Saravanan666/pypi-org huggingface dataset:
Package: lgl
## lgl - python packaging manager launcherlibgirl launcher is a packaging manager to create python project## Installation```pip install lgl```## Features* Create project directory.* Find lacking packge and install after analyze source code.* manage `import` forms for the package.* Launch application.## Usage```$ lglusage: lgl [-h] {run,install,fmt,init} ...positional arguments:{run,install,fmt,init}run                 see `run -h`install             see `install -h`fmt                 see `fmt -h`init                see `init -h`optional arguments:-h, --help            show this help message and exit```$ lgl init project-name # create project directory$ lgl install           # install depending libraries.$ lgl fmt               # manage `import` forms$ lgl run [arguments]   # launch application## AuthorTeam Libgirl(team@libgirl.com)## LicenseLicensed under the Apache License 2.0 License.
Package: lgl-get-ena-metafile
本代码主要通过构筑检索式无头浏览下载ENA数据库中高通量测序数据的元数据安装通过以下代码pipinstalllgl_get_ena_metafile使用需要依次传入3个参数，分别为input_list_txt：数据文件所在路径download_path：文件下载路径chromedriver ：谷歌浏览器驱动程序绝对路径通过以下代码使用：fromlgl_get_ena_metafileimportget_ena_metafiledownload_path=r"C:\Users\Huawei\Desktop\test"##定义下载地址input_list_txt=r'C:\Users\Huawei\Desktop\test_sra.txt'##定义输入文件路径chromedriver=r"C:\Program Files (x86)\Google\Chrome\Application\chromedriver.exe"##定义浏览器驱动地址get_ena_metafile(input_list_txt,download_path,chromedriver)
Package: lg-linter
LG-LinterA simple pre-commit linter for bash, python and c++.InstallationMake sure you havepip3,clang-formatandshellcheckinstalled. If not you can install them withsudoaptupdate
sudoaptinstall-ypython3-pipclang-formatshellcheckNext install the linter withpip3installlg-linterNote:This will install / overwrite the linter config files in your home directory.How to useInside your git repo runinit_lg_linterThe linter is now active and will be run before every commit.
If you want to remove the linter from your repo usedeinit_lg_linterPro Tip:If the linter complains about stuff which clearly is wrong you can override him withgit commit --no-verifyUse with care, with great power comes great responsibility!ContactFor feature requests or bug reports please drop an issue athttps://github.com/lgulich/lg-linter.
Package: lgloria-mysqltosqlite3
MySQL to SQLite3A simple Python tool to transfer data from MySQL to SQLite 3.This is the long overdue complimentary tool to mySQLite3 to MySQL. It
transfers all data from a MySQL database to a SQLite3 database.How to runpipinstallmysql-to-sqlite3
mysql2sqlite--helpUsageUsage: mysql2sqlite [OPTIONS]

  Transfer MySQL to SQLite using the provided CLI options.

Options:
  -f, --sqlite-file PATH          SQLite3 database file  [required]
  -d, --mysql-database TEXT       MySQL database name  [required]
  -u, --mysql-user TEXT           MySQL user  [required]
  -p, --prompt-mysql-password     Prompt for MySQL password
  --mysql-password TEXT           MySQL password
  -t, --mysql-tables TEXT         Transfer only these specific tables (space
                                  separated table names). Implies --without-
                                  foreign-keys which inhibits the transfer of
                                  foreign keys.

  -L, --limit-rows INTEGER        Transfer only a limited number of rows from
                                  each table.

  -C, --collation [BINARY|NOCASE|RTRIM]
                                  Create datatypes of TEXT affinity using a
                                  specified collation sequence.  [default:
                                  BINARY]

  -K, --prefix-indices            Prefix indices with their corresponding
                                  tables. This ensures that their names remain
                                  unique across the SQLite database.

  -X, --without-foreign-keys      Do not transfer foreign keys.
  -h, --mysql-host TEXT           MySQL host. Defaults to localhost.
  -P, --mysql-port INTEGER        MySQL port. Defaults to 3306.
  -S, --skip-ssl                  Disable MySQL connection encryption.
  -c, --chunk INTEGER             Chunk reading/writing SQL records
  -l, --log-file PATH             Log file
  -V, --vacuum                    Use the VACUUM command to rebuild the SQLite
                                  database file, repacking it into a minimal
                                  amount of disk space

  --use-buffered-cursors          Use MySQLCursorBuffered for reading the
                                  MySQL database. This can be useful in
                                  situations where multiple queries, with
                                  small result sets, need to be combined or
                                  computed with each other.

