\n--trimal_p\n Set trimal advance parameters, please see `trimal command line `_.\n\n--raxml\n Reconstruct phylogenetic tree by RAxML (default).\n\n--raxml_p\n Set RAxML advanced parameters. The default is ``-f a -m PROTGAMMAJTTX -p 12345 -x 12345 -# 100 -n T1``,\n please see `RAxML Manual `_.\n\n -f\n select algorithm. The PhySpeTree default set is ``a``, rapid Bootstrap analysis and search for best\u00adscoring ML tree in one program run.\n\n -m\n Model of Binary (Morphological), Nucleotide, Multi\u00adState, or Amino Acid Substitution. The PhySpeTree default set is PROTGAMMAJTTX.\n\n -p\n Specify a random number seed for the parsimony inferences. The physep default set is 12345.\n\n -x\n Specify an integer number (random seed) and turn on rapid bootstrapping. The PhySpeTree default set is 12345.\n\n -N\n The same with -# specify the number of alternative runs on distinct starting trees. The PhySpeTree default set is 100.\n\n\n--fasttree\n Reconstruct phylogenetic tree by FastTree.\n\n--fasttree_p\n Set FastTree advance parameters,\n please see `FastTree `_.\n\n--iqtree\n Reconstruct phylogenetic tree by iqtree.\n\n--iqtree_p\n Set iqtree advance parameters,\n please see `IQ-TREE `_.\n\nbuild\n^^^^^^^^^^^^^^^^^^^^\n\nThe `build` module is used to reconstruct species trees with manually prepared sequences. Advanced options are the same as `autobuild` module.\n\nUse **build** in command line to reconstruct phylogenetic tree:\n\n* build phylogenetic tree by multiple method:\n\n\n.. code-block:: console\n\n $ PhySpeTree build -i example_hcp -o output --multiple\n\n\n* build phylogenetic tree by SSU rRNA method:\n\n\n.. code-block:: console\n\n $ PhySpeTree build -i example_16s_ssurna.fasta -o output --single\n\nbuild options\n#####################\n\n-h\n Print help message and exits.\n\n-i\n Input a TXT file containing abbreviated species names.\n\n-o\n A directory to store outputs. The default is \"Outdata\".\n\n-t\n Number of processing threads (CPUs). The default is 1.\n\n--multiple\n\n Specify concatenate highly conserved protein method to reconstruct phylogenetic tree. The default method.\n\n--single\n\n Use SSU rRNA data to reconstruct phylogenetic tree.\n\ncombine\n^^^^^^^^^^^^^^^^^^^^\n\nThe **combine** module is used to combine trees generated from different methods. It contains two steps, at first merge different tree files into the same file. You can use `cat` bash command in the Linux system, for example:\n\n.. code-block:: console\n\n $ cat tree1.tree tree2.tree > combineTree.tree\n\n\nThen, use **combine**\n\n.. code-block:: console\n\n $ PhySpeTree PhySpeTree combine -i combineTree.tree [options]*\n\n\ncombine options\n#####################\n\n-h\n Print help message and exits.\n\n-i\n Input PHYLIP format file containing multiple trees.\n\n-o\n Output directory. The default is \"combineTree\".\n\n--mr\n Majority rule trees..\n\n--mre\n Extended majority rule trees.\n\n--strict\n Strict consensus trees.\n\n--supertree\n Use Spr_Supertree combining conflicting evolutionary histories that are due to lateral gene transfer (LGT).\n\niview\n^^^^^^^^^^^^^^^^^^^^\n\nPhySpeTree provides the `iview` module to annotate taxonomic information (kingdom, phylum, class, or order) of output trees and to generate configure files linked to `iTol `_.\n\n\nUse **iview** in command line like this:\n\n.. code-block:: console\n\n $ PhySpeTree iview -i organism_example_list.txt --range\n\n\niview options\n#####################\n\n\n-h\n Print help message and exits.\n\n-i\n Input a TXT file containing abbreviated species names.