Saravanan666/pypi-org huggingface dataset:
Package: jk-uploadpack
jk_uploadpackIntroductionThis python module provides a packer/unpacker based on 'tar' that reduces redundancies before packing.Information about this module can be found here:github.orgpypi.python.orgWhy 'uploadpack'?Classic compression tools work very well in general. But in very specific situations these tools won't work well enough: If you need to compress data containing redundant
data that can't be compressed very well. This is the case with some directory trees for web sites hosted by webservers. And precisely that was the motivation to implementuploadpack.Souploadpackis nothing more than atarbased compression tool. In fact anuploadpackis nothing else but atarfile (possibly compressed withgz,bzip2orxz)
with a very specific structure: It avoids redundancies.Limitations of this moduleThisuploadpackcurrently only suppors files and directories, no links.PreliminariesPlease include an import statement for this module into your application by using the following code:importjk_uploadpackHow to compress a directory tree to anuploadpackarchiveIn order to create anuploadpackyou need to instantiate a packer:up=jk_uploadpack.Packer("archive.up.gz")Now you can create a file group (here: "foo") and add a file to it (here: "foobar.txt"):up.fileGroup("foo").addFile("/path/to/dir/foobar.txt","dir/foobar.txt")Of course you can repeat that with any number of files.After having added all files you need to close the archive:up.close()You must always invokeclose()as otherwise essential data will not be written.A more secure way of doing this is by usingPackerwithwith:withjk_uploadpack.Packer("archive.up.gz")asup:up.fileGroup("foo").addFile("/path/to/dir/foobar.txt","dir/foobar.txt")In this caseclose()will be called automatically.How to uncompress anuploadpackarchiveIn order to decompress anuploadpackyou need to instantiate an unpacker:up=jk_uploadpack.Unpacker("archive.up.gz")Then you can unpack all files to a target directory:up.fileGroup("default").unpackToDir("outdir")After having extracted all files you can close the archive:up.close()You should always invokeclose().A more secure way of doing this is by usingUnpackerwithwith:withjk_uploadpack.Unpacker("archive.up.gz")asup:up.fileGroup("default").unpackToDir("outdir")In this caseclose()will be called automatically.Specific FeaturesFile Groupsuploadpackalways puts files in so called file groups. File groups are organizational units that can be considered as being an archive themselves. Characterstics of such a file group are:A file group is identified by a name.On decompression all files of a file group are always written to a specific directory.Certain parameters can be set at a file group that take effect for all files in that file group.If you don't need to use file groups for a specific reason, use "default" as a convention.Contact InformationAuthor(s):Jürgen Knauth:pubsrc@binary-overflow.deLicenseThis software is provided under the following license:Apache Software License 2.0
Package: jk-utils
jk_utilsIntroductionThis python module provides various utility functions and classes.Information about this module can be found here:github.orgpypi.python.orgHow to use this module........Contact InformationThis is Open Source code. That not only gives you the possibility of freely using this code it also
allows you to contribute. Feel free to contact the author(s) of this software listed below, either
for comments, collaboration requests, suggestions for improvement or reporting bugs:Jürgen Knauth:jknauth@uni-goettingen.de,pubsrc@binary-overflow.deLicenseThis software is provided under the following license:Apache Software License 2.0
Package: jk-vcard
jk_vcardIntroductionThis python module parses (and produces) vCard data as provided in vcf files.Information about this module can be found here:github.orgpypi.python.orgHow to use this moduleImport this modulePlease include this module into your application using the following code:importjk_vcardParse a .vcf fileIf you export your contacts in your Android smart phone, a VCF file is created. This can serve as an example file and can be parsed using the following code:withopen("contacts.vcf","r")asf:data=f.read()forvCardinVCFParser.parseText(data):print("-"*120)print()vCard.dump()print()print("-"*120)Produce a .vcf file from vCard dataIf you want to produce a.vcffile you simply can invokeVCFEncoder.toLines(...)in order to generate text