  -q, --quiet                     Quiet. Display only errors.
  --version                       Show the version and exit.
  --help                          Show this message and exit.
Package: lgm
lgmLGM is a lightweight python3 library for natural LanGuage Modeling (LGM), useful for deep learning and reinforcement learning experiments with natural language data.Originally, the code was based partly on code from the fastai course v3, dl2 (March-April 2019), and partly on code from the University of Alberta Reinforcement Learning specialization (Coursera, fall 2019).To install:pip3 install lgm
Package: lgpdXml
lgpdXml1 - pip Installpip install lgpdXml2 - example find value of tag#library
from lgpdXml import find, replace

#text
xml = '''<CNPJ>012.345.678/0001-01</CNPJ>
<NOMERAZAO>CLAUDIO TORRES ARBE</NOMERAZAO>
<CNPJ>001.001.001/0001-01</CNPJ>'''

#find using tag
nome = find(xml,'<NOMERAZAO>','</NOMERAZAO>')

#result
print(nome)

#all results of tag
cnpj = find(xml,'<CNPJ>','</CNPJ>')

#results
print(cnpj)

#specifying the index
cnpj = find(xml,'<CNPJ>','</CNPJ>')[1]

#result
print(cnpj)

#looking for tag that doesn't exist
email = find(xml,'<EMAIL>','</EMAIL>')

#result
print(email)3 - example replace value#library
from lgpdXml import find, replace

#text
xml = '''<CNPJ>012.345.678/0001-01</CNPJ>
<NOMERAZAO>CLAUDIO TORRES ARBE</NOMERAZAO>
<CNPJ>001.001.001/0001-01</CNPJ>'''

#find using tag
nome = find(xml,'<NOMERAZAO>','</NOMERAZAO>')[0]

#all results of tag
cnpj = find(xml,'<CNPJ>','</CNPJ>')[1]

#replace tag
xml = replace(xml,'****','<NOMERAZAO>',nome,'</NOMERAZAO>')

#replace tag
xml = replace(xml,'****','<CNPJ>',cnpj,'</CNPJ>')

