Saravanan666/pypi-org huggingface dataset:
Package: pyseq
PySeq is a python module that finds groups of items that follow a naming convention containing
a numerical sequence index (e.g. fileA.001.png, fileA.002.png, fileA.003.png…) and serializes
them into a compressed sequence string representing the entire sequence (e.g. fileA.1-3.png). It
should work regardless of where the numerical sequence index is embedded in the name. For examples,
see basic usage below orhttp://rsgalloway.github.io/pyseqInstallationInstallation using setuputils:% pip install pyseqBasic UsageUsing the “z1” file sequence example in the “tests” directory, we start by listing the directory
contents usingls.$ ls tests/files/z1*
tests/files/z1_001_v1.1.png tests/files/z1_002_v1.3.png
tests/files/z1_001_v1.2.png tests/files/z1_002_v1.4.png
tests/files/z1_001_v1.3.png tests/files/z1_002_v2.1.png
tests/files/z1_001_v1.4.png tests/files/z1_002_v2.2.png
tests/files/z1_002_v1.1.png tests/files/z1_002_v2.3.png
tests/files/z1_002_v1.2.png tests/files/z1_002_v2.4.pngNow we list the same directory contents usinglss, which will find the sequences and display them
in the default compressed format.$ lss tests/files/z1*
   4 z1_001_v1.%d.png [1-4]
   4 z1_002_v1.%d.png [1-4]
   4 z1_002_v2.%d.png [1-4]… with a custom format:$ lss tests/files/z1* -f "%h%r%t"
z1_001_v1.1-4.png
z1_002_v1.1-4.png
z1_002_v2.1-4.png… recursive:$ lss -r tests
tests
├── test_pyseq.py
└── files
    ├── 012_vb_110_v001.1-10.png
    └── 012_vb_110_v002.1-10.pngAPI ExamplesCompression, or serialization, of lists of items>>> s = Sequence(['file.0001.jpg', 'file.0002.jpg', 'file.0003.jpg'])
>>> print(s)
file.1-3.jpg
>>> s.append('file.0006.jpg')
>>> print(s.format("%h%p%t %R"))
file.%04d.jpg [1-3, 6]Uncompression, or deserialization, of compressed sequences strings>>> s = uncompress('./tests/012_vb_110_v001.%04d.png 1-1001', fmt='%h%p%t %r')
>>> len(s)
1001
>>> print(s.format('%04l %h%p%t %R'))
1001 012_vb_110_v001.%04d.png [1-1001]
Package: pyseq-align
pyseq-alignPython interface for theseq-alignC library, written by Isaac Turner (@noporpoise).Installationpip install pyseq-alignTo install directly from GitHub,git clone https://github.com/Lioscro/pyseq-align.git --recursive
cd pyseq-align
pip install .UsageTwo alignment algorithms are provided: Needleman-Wunsch and Smith-Waterman.frompyseq_alignimportNeedlemanWunschnw=NeedlemanWunsch()al=nw.align('ACGT','ACGTC')print(al.result_a)# ACGT-print(al.result_b)# ACGTCprint(al.score)frompyseq_alignimportSmithWatermansw=SmithWaterman()als=sw.align('ACGT','ACGTC')# unlike above, this is a list of Alignment'sforalinals:print(al.result_a,al.pos_a)# ACGT, 0print(al.result_b,al.pos_b)# ACGT, 0print(al.score)
Package: pyseqfile
# pyseqfilePyseqfile is a python wrapper on top of [seq_file](https://github.com/noporpoise/seq_file) which allow for reading multiple sequence file formats.Currently supports:FASTA & FASTQTO DO:* SAM & BAM (make seq_file with htslib)* gzipped FASTA* gzipped FASTQ# Installpip install pyseqfile# Usagefrom pyseqfile import Readerreader = Reader('path/to/seqfile{.fq,.fq,.fa,bam,.sam}')for r in reader:print(r)# Benchmarkspyseqfile is *much* faster than Biopython.$ python benchmark.pyReading 10k lines 100 times: Biopython : 6.6768401420122245sReading 10k lines 100 times: seqfile : 0.1060560290061403s
Package: pyseqlib
A small python library to process sequencing data. It is under active development.What’s inside?intronX: a program to fetch sequence related features for introns:
1) length, 2) splice site motif strength, 3) second structure energy
4) frequecy of k-mers. Seemanualandexample.pymfold: a python wrap of mfold for calculate energy of RNA secondary
structure. We got installation issue from mfold, similar asthis. Therefore,
we recommend usingpyRNAfoldinstead.pyRNAfold: a python wrap of for another predictor, RNAfold, of RNA
secondary structure energy. It is from theViennaRNApackage, which can be