lines in this format:vCard=....fortextLineinVCFEncoder.toLines(vCard):print(textLine)If you have a list ofVCardobjects you can simple (re)create a.vcffile like this:withopen("contacts.vcf","w")asf:forvCardinmyVCardList:fortextLineinVCFEncoder.toLines(vCard):f.write(textLine+"\n")Contact InformationThis work is Open Source. This enables you to use this work for free.Please have in mind this also enables you to contribute. We, the subspecies of software developers, can create great things. But the more collaborate, the more fantastic these things can become. Therefore Feel free to contact the author(s) listed below, either for giving feedback, providing comments, hints, indicate possible collaborations, ideas, improvements. Or maybe for "only" reporting some bugs:Jürgen Knauth:pubsrc@binary-overflow.deLicenseThis software is provided under the following license:Apache Software License 2.0
Package: jkx
json-key-explorerCLI tool to explore the keys in a JSON file.Use CaseUseful for discovering the various key paths inside a large JSON file. Ignore the unwanted clutter inside the JSON and focus on the path that is important to you.Installationpip install jkxUsagejkx -f file.jsonTo print the JSON path in different formats, pass the following flags:JavaScript -jsjkx -f file.json -js

Example Output:
---------------
Path = data.servers[1].variables.region.enum[4]Python -pyjkx -f file.json -py

Example Output:
---------------
Path = data['servers'][1]['variables']['region']['enum'][4]
Package: jk_xmljsonconv
IntroductionThis python module provides possibilities to convert XML to JSON vice versa through a conversion manager.Information about this module can be found here:[github.org](https://github.com/jkpubsrc/python-module-jk-xmljsonconv)[pypi.python.org](https://pypi.python.org/pypi/jk_xmljsonconv)Contact InformationThis is Open Source code. That not only gives you the possibility of freely using this code it also
allows you to contribute. Feel free to contact the author(s) of this software listed below, either
for comments, collaboration requests, suggestions for improvement or reporting bugs:Jürgen Knauth:jknauth@uni-goettingen.de,pubsrc@binary-overflow.deLicenseThis software is provided under the following license:Apache Software License 2.0
Package: jk-xmlparser
jk_xmlparserIntroductionThis python module parses XML (and HTML) files.Please be aware that this parser has some unique features like leaving entities unprocessed, and therefore does not follow the XML standards in all aspects. Therefore this parser might may not be suitable for all purposes (while at the same time the 100% standard-compliant XML parsers are not suitable for specific purposes in which this parser excels.)Information about this module can be found here:github.orgpypi.python.orgHistoryThis project is largly a port of some non-Python code written in the first half of 201X for an academic project.Current state of the project: Beta.How to use this module...Contact InformationThis is Open Source code. That not only gives you the possibility of freely using this code it also
allows you to contribute. Feel free to contact the author(s) of this software listed below, either
for comments, collaboration requests, suggestions for improvement or reporting bugs:Jürgen Knauth:jknauth@uni-goettingen.de,pubsrc@binary-overflow.deLicenseThis software is provided under the following license:Apache Software License 2.0
Package: jlab-create-sas-file
jlab_create_sas_fileCreate a SAS file from the Jupyter Lab interfaceRequirementsJupyterLab >= 3.0Installpipinstalljlab_create_sas_fileContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the jlab_create_sas_file directory# Install package in development modepipinstall-e.# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Rebuild extension Typescript source after making changesjlpmrunbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmrunwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm run buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseUninstallpipuninstalljlab_create_sas_file
Package: jlabdev
JLAB DevDevelop python packages using jupyterlab.This library allows you to develop regular python packages while writing your code in jupyterlab.
You can create notebooks to develop your code and in these notebooks, simply annotate your cells with#exportif you want them to be put in the library. (A notebook must be marked for conversion with#convertin the first code cell.)