#result
print(xml)
Package: lgpio
lgpio Packagelgpio is a module for Linux Single Board Computers (SBC) which allows control of the General Purpose Input Outputs (GPIO).Featuresreading and writing GPIO singly and in groupssoftware timed PWM and wavescallbacks on GPIO level changenotifications via pipe on GPIO level changeI2C wrapperSPI wrapperserial link wrapperInstallationpypy can not handle Linux libararies properly at the moment.You need to install the lgpio module from the lg archive.Seehttp://abyz.me.uk/lg/download.html
Package: l-graph
lgraphPython module for working with L-graphs.Installationpipinstalll-graphCreating an L-graphfromlgraphimportLGraphlg=LGraph(3)lg.add_edge(lg.initial_main.name,'1')lg.add_edge('1','2',label='b',round_trace=')',square_trace='[')lg.add_edge('2','3',label='c',square_trace=']')lg.add_edge('3',lg.final_main.name)lg.add_edge('1','1',label='a',round_trace='(')lg.add_edge('2','2',label='b',round_trace=')',square_trace='[')lg.add_edge('3','3',label='c',square_trace=']')Saving and loading L-graphslg.save('graph_examples/a^n_b^n_c^n')lg.load('graph_examples/a^n_b^n')Cheking if string is in the language of the L-graphlg=LGraph()lg.load('graph_examples/a^n_b^n_c^n')'abc'inlg>>>True'abccc'inlg>>>False# Finding path of the stringpath=lg.find_successful_path('abc')LGraph.path_to_string(path)>>>initial_main---->1--a-->1--b-->2--c-->3---->final_mainType definition of the L-graphL-graph types defined in LGraph.LGraphTypeclassLGraphType(Enum):RECURSIVELY_ENUMERABLE=0CONTEXT_SENSITIVE=1CONTEXT_FREE=2REGULAR=3To define type of the L-graph use:lg.typeTo check properties of L-graph use:lg.is_regular()lg.is_context_free()lg.is_context_sensitive()OpeartionsLeft:Right:lg_left,lg_right=LGraph(),LGraph()lg_left.load('graph_examples/left')lg_right.load('graph_examples/right')Concatenationlg = lg_left * lg_right
lg.save('graph_examples/concatenate_result')Unionlg=lg_left+lg_rightlg.save('graph_examples/union_result')Shorter version is also available:lg_left*=lg_rightlg_left+=lg_right
Package: lgrt4gps
Welcome to the documentation forlgrt4gps!lgrt4gpsis a Python library which provides a simple API for
locally growing random trees for Gaussian processes.
For more details, we refer to the publication onArXiv.
Written by Jonas Umlauft and Patricia M. Strutz.RequirementsPython 3.6+DocumentationA documentation is available onreadthedocs.
The academic publication can be found atArXiv.InstallationTo install a stable version fromPyPi:~$pipinstalllgrt4gpsThe latest version is available onGitHub:
Package: lgtm-art
LGTM ArtEver wanted to spice up your code reviews? Now you can withLGTM ArtInstall withpip3installlgtm-artRun withlgtm-art /path/to/image.pnglgtm-art~/Downloads/image.pnglgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtmlgtml
Package: lgtmeow
LGTMeow 🐾—— 「本喵觉得很不错～」Nyakku 的自用 LGTM 模板，以「LGTMeow 🐾」为基础的 Emoji Kitchen 扩充版～InstallationVia cargo# If you have installed rust toolchain, you can install it via cargocargoinstalllgtmeow# or enable `copy` feature by runcargoinstalllgtmeow--featurescopyVia pipx# lgtmeow has been published to pypi, you can install it via pipxpipxinstalllgtmeow# The PyPI version has `copy` feature enabled by defaultUsage# Setup with default preferenceslgtmeowsetup--default# Random choose a LGTMeow 🐾 from presetlgtmeow-r# Use it with github clighprreview--approve-b"$(lgtmeow-r)"# Copy to clipboard (need `copy` feature)lgtmeow-r-cAcknowledgementxsalazar/emoji-kitchenprovide afrontendto view and search all available emoji-kitchen combinations. And we use it'sbackend datato generate the preset list.
Package: lgtm-lint
LGTM LinterLooks good to me! This is a satirical "linter" that doesn't actually assert or check anything. Linters have become so picky and opinionated that we thought it might be refreshing to have one that is happy with your code just the way it is!Python InstallYou can install this package via PyPI with the following command:pipinstalllgtm-lintThis will automatically addlgtm-lintto your path.Legacy InstallJust run the following:./legacy_install.shThis will install the script in your user bin. Also, Python3 is required to run the linter.UsageExecute the linter over any code you'd like linted! You can do this by running the following:lgtm-lint*Or a more specific file or directory, up to you.
Package: lh3api
Install=======Via Python Package Authority::pip install lh3apiConfiguration============In ~/.lh3/config::[default]server = libraryh3lp.comtimezone = UTCsalt = "you should probably change this"The `salt` is used when generating system-level utility accounts.This is not something you do often.  If your `salt` is unique, yourpasswords will be unique.In ~/.lh3/credentials::[default]username = <ADMIN_USER>password = <ADMIN_PASS>[test]username = <TEST_USER>password = <TEST_PASS>You can define different profiles (`test` above) that have differentlevels of access to the system, or access to different parts of thesystem.
Package: lhapdf-management
Management library for LHAPDFThis a pure-python LHAPDF management library to download, list and load PDFs.