installed from thesource code, or fromBioConda.motif-score: a motif score calculatea sequence mapper to find lariat in RNA-seq reads (under test)a sam file resampling methodHow to install?Pyseqlib was initially developed in Python 2 environment, hence best to be used
in Py2 environment. By using Anaconda platform, no matter Py2 or Py 3, it is
easy to set up a conda environment with Py2, for example by following commond:condacreate-nPy2python=2.7numpy==1.15.4pysam==0.15.2Cython==0.29.3matplotlib==2.2.3sourceactivatePy2Once you are in a Python 2 environment, you can download the codes from this
github repository and then run the following command line:python setup.py installOrpip install -U git+https://github.com/huangyh09/pyseqlibIf you don’t have the root permission, add--user.Rquired libraries:pysam,numpy,Cython.
Package: pyseqlsa
LSA(lag sequential analysis)滞后序列分析python版安装pip install pyseqlsa或者pip3 install pyseqlsa快速使用from pyseqlsa import LSA
data = [['A', 'B', 'C', 'B', 'C', 'B', 'C'],
        ['C', 'C', 'B', 'A', 'C', 'A', 'B', 'C', 'B', 'C']]

lsa = LSA(['A', 'B', 'C'])
lsa.fit(data)若不想打印输出，可以设置output=Falselsa.fit(data,output=False)单独查看Z矩阵的方法# 属性Z即是残差显著性的矩阵，大于1.96即显著
lsa.Z如果想转换Gseq5为sds文件，可以调用lsa.to_sds(data, "filename.sds")通过csv获得seqs，并进行滞后序列分析注意此处默认csv的格式，第一列为序列的id，第二列为code，标题名可以随意，从第二行开始读取，如下所示idcode1a1b1a2a2b2c读取后的数据即可直接用于LSA代码如下所示from pyseqlsa import read_seqs_from_csv
from pyseqlsa import LSA

data = read_seqs_from_csv('test.csv')
lsa = LSA(['A', 'B', 'C'])
lsa.fit(data)通过excel获得seqs，并进行滞后序列分析excel 请按照以下的格式设置，第一列为序列的id，第二列为code，标题名可以随意，从第二行开始读取，如下所示idcode1a1b1a2a2b2c读取后的数据即可直接用于LSA代码如下所示from pyseqlsa import read_seqs_from_excel
from pyseqlsa import LSA

data = read_seqs_from_excel('test.xlsx')
lsa = LSA(['a', 'b', 'c'])
lsa.fit(data)
Package: pySeqRNA
pyseqrnapySeqRNA: a python-based package for RNASeq data analysisInstallationDownload the installer:Miniconda installer for Linux.conda env create -f pyseqrna_environment.ymlconda activate pyseqrna_0.0.2pip install .Run pyseqrnapyseqrna -hPlease CiteDuhan N and Kaundal R. pySeqRNA: an automated Python package for RNA sequencing data analysis [version 1; not peer reviewed]. F1000Research 2020, 9(ISCB Comm J):1128 (poster) (https://doi.org/10.7490/f1000research.1118314.1)ContactWritten by Naveen Duhan (naveen.duhan@usu.edu),
Kaundal Bioinformatics Lab, Utah State University,
Released under the terms of GNU General Public Licence v3
Package: pysequila
pysequilapysequila is a Python entrypoint to SeQuiLa, an ANSI-SQL compliant solution for efficient sequencing reads processing and genomic intervals querying built on top of Apache Spark. Range joins, depth of coverage and pileup computations are bread and butter for NGS analysis but the high volume of data make them execute very slowly or even failing to compute.RequirementsPython 3.7, 3.8, 3.9Featurescustom data sources for bioinformatics file formats (BAM, CRAM, VCF)depth of coverage calculationspileup calculationsreads filteringefficient range joinsother utility functionssupport for both SQL and Dataframe/Dataset APISetup$ python -m pip install --user pysequila
or
(venv)$ python -m pip install pysequilaUsage$ python
>>> from pysequila import SequilaSession
>>> ss = SequilaSession \
  .builder \
  .config("spark.jars.packages", "org.biodatageeks:sequila_2.12:1.1.0") \
  .config("spark.driver.memory", "2g") \
  .getOrCreate()
>>> ss.sql(
      f"""
      CREATE TABLE IF NOT EXISTS reads
      USING org.biodatageeks.sequila.datasources.BAM.BAMDataSource
      OPTIONS(path "/features/data/NA12878.multichrom.md.bam")
      """
>>> ss.sql ("SELECT * FROM  coverage('reads', 'NA12878','/features/data/Homo_sapiens_assembly18_chr1_chrM.small.fasta")
>>> # or using DataFrame/DataSet API
>>> ss.coverage("/features/data/NA12878.multichrom.md.bam", "/features/data/Homo_sapiens_assembly18_chr1_chrM.small.fasta")ChangeLog0.1.0 (2020-09-16)Initial release.