\n\n-o\n A directory to store outputs. The default is \"iview\".\n\n-r\n Annotating labels with ranges by kingdom, phylum, class or order. The default is phylum.\n\n-c\n Annotating labels without ranges by kingdom, phylum, class or order. The default is phylum.\n\n-a\n Colored ranges by users assign, users can choice from [kingdom, phylum, class and order].\n\n-l\n Change species labels from abbreviated names to full names.\n\ncheck\n^^^^^^^^^^^^^^^^^^^^\n\nThe `check` module is used to check whether input organisms are in pre-built databases.\n\n\n.. code-block:: console\n\n $ PhySpeTree check -i organism_example_list.txt -out check --ehcp\n\n\n\ncheck options\n#####################\n\n\n\n-h\n Print help message and exits.\n\n-i\n Input a TXT file containing abbreviated species names.\n\n-o\n A directory to store outputs. The default is \"check\".\n\n--hcp\n Check whether organisms are supported in the KEGG database.\n\n--ehcp\n Check input organisms prepare for extend autobuild tree module.\n\n--srna\n Check whether organisms are supported in the SILVA database.\n\n\nFrequently Asked Questions (FAQ)\n--------------------------------------------------------------------------------\n\n**1.What is the input of PhySpeTree?**\n\nUsers only need to prepare a TXT file containing `KEGG `_ abbreviated species names. For example, `organism example list `_.\n\n**2.How to explain PhySpeTree outputs?**\n\nPhySpeTree returns two folders, `Outdata` contains the output species tree and `temp` includes temporary data. Files in `temp` can be used to check the quality of outputs in each step. If HCP method (`--hcp`) is selected, the `temp` folder includes:\n\n * `conserved_protein`: highly conserved proteins retrieved from the KEGG database.\n * `alignment`: aligned sequences.\n * `concatenate`: concatenated sequences and conserved blocks.\n\nIf SSU rRNA method (`--srna`) is selected, the `temp` folder includes:\n\n * `rna_sequence`: SSU rRNA sequences retrieved from the SILVA database.\n * `rna_alignment`: aligned sequences and conserved blocks.\n\n\n**3.What classes of HCP are selected?**\n\nPhySpeTree uses 31 HCP without horizontal transferred genes according to Ciccarelli *et al.*.\n\n**cite:**\n\n Ciccarelli F D, Doerks T, Von Mering C, et al. Toward automatic reconstruction of a highly resolved tree of life[J]. science, 2006, 311(5765): 1283-1287.\n\nThe 31 HCP and corresponding KEGG KO number are shown in the following table:\n\n\n==================================================== ============== ===============\nProtein Names Eukaryotes KO Prokaryotes KO\n==================================================== ============== ===============\nDNA-directed RNA polymerase subunit alpha K03040 K03040\nRibosomal protein L1 K02865 K02863\nLeucyl-tRNA synthetase K01869 K01869\nMetal-dependent proteases with chaperone activity K01409 K01409\nPhenylalanine-tRNA synthethase alpha subunit K01889 K01889\nPredicted GTPase probable translation factor K06942 K06942\nPreprotein translocase subunit SecY K10956 K10956\nRibosomal protein L11 K02868 K02867\nRibosomal protein L13 K02873 K02871\nRibosomal protein L14 K02875 K02874\nRibosomal protein L15 K02877 K17437\nRibosomal protein L16/L10E K02866 K02872\nRibosomal protein L18 K02883 K02882\nRibosomal protein L22 K02891 K02890\nRibosomal protein L3 K02925 K02906\nRibosomal protein L5 K02932 K02931\nRibosomal protein L6P/L9E K02940 K02939\nRibosomal protein S11 K02949 K02948\nRibosomal protein S15P/S13E K02958 K02956\nRibosomal protein S17 K02962 K02961\nRibosomal protein S2 K02981 K02967\nRibosomal protein S3 K02985 K02982\nRibosomal protein S4 K02987 K02986\nRibosomal protein S5 K02989 K02988\nRibosomal protein S7 K02993 K02992\nRibosomal protein S8 K02995 K02994\nRibosomal protein S9 K02997 K02996\nSeryl-tRNA synthetase K01875 K01875\nArginyl-tRNA synthetase K01887 K01887\nDNA-directed RNA polymerase beta subunit K03043 K03043\nRibosomal protein S13 K02953 K02952\n==================================================== ============== ===============\n\n\n\n**4.How are SSU rRAN created?