At the moment it cannot do any interpolation or perform anything that would need a complete LHAPDF installation.InstallIt can be installed from pypi with a simple commandpip install lhapdf-managementFeaturesAt the moment is very bare-bones and includes only:UpdateUpdates the local reference indexlhapdf_management updateIf no installation of LHAPDF is found, the program will fail to do anything, as creating theLHAPDFdirectory is not the business of the management module.
In order to run lhapdf-management and make it believe that LHAPDF already exist a possibility is to populate theLHAPDF_DATA_PATHenvironment variable, i.e.,LHAPDF_DATA_PATH=$(python-c'from pathlib import Path ; from sys import prefix ; print(Path(prefix) / "share" / "LHAPDF")';lhapdf-managementupdateIt is possible to create the directory in the "best guess location" doinglhapdf_management update --initListLists all available PDFslhapdf_management list [PATTERNS ...] [--installed] [--codes]InstallInstalls a given PDFlhapdf_management install <pdf_name> [--upgrade] [--keep]Open a PDFIt can also be used to programatically get an object pointing to all the right parts of a PDF.
No interpolation will be provided by this script at this point and when/if it is ever provided
will be done by importing the normalpythoninterface of LHAPDF (and so at that point LHAPDF
will need to be installed)fromlhapdf_management.pdfsetsimportPDFfromlhapdf_management.configurationimportget_lhapdf_datapathdata_path=get_lhapdf_datapath()pdf=PDF(data_path/"NNPDF31_nnlo_as_0118")grids=pdf.get_member_grids(0)Programatically use the interfaceA very useful feature of this library is the possibility of using everything programatically.
The three given interfaces (install, list and update) take as input the same arguments
as the script interface.fromlhapdf_managementimportpdf_install,pdf_list,pdf_updatelist_of_pdfs=pdf_list("--installed")pdf_install("NNPDF31_nnlo_as_0118")Download all PDFs matching patternThere are some arguments that have been modified for simplicity as their behaviour can also
be obtained by other means.
For instance, in order to download all PDFs matching a certain pattern one can write the
following short bash script:forpdfin$(lhapdf_managementlistNNPDF31*)dolhapdf_managementinstall${pdf}--upgradedoneTODOWhile this script can (if needed) be used as is, there are a number of features missing to be compatible with thelhapdf.
The list of features that are currently missing with respect to the previous script are:list--outdatedinstall--dryrun
Package: lhcb-ftcalib
lhcb_ftcalibLHCb Flavour Tagging calibration softwareAt high-energy proton-proton collider experiments, the production flavour of neutral B mesons needs to be reconstructed from particle charges
from hadronisation processes in the associated event, i.e. from additional hadronisations on the signal meson side, as well as
hadronisation and decays of the partner B hadron. This is commonly done with ML techniques like (recurrent) neural networks or boosted decision trees.
The mistag probability estimates of these models (probability that predicted production flavour is wrong) usually need to have the property of probabilities.
This calibration tool optimizes a GLM function to predict the mistag probabilities and takes into account the fact that neutral mesons can undergo
oscillation before they decay. In addition, it provides helper functions to measure the performance and correlations of these models.Documentation:Read the DocsInstallationpip install lhcb_ftcalibCommand Line Interface ExamplesRunftcalib --helpfor a list of all options orread the docs1. Calibrating opposite side taggers in a sample and saving resultftcalib file:tree -OS VtxCh Charm OSElectronLatest OSMuonLatest OSKaonLatest \
        -mode Bd -tau B_tau -id B_ID -op calibrate -out output2. Calibrating both tagging sides, combining them inidividually, and calibrating+saving the resultsftcalib file:tree -OS VtxCh Charm OSElectronLatest OSMuonLatest OSKaonLatest \
        -SS SSPion SSProton \
        -mode Bd -tau B_tau -id B_ID -op calibrate combine calibrate -out outputNote:The command line interface is by design not feature complete. Use the API to fine tune the calibration settings.Requirementsuproot >= 4iminuit >= 2.3.0pandas < 1.5numpy <= 1.21scipymatplotlibnumba == 0.53.1For developersTesting multiple python versions via toxClick to expandTo test lhcb_ftcalib in different python environments, interpreters for each
version need to be installed. Multiple python versions can be installed withpyenv:CC=clangpyenvinstall3.6.15
pyenvinstall3.7.13
pyenvinstall3.8.13
pyenvinstall3.9.13
pyenvinstall3.10.5
pyenvinstall3.11.8
pyenvinstall3.12.2Whereby only missing versions need to be installed! Note that python 3.6 has
issues with pip throwing segfaults if not built with clang. To make the newly
installed versions globally available runpyenvglobal3.6.153.7.133.8.133.9.133.10.53.11.83.12.2and add$HOME/.pyenv/shimsto yourPATH.
To run the basic tests, executetoxin the lhcb_ftcalib directory
Package: lhcb-hooks
Pre-commit hooksPlatform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <4
Package: lhclient