Package: pyser
PySer(fulldocumentation) is a library for serializing and deserializing data in different data formats through intuitive mappings in defined inside a Python class.Current formats supported are JSON and config files, with more coming later on.ExamplesClass mappings for serializing and deserializing in JSONfrompyserimportSchemaJSON,SerField,DeserFieldclassFruitBasketSchema(SchemaJSON):def__init__(self):self.name=DeserField()self.fruit=DeserField()self.iD=DeserField(name='ref',kind=int)self.intString=DeserField(kind=int)self.optionalString=DeserField(kind=str,optional=True)self.items=DeserField(repeated=True)self.name=SerField()self.fruit=SerField()self.iD=SerField(name='ref',kind=int)self.intString=SerField(kind=int)self.optionalString=SerField(optional=True)self.items=SerField(repeated=True)self.register=SerField(parent_keys=['checkout'],kind=int)self.amount=SerField(parent_keys=['checkout'],kind=int)fruit_basket_schema=FruitBasketSchema()classFruitBasket():def__init__(self):self.name='basket'self.fruit='banana'self.iD='123'self.intString='12345'self.optionalString=Noneself.items=['paper','rock']self.register='1'self.amount='10'Serializing to a JSON filebasket=FruitBasket()fruit_basket_schema.to_json(basket,filename="basket.json")File contents of basket.json after serializing:{"name":"basket","fruit":"banana","ref":123,"intString":12345,"items":["paper","rock"],"checkout":{"register":1,"amount":10}}Similarly deserialization from a json file:basket=FruitBasket()fruit_basket_schema.from_json(basket,raw_json=raw_json)InstallationInstallation by hand:you can download the source files from PyPi or Github:pythonsetup.pyinstallInstallation with pip:make sure that you havepipinstalled, type this in a terminal:pipinstallpyserDocumentationRunningbuild_docshas additional dependencies that require installation.pipinstallpyser[docs]The documentation can be generated and viewed via:$pythonsetup.pybuild_docsYou can pass additional arguments to the documentation build, such as clean build:$pythonsetup.pybuild_docs-EMore information is available from theSphinxdocumentation.Running TestsRun the python commandpythonsetup.pytestContributeFork the repository from GithubClone your forkgitclonehttps://github.com/yourname/pyser.gitAdd the main repository as a remotegitremoteaddupstreamhttps://github.com/jonnekaunisto/pyser.gitCreate a pull request and follow the guidelinesMaintainersjonnekaunisto(owner)
Package: pyserato
pyseratoProgramatically create crates in Serato.Example use using the DEFAULT_SERATO_FOLDER.