**\n\nThe SSU rRAN sequences are created from the `SILVA `_ database (123.1 release). Sequences haven been truncated, which means unaligned nucleotides are removed.\n\n\n**5. How do I use PhySpeTree when I can't connect to the Internet?**\n\nWhen users can't connect to the Internet. They can download the HCP or SSU rRNA database to local and reconstruct species tree.\n\n * SSU rRNA database: [database16s.tar.gz](ftp://173.255.208.244/pub/db/database16s.tar.gz)\n * HCP database: [databasehcp.tar.gz](ftp://173.255.208.244/pub/db/databasehcp.tar.gz)\n\nUse `$ tar -zxvf database16s.tar.gz` decompress the download database.\n\nUse `-db` option setting the absolute path to decompression directory.\n\n\n.. |PyPI version| image:: https://img.shields.io/pypi/v/PhySpeTree.svg?style=flat-square\n :target: https://pypi.python.org/pypi/PhySpeTree\n.. |Docs| image:: https://img.shields.io/badge/docs-latest-brightgreen.svg?style=flat-square\n :target: https://yangfangs.github.io/physpetools/\n.. |License| image:: https://img.shields.io/aur/license/yaourt.svg?maxAge=2592000\n :target: https://github.com/yangfangs/physpetools/blob/master/LICENSE.txt", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/yangfangs/physpetools", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "PhySpeTree", "package_url": "https://pypi.org/project/PhySpeTree/", "platform": "", "project_url": "https://pypi.org/project/PhySpeTree/", "project_urls": { "Homepage": "https://github.com/yangfangs/physpetools" }, "release_url": "https://pypi.org/project/PhySpeTree/0.3.8/", "requires_dist": null, "requires_python": "", "summary": "One command line auto reconstruct phylogenetic tree.", "version": "0.3.8" }, "last_serial": 5923465, "releases": { "0.2.4": [ { "comment_text": "", "digests": { "md5": "11ddd42c60bf7ccae7a01e38a8d19a40", "sha256": "9b24d8026d02c033e22fc95ab43b91819ca59c3a4dc933ccd26131e071c8f13f" }, "downloads": -1, "filename": "PhySpeTree-0.2.4.tar.gz", "has_sig": false, "md5_digest": "11ddd42c60bf7ccae7a01e38a8d19a40", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4748520, "upload_time": "2016-09-27T08:47:10", "url": "https://files.pythonhosted.org/packages/7e/24/4e67a22206888ae76bb528b4e3037124b708b4a63c4d6a0e6afb9ff456b9/PhySpeTree-0.2.4.tar.gz" } ], "0.2.5": [ { "comment_text": "", "digests": { "md5": "4624cddc6ef642c39f014a0c24e75eb7", "sha256": "12c7c1df742273d255f261f8f747591401e831f06e72324f340d1ccb55b51806" }, "downloads": -1, "filename": "PhySpeTree-0.2.5.tar.gz", "has_sig": false, "md5_digest": "4624cddc6ef642c39f014a0c24e75eb7", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4750253, "upload_time": "2016-10-28T11:51:39", "url": "https://files.pythonhosted.org/packages/f4/18/c5f0fdfc7b0833601f5081a9197cec0b01514fc0f01296ef3e63e0452ed1/PhySpeTree-0.2.5.tar.gz" } ], "0.2.6": [ { "comment_text": "", "digests": { "md5": "3d4e469751c4f2cef7c4119a4fb4583c", "sha256": "61d283ff597fea400dd6591f67309cab4bd6c33aca3e3fa497b2681bc4d79ac4" }, "downloads": -1, "filename": "PhySpeTree-0.2.6.tar.gz", "has_sig": false, "md5_digest": "3d4e469751c4f2cef7c4119a4fb4583c", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4750742, "upload_time": "2016-11-09T06:22:34", "url": "https://files.pythonhosted.org/packages/34/7a/3edc71ed036f349834c693acc3812ce89430fbdc61f3d349e0442a6f0fcf/PhySpeTree-0.2.6.tar.gz" } ], "0.2.7": [ { "comment_text": "", "digests": { "md5": "9113a510383d1be0cec878d6cfb22103", "sha256": "d24d441e06abc928b29759de7016548386d16a0a233b7df85b1b0e5542d73143" }, "downloads": -1, "filename": "PhySpeTree-0.2.7.tar.gz", "has_sig": false, "md5_digest": "9113a510383d1be0cec878d6cfb22103", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4749246, "upload_time": "2017-04-11T08:43:35", "url": "https://files.pythonhosted.org/packages/60/26/bdda6f46093cd74b190a6e05e983e30cb60ad65d40aa2b447923751a86cc/PhySpeTree-0.2.7.tar.gz" } ], "0.2.8": [ { "comment_text": "", "digests": { "md5": "45b64bb7d1ea6485066d880b2a0ae328", "sha256": "0bce2590611d0e576074b70a0ea8b94f4842ebfd2579dc9100d12d3a02674e0b" }, "downloads": -1, "filename": "PhySpeTree-0.2.8.tar.gz", "has_sig": false, "md5_digest": "45b64bb7d1ea6485066d880b2a0ae328", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4821431, "upload_time": "2017-08-15T11:07:42", "url": "https://files.pythonhosted.org/packages/8e/d3/9c6ddadd4f8930f95e7e321ae18944b3f1281c400cce9a5b24183bf777f6/PhySpeTree-0.2.8.tar.gz" } ], "0.2.9": [ { "comment_text": "", "digests": { "md5": "b39d3912118ec39b4e6f0f097fbd6b0d", "sha256": "2563fef1cb2b74a78c97564ff7af2e25f5024145ff31efa71a113508386d2591" }, "downloads": -1, "filename": "PhySpeTree-0.2.9.tar.gz", "has_sig": false, "md5_digest": "b39d3912118ec39b4e6f0f097fbd6b0d", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4821702, "upload_time": "2017-08-16T11:57:40", "url": "https://files.pythonhosted.org/packages/ba/64/467fc9c42f62ca6123851c2d36cf6d7e9e09f16ce568822df0d593e63dc1/PhySpeTree-0.2.9.tar.gz" } ], "0.3.0": [ { "comment_text": "", "digests": { "md5": "90607b84dc6001aa52e4a6a49a20d523", "sha256": "d6544145bd1c95d0babb95c05e05978a2176cf2323f4433639bdbab0d249fb5b" }, "downloads": -1, "filename": "PhySpeTree-0.3.0.tar.gz", "has_sig": false, "md5_digest": "90607b84dc6001aa52e4a6a49a20d523", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4821700, "upload_time": "2018-01-13T09:24:41", "url": "https://files.pythonhosted.org/packages/ff/49/11d7e3d4d573d640531e6becfe676574c71faa65d64f8ebf5596fa0dabd1/PhySpeTree-0.3.0.tar.gz" } ], "0.3.1": [ { "comment_text": "", "digests": { "md5": "a1f3b9aa1a8121c89e81f9b4abb8ec75", "sha256": "baa0b918108ef33f6c785c8d7aec3292d3063433bc666867afa89cc7eddc8d7d" }, "downloads": -1, "filename": "PhySpeTree-0.3.1.tar.gz", "has_sig": false, "md5_digest": "a1f3b9aa1a8121c89e81f9b4abb8ec75", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4821763, "upload_time": "2018-03-07T05:36:34", "url": "https://files.pythonhosted.org/packages/8d/8a/1d99d03dc7ac7a3debc9d6bcbcc450529c5f73eb9f68dbdb9fd33dc30415/PhySpeTree-0.3.1.tar.gz" } ], "0.3.2": [ { "comment_text": "", "digests": { "md5": "7bf293b958c49c4f2fcb9e900b632a94", "sha256": "ce845a23c9b9faef2941bf4770ed899b5310057fef97549021aa50c6ce0f9a69" }, "downloads": -1, "filename": "PhySpeTree-0.3.2.tar.gz", "has_sig": false, "md5_digest": "7bf293b958c49c4f2fcb9e900b632a94", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4821761, "upload_time": "2018-06-22T09:31:44", "url": "https://files.pythonhosted.org/packages/16/71/b7e36ea1d5c96844e2dd4e97b6a71b94e5c6944a9fe3895a5244b92cf407/PhySpeTree-0.3.2.tar.gz" } ], "0.3.3": [ { "comment_text": "", "digests": { "md5": "b9607d59207454fbdfd9af85df32600f", "sha256": "7043cbcc847307ff9680d84de9ec9210619c99fa0a242f2760db443ef92264b6" }, "downloads": -1, "filename": "PhySpeTree-0.3.3.tar.gz", "has_sig": false, "md5_digest": "b9607d59207454fbdfd9af85df32600f", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4825274, "upload_time": "2018-08-02T10:13:52", "url": "https://files.pythonhosted.org/packages/5c/71/fd5604d43007b2e8ea11ffceb6032e655a3319897c0f970856a6e47d9ff6/PhySpeTree-0.3.3.tar.gz" } ], "0.3.4": [ { "comment_text": "", "digests": { "md5": "29aad0b8575238b17e3d8d30a9e31133", "sha256": "265f5696ac0dc53f045491554f9431ca7334ee17aab5fd6a52afd49169a60f6d" }, "downloads": -1, "filename": "PhySpeTree-0.3.4.tar.gz", "has_sig": false, "md5_digest": "29aad0b8575238b17e3d8d30a9e31133", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 8216505, "upload_time": "2018-11-19T07:43:48", "url": "https://files.pythonhosted.org/packages/7a/e2/1968ab975d1e1319764db8689ffcb6770ac8aa71465e1c19c9b4c4ae1863/PhySpeTree-0.3.4.tar.gz" } ], "0.3.5": [ { "comment_text": "", "digests": { "md5": "39bc39c8c19c9b7fb2fac325b22009c3", "sha256": "e6fcf2597d3ea1bcbdc31b5ddd49603b3059453d77dc56fd50a6304384d17dbd" }, "downloads": -1, "filename": "PhySpeTree-0.3.5.tar.gz", "has_sig": false, "md5_digest": "39bc39c8c19c9b7fb2fac325b22009c3", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11603658, "upload_time": "2019-01-10T13:27:21", "url": "https://files.pythonhosted.org/packages/9f/10/435310ffdae4a73dcd3b808266b5941690751041e335ea3d2e315eb00e28/PhySpeTree-0.3.5.tar.gz" } ], "0.3.6": [ { "comment_text": "", "digests": { "md5": "cce547fa32979f682f5340581efef1a5", "sha256": "4f778331c71a09865733849ab96dec1fb07a17021d7e4e520010402e15e38536" }, "downloads": -1, "filename": "PhySpeTree-0.3.6.tar.gz", "has_sig": false, "md5_digest": "cce547fa32979f682f5340581efef1a5", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11655343, "upload_time": "2019-06-03T02:54:57", "url": "https://files.pythonhosted.org/packages/6d/65/2b4e52e5815bec551ae06c0b3718d49d844b9bf71a4c1ff917dc9a0a9a6c/PhySpeTree-0.3.6.tar.gz" } ], "0.3.7": [ { "comment_text": "", "digests": { "md5": "a80b48ad6b4103b80bedda6324fea7a5", "sha256": "a7ed6f96076133e30f57145e16ed73bd6f86161c58ed861f1e99951affd93d7f" }, "downloads": -1, "filename": "PhySpeTree-0.3.7.tar.gz", "has_sig": false, "md5_digest": "a80b48ad6b4103b80bedda6324fea7a5", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 13488740, "upload_time": "2019-10-02T08:10:49", "url": "https://files.pythonhosted.org/packages/45/90/6593183a0cfdd4c899b4ea23ede791e3cdead100b34760f82d9ee4a18cc6/PhySpeTree-0.3.7.tar.gz" } ], "0.3.8": [ { "comment_text": "", "digests": { "md5": "0c5a74f7416694410facf6e76c3f8b13", "sha256": "57b033136030d7fadbccd1d7e437f6d491dff1b78fccbb4ccf0824e0c7ee472a" }, "downloads": -1, "filename": "PhySpeTree-0.3.8.tar.gz", "has_sig": false, "md5_digest": "0c5a74f7416694410facf6e76c3f8b13", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 13448619, "upload_time": "2019-10-03T13:29:26", "url": "https://files.pythonhosted.org/packages/fa/64/54a83cdb2fb615e639bb29b0dd93fd428836af7de2d64b6bdf21deaef525/PhySpeTree-0.3.8.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "0c5a74f7416694410facf6e76c3f8b13", "sha256": "57b033136030d7fadbccd1d7e437f6d491dff1b78fccbb4ccf0824e0c7ee472a" }, "downloads": -1, "filename": "PhySpeTree-0.3.8.tar.gz", "has_sig": false, "md5_digest": "0c5a74f7416694410facf6e76c3f8b13", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 13448619, "upload_time": "2019-10-03T13:29:26", "url": "https://files.pythonhosted.org/packages/fa/64/54a83cdb2fb615e639bb29b0dd93fd428836af7de2d64b6bdf21deaef525/PhySpeTree-0.3.8.tar.gz" } ] }