lhclientThis utility connects to a deployment toImport scriptsImport modulesImport flowCreate an Event Type from a CSV fileParametersAll actions expect the following parametersorigin: eg. https:///apiusernamepassword (prompted interactively if missing)The last argument is either a file or a directory. If a directory is provided, the script will apply the action to all the files in the directory with suffixes .json, .py, .sh, .csv.ActionsImport a scriptUploads either a python or a bash script. If a script with the same name already exists, its contents are overwritten with the new contents (that's how the backend works, nothing specific to this script).Syntaxpython lhclient.py import script --origin https://<deployment_host>/api --username <username> <the py/sh file or folder>Import a moduleImports a module from its JSON representation. If a module with the same ID already exists, it will fail with theDuplicateModuleIdExceptionexception.Syntaxpython lhclient.py import module --origin https://<deployment_host>/api --username <username> <the json file or folder>Import a flowImports a flow from its JSON representation. We are currently using the legacy API, so import will fail if a flow with the same name already exists.Syntaxpython lhclient.py import flow --origin https://<deployment_host>/api --username <username> <the json file or folder>Create Event Type from CSVUploads a CSV file, creates a new FileConnection (named as the file, without the extension) and creates a new EventType (named as the file, without the extension as well). If the CSV file already exists, its contents will NOT be overwritten on the server. If an EventType already has the name of the filename, the creation will fail (we can't have two EventTypes with the same name).You can optionally use the --name argument to specify the name to use for both the FileConnection and the EventTypeSyntaxpython lhclient.py create event-type from-csv --origin https://<deployment_host>/api --username <username> <the csv file or folder>
Package: lhc-python
lhc-pythonThis is my personal library of python classes and functions, many of them have bioinformatics applications. The library changes constantly and at a whim. If you want to use it, approach with caution. Over time however, parts appear to be settling on a stable configuration.lhc.binflhc.binf.alignmentA pure Python implementation of the Smith-Waterman local alignment algorithm.lhc.binf.digenA C++ and pure Python implementation of sequence generation algorithm. The generated sequence will have a specified dinucleotide frequency.lhc.binf.genomic_coordinateAn implementation of intervals and points for genomic coordinates. Useful for representing gene models.lhc.binf.genetic_codeA class to read genetic codes and translate DNA sequences into protein sequenceslhc.binf.iupacA class to convert protein names between the one and three letter codes and the full name.lhc.binf.kmerA class that calculates k-mers for a given sequence. The class behaves likea dict, but calculates new k-mers on the fly.lhc.binf.skewA class that calculates skews for a given sequence. The class behaves like a dict, but calculates new skews on the fly.lhc.collectionsSeveral collections mostly for holding intervals. If only intervals need to be held, use the IntervalTree, otherwise the MultiDimensionMap may be more appropriate.lhc.filetoolsClasses for working with fileslhc.graphA pure Python implementation of graphslhc.indicesIntended to be my own code for indexing files but is still very unstable an immaturelhc.intervalA class for intervals and interval operationslhc.ioClasses for parsing and working with several file formatslhc.itertoolsClasses for working with iteratorslhc.toolsVarious classes, mostly unused and out-of-datelhc.randomlhc.random.reservoirAn implementation of the reservoir sampling algorithm. Can also be run from the command line to sample lines from files. To sample 50 lines from a file called input_file.txt, run:python-mlhc.random.reservoirinput_file.txt50lhc.statsReally old code. Probably the NIPALS and PCA algorithms are of most use.lhc.testUnit tests! These should be mostly up-to-date now.lhc.toolslhc.tools.sorterA sorter for very large iterators. The iterator will be split into chunks which are then sorted individually and then merged into a single file.lhc.tools.tokeniserA basic tokeniser. Users define which characters belong to which classes and the tokeniser will split strings into substrings where all characters have the same type.>>>tokeniser=Tokeniser({'word':'abcdefghijklmnopqrstuvwxyz','number':'0123456789','space':'\t'})>>>tokens=tokeniser.tokenise('there were 1000 bottles on the wall')>>>tokeniser.next()Token(type='word',value='there')>>>tokeniser.next()Token(type='space',value=' ')>>>tokeniser.next()Token(type='word',value='were')>>>tokeniser.next()Token(type='space',value=' ')>>>tokeniser.next()Token(type='number',value='1000')
Package: lhctodd
LHCToDDQuick startimportlhctodd# Listing all the available DD limitslhctodd.list()You can get then any limit# Geeting the XENON1T limitslimit=dd.DD(arxiv="1805.12562")# cross-section limit values at 100 GeVlimit.sigma(100)# plot the limitlimit.plot()# get the datadata=limit.data()# ordata=limit.to_pandas()to translate LHC limit to DDaxial_model=lhctodd.SD(g_chi=1.0,g_g=0.25,g_l=0.0,label="CMS MonoZ")axial_dd=axial_model.from_csv("limit-EXO-19-003-SD-90CL.csv")axial_model.plot()# orimportmatplotlib.pyplotaspltplt.plot(axial_dd[:,0],axial_dd[:,1])plt.xlabel("DM mass")plt.ylabel("DM-Nucleon cross-section (cm2)")note:  all the limits should be at 90%CLinstallationTo installlhctoddfrom PyPIpipinstalllhctodd