This can be overwritten to a non default location by passing the desired root in to thebuilder.save()API.frompathlibimportPathfrompyserato.crateimportDEFAULT_SERATO_FOLDER,Crate,Builderdeflist_crates_sync(serato_folder:Path=DEFAULT_SERATO_FOLDER)->list[Crate]:all_crates=[]subcrates_folder=serato_folder/"SubCrates"crates=[Crate(name.stem)fornameinsubcrates_folder.glob("*.crate")]all_crates.extend(crates)returnall_cratesif__name__=='__main__':crates=list_crates_sync()print(crates)child_crate3=Crate('child3')child_crate3.add_song("/Users/lukepurnell/nav_music/Laker/Noise From The Ruliad/00 Cloud Formation.mp3")child_crate=Crate('child1',children=[child_crate3])child_crate.add_song("/Users/lukepurnell/nav_music/Russian Circles/Gnosis/01 Tupilak.wav")child_crate2=Crate('child2')child_crate2.add_song("/Users/lukepurnell/nav_music/Laker/Noise From The Ruliad/00 Entropy Increasing.mp3")child_crate.add_song("/Users/lukepurnell/nav_music/Laker/Noise From The Ruliad/00 Cloud Formation.mp3")root_crate=Crate('root',children=[child_crate,child_crate2])builder=Builder()builder.save(root_crate)
Package: pysercomb
pysercombpython parser combinator and parsersUnitsThe most useful thing in this repo is probably the units parser which
has been tuned to extract scientific units from the published literature.protc dependencyIf you want to use units parser you will need to have a copy of theprotc repoand have the repo version protcur installed. See.travis.ymlfor details.
The units parser and protc are still tightly coupled for the time being.
Package: pyserde
pyserdeYet another serialization library on top ofdataclasses, inspired byserde-rs.Guide|API Docs|ExamplesOverviewDeclare a class with pyserde's@serdedecorator.@serde@dataclassclassFoo:i:ints:strf:floatb:boolYou can serializeFooobject into JSON.>>>to_json(Foo(i=10,s='foo',f=100.0,b=True))'{"i":10,"s":"foo","f":100.0,"b":true}'You can deserialize JSON intoFooobject.>>>from_json(Foo,'{"i": 10, "s": "foo", "f": 100.0, "b": true}')Foo(i=10,s='foo',f=100.0,b=True)FeaturesSupported data formatsdicttupleJSONYamlTomlMsgPackPickleSupported typesPrimitives (int,float,str,bool)ContainersList,Set,Tuple,DictFrozenSet,DefaultDicttyping.Optionaltyping.UnionUser defined class with@dataclasstyping.NewTypefor primitive typestyping.Anytyping.Literaltyping.Generictyping.ClassVardataclasses.InitVarEnumandIntEnumStandard librarypathlib.Pathdecimal.Decimaluuid.UUIDdatetime.date,datetime.time,datetime.datetimeipaddressPyPI librarynumpytypesClass AttributesField AttributesDecoratorsType CheckUnion RepresentationForward referencePEP563 Postponed Evaluation of AnnotationsPEP585 Type Hinting Generics In Standard CollectionsPEP604 Allow writing union types as X | YPEP681 Data Class TransformCase ConversionRenameAliasSkip (de)serialization (skip,skip_if,skip_if_false,skip_if_default)Custom field (de)serializerCustom class (de)serializerCustom global (de)serializerFlattenExtensionspyserde-timedelta: (de)serializing datetime.timedelta in ISO 8601 duration format.Contributors ✨Thanks goes to these wonderful people (emoji key):yukinarit💻Alexander Miskaryan💻ydylla💻Kevin Squire💻📖Yushi OMOTE💻Yuji Kanagawa💻Weiliang Li💻Mauve💻adsharma💻Guilhem C.📖Pierre Tardy💻Raphael Nestler📖Pranav V P💻andreymal💻Johann Fuechsl💻DoeringChristian💻Stuart Axelbrooke💻Jakub Beránek💻Fredrik Reinholdsen💻Bruno Oliveira📖Kyle Kosic💻Gajo Petrovic📖m472💻acolley-gel💻Marc-André Allaire💻Ganden Schaffner💻Dave Tapley💻Add your contributionsThis project follows theall-contributorsspecification. Contributions of any kind welcome!LICENSEThis project is licensed under theMIT license.
Package: pyserde-timedelta
pyserdeextension fordatetime.timedelta.importserde_timedeltafromserdeimportserdefromserde.jsonimportto_json,from_jsonfromdatetimeimporttimedelta# Initialize serde_timedelta extension.serde_timedelta.init()@serdeclassFoo:a:timedeltaf=Foo(timedelta(hours=10))json=to_json(f)print(json)# Prints {"a":"PT10H"}print(from_json(Foo,json))# Prints Foo(a=datetime.timedelta(seconds=36000))
Package: pyseri
frompyseriimportserializerclassA():name='class a'classB():name='class b'a=[A(),A(),A()]serializer.dump(B(),mapper={'A':{'name'},'B':{'name','a'}})#output"""{'name': 'class b','a': [{'name': 'class a'},{'name': 'class a'},{'name': 'class a'}]}"""frompyseriimportserializerclassA():getters=['name']#this key is importantname='class a'classB():getters=['name','a']#this key is importantname='class b'a=[A(),A(),A()]serializer.dump(B())#output"""{'a': [{'name': 'class a'},{'name': 'class a'},{'name': 'class a'}],'name': 'class b'}"""
Package: pyserial
Python Serial Port Extension for Win32, OSX, Linux, BSD, Jython, IronPythonStable:Documentation:http://pythonhosted.org/pyserial/Download Page:https://pypi.python.org/pypi/pyserialLatest:Documentation:http://pyserial.readthedocs.io/en/latest/Project Homepage:https://github.com/pyserial/pyserial
Package: pySerialForAt
pySerialForAt介绍串口软件架构软件架构说明安装教程xxxxxxxxxxxx使用说明pip install pySerialForAtxxxxxxxx参与贡献Fork 本仓库新建 Feat_xxx 分支提交代码新建 Pull Request特技使用 Readme_XXX.md 来支持不同的语言，例如 Readme_en.md, Readme_zh.mdGitee 官方博客blog.gitee.com你可以https://gitee.com/explore这个地址来了解 Gitee 上的优秀开源项目GVP全称是 Gitee 最有价值开源项目，是综合评定出的优秀开源项目Gitee 官方提供的使用手册https://gitee.com/helpGitee 封面人物是一档用来展示 Gitee 会员风采的栏目https://gitee.com/gitee-stars/
Package: py-serializable
py-serializableThis Pythonic library provides a framework for serializing/deserializing Python classes to and from JSON and XML.It relies upon the use ofPython Propertiesin your Python
classes.Read the fulldocumentationfor more details.InstallationInstall this fromPyPi.orgusing your preferred Python package manager.Example usingpip:pipinstallpy-serializableExample usingpoetry:poetryaddpy-serializableUsageSee the fulldocumentationor ourunit testsfor usage and details.Python SupportWe endeavour to support all functionality for allcurrent actively supported Python versions.
However, some features may not be possible/present in older Python versions due to their lack of support.ContributingFeel free to open issues, bugreports or pull requests.See theCONTRIBUTINGfile for details.Copyright & Licensepy-serializableis Copyright (c) Paul Horton 2022. All Rights Reserved.Permission to modify and redistribute is granted under the terms of the Apache 2.0 license.See theLICENSEfile for the full license.
Package: py-serializer
SerializerA serialization module for python objectsQuickstartpip install py-serializerfromtypingimportListfromserializerimportserializable@serializableclassRole:role_type:strattributes:List[str]@serializableclassPerson:name:strage:intheight:floatweight:floataddress:strrole:List[Role]p=Person(name="Paul",age=25,height=1.70,weight=83.5,address="earth",role=[Role(role_type='human',attributes=['speak','eat','sleep'])])print(p.to_dict()){
    'name': 'Paul', 
    'age': 25, 
    'height': 1.7,
    'weight': 83.5, 
    'address': 'earth', 
    'role': [
          {
            'role_type': 'human',
            'attributes': ['speak', 'eat', 'sleep']
          }
    ]
}Serializable wrapper extendsdataclassso you can treat it like a normal dataclass.MixinIt is possible to have a class extend abstract class SerializableMixinfromserializerimportSerializableMixin,serializerclassTest(SerializableMixin):def__init__(self,name:str):self.name=namedef__serialize__(self):returndict(name=serializer(self.name))>> Test(name='Paul').to_dict(){ 'name': 'Paul' }For object to be seriazable they only need to implement a__serialize__method.
Package: pyserial-labgrid
OverviewThis module encapsulates the access for the serial port. It provides backends
forPythonrunning on Windows, OSX, Linux, BSD (possibly any POSIX compliant
system) and IronPython. The module named “serial” automatically selects the
appropriate backend.This fork integrates RFC2217 relevant fixes which haven’t been accepted
upstream. We used to install from git, but newer pip enforces that all packages
installed from pypi also have all dependencies on pypi. Therefore this is now a
proper fork which:converts to pyproject.tomlintegrates rfc2217 fixeswill be available as pyserial-labgrid on pypiProject Homepage:https://github.com/pyserial/pyserial-labgridDownload Page:https://pypi.python.org/pypi/pyserial-labgridBSD license, (C) 2001-2020 Chris Liechti <cliechti@gmx.net>
BSD license, (C) 2023-2023 Rouven Czerwinski <entwicklung@pengutronix.de>DocumentationFor API documentation, usage and examples see files in the “documentation”
directory.  The “.rst” files can be read in any text editor or being converted to
HTML or PDF usingSphinx. An HTML version is online athttps://pythonhosted.org/pyserial/ExamplesExamples and unit tests are in the directoryexamples.Installationpip install pyserialshould work for most users.Detailed information can be found indocumentation/pyserial.rst.The usual setup.py forPythonlibraries is used for the source distribution.
Windows installers are also available (see download link above).orTo install this package with conda run:conda install-cconda-forgepyserialconda builds are available for linux, mac and windows.
Package: py-serial-rs
The goal of this package is to provide a fast and reliable interface to the serial ports.Instead of implementing the logic in Python, this package builds aroundserialportwritten in Rust. This package supports threading.InstallationPyO3(with maturin) will build a pip package for you. For this, make
sure that you are able to build rust packages withcargo. Create a virtual environment
and install the required pip packages withpipinstall-rrequirements.txtThe pip package can then easily be build withmaturinbuild--releaseVoilà, a pip package to be used in your code!Demo ScriptsDemo scripts are located in/python:demo.pyshows a simple direct communication via the serial connectiondemo_threads.pydemonstrates how this package can be used with threadsDocumentationLink to the documentation:https://py-serial-rs.readthedocs.io/
Package: pyserialui
PySerialUISupport and examples for Python SerialUI callbacks, overrides and functionality.SerialUI, Device Druid and BuilderSerialUI provides a user-defined set of menus, commands, inputs, tracked states and data views through a serial channel (e.g. USB or bluetooth LE serial), for embedded and Linux devices (Arduino, Raspberry Pi, etc).It also includes a programatic API to allow clients, such asdevice druid, to create and manage the SerialUI menu items while providing any desirable interface such as a GUI.TheDevice Druid Builderis the easiest way to define the SerialUI menu structure and will generate projects that use the SerialUI library and implement your layout.PythonOn embedded devices, functionality is implemented by fleshing out the various callbacks in C++.On Linux hosts, such asRaspberry PiorUbuntu, Python may be used instead thanks to the built-in CPython support and (optionally) this library.Copyright and LicensePySerialUI is
Copyright (C) 2019 Pat Deegan,psychogenic.comand is released under the terms of the LGPLv3.  See the LICENSE file for details.More information is available through thedevice druidandinductive-kickbackwebsites.
Package: pyserini-indexer
pyserini-indexerHelper application for building index files that uses pyseriniPrerequisitespython 3.9 (pytorch + faiss are only working under this version unfortunaly ☹️ )if you would want to create/search using learnable
Sparse indexes (UNICOIL), you would need CUDA support (pyserini requires here CUDA for backend 😞)Indexing methods:Sparse:BM25 - traditional not-learnable indexing techniqueUNICOIL - uses LuceneImpact underneathDense:MINILM_V2 - smallest model availableANCETCT_COLBERT - biggest (0.5 gb) and provides best resultsBackend supportBy defaultallindexing methods use CPU. If you would want to change this behaviour, set environment variableUSE_GPUto some value.Example usageCreate BM25 sparse index directorypythonpyserini-indexerBM25index_input-otests/indexes/bm25Create dense index directorypythonpyserini-indexerMINILM_V2index_input-otests/indexes/minilm_v2