Other cells will be used as examples in your doc (together with the markdown of your notebook) unless marked with#hide.Of course JLAB Dev itself is completly implemented as a notebook in jupyterlab (seehere).InstallationIt is as simple as a pip install.# For stable versionpipinstalljlabdev# or for bleeding edgepipinstallgit+https://github.com/penguinmenac3/jlabdev.gitUsageBasicsSimply create your notebooks and add a code cell with#convertas the first cell and annotate all cells you want to export with#export.Now you can compile your notebook into python and markdown doc by saving it and then running these commands at the root of your project folder:nb2py# Creates python files next to the notebooksnb2md# Creates markdown doc in docsWhen you edit your python file (e.g. refactoring) and want to update the notebook from the python file.py2nbDocumentationDocumentation can be found indocsit will be automatically generated there. The README.md is an overview over all packages availible.LicenseThe MIT License (MIT)Copyright (c) 2020 Michael FuerstPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: jlab-enhanced-launcher
jlab-enhanced-launcherA enhanced launcher for JupyterLab.This codes started fromhttps://github.com/jupyterlab/jupyterlab/pull/5953.RequirementsJupyterLab >= 3.0For JupyterLab 2.x, have lookthere.Installpipinstalljlab-enhanced-launcherorcondainstall-cconda-forgejlab-enhanced-launcherUninstallpipuninstalljlab-enhanced-launcherorcondaremove-cconda-forgejlab-enhanced-launcherContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the jlab_enhanced_launcher directory# Install package in development modepipinstall-e.# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Rebuild extension Typescript source after making changesjlpmrunbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmrunwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm run buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=False
Package: jla-demultiplexer
jla-demultiplexer: Internal JLA lab tool for processing gene-specific sequencing experimentsInstallationpipinstalljla-demultiplexerUsagefastqbreakdown: Removes duplicate reads and trims barcodes and randommer additionfastqbreakdown-r1[read1location]-r2[read2location]\-r[lengthofrandom-mer]-b[barcode]NotesRandom-mer length supplied should be 10 or 11barcode supplied should be barcode column + gene specific column from manifestUsagedemultiplexer: Use JLA standard manifests to align and create tail files. Very specific to our gene-specific sequencing methodologydemultiplexer-r1[read1location]-r2[read2location]\-m[manifestlocation]-e[ensids]-f[referencefasta]NotesMust provide either -e (comma separated) or -f, but not bothoutputs to location of read 1tail file output is compatible with Tailer-Analysis which can be found athttps://timnicholsonshaw.shinyapps.io/tailer-analysis/Usagejla-trim: Removes duplicate reads and trims randommer addition only. FASTQ outputjla-trim-r1[read1location]-r2[read2location]\-r[lengthofrandom-mer]NotesRandom-mer length supplied should be 10 or 11
Package: jla-tailer
Tailer: A tool for 3' end analysis of non-polyadenylated RNAs from 3' sequencing dataRequirementsPython >= 3.6pysamBiogffuitlsrequeststqdmInstallationpipinstalljla-tailerUsageGlobal alignment with a GTF annotation and SAM/BAM formatted filesTailer-a[GTFAnnotation][SAMorBAMFiles]Required Arguments-a, --annotationGTF formatted database to be used to infer 3' ends. Ensembl GTFs have worked well for this pipeline[SAM or BAM Files]Space separated list of sam/bam formatted file locations to perform 3' end tail analysisLocal alignment with with FASTA/Q and specific Ensembl IDs of interest or reference fastaTailer-e[commaseparatedlistofEnsIDsnospaces][FASTA/Qfiles]Tailer-ffasta_reference_file.fasta[FASTA/Qfiles]Required Arguments-e, --ensidsComma separated list of ensembl IDs. Either -e or -f inputs are required.-f, --fastaFASTA formatted file to align reads against. Either -f or -e inputs are required[Trimmed FASTQ files]Space separated FASTQ file locations for analysis.Optional arguments-t, --threshold [int, default=100]Any alignment identified further than this distance in nucleotides from the mature end will be considered spurious and discarded-x, --trim [int, default=0]Helper for local mode only, can remove X nucleotides from adapter on the 3' end-read, --read [int, default=1]Paired end only. 1 or 2 to signify which end contains the 3' end information.-r, --rev_compIf set, will reverse complement the reads. Necessary for some library prep methods-f, --fastaUse a fasta file as a reference instead of building one from ensembl IDs (Local Only)-s, --sequenceOutput sequence in the tail file. Useful for debugging.miRNA tailing (in development)Tailer--miRNA[samfiles]Determines tails using an alignment file (SAM/BAM) that was aligned to a fasta genome of mature miRNAsOptional arguments--rpad [int, default=0]Number of downstream nucleotides added to distinguish between post-transcriptional and genome-encoded tails
Package: jlcpcbexporter
jlcpcbexporterTool to generate BOM and CPL files compatible with JLCPCB's SMT process.This tool takes an EAGLE CAM export zip file, and generates comma-separated
values (CSV) files that can be uploaded to JLCPCB's web interface to request
SMT treatment for a board.Usage$ pip install jlcbpcexporter
$ jlcpcbexporter --layer top eagle-cam-export.zipThe--layerflag selects betweentopandbottomlayer, as JLCPCB only
allows SMT on one of the two.CompatibilityThe tool has been developed with Python 3.8 on Windows, but it should be
compatible with any reasonably modern Python on any operating system.NotesI am providing code in the repository to you under an open source license.
Because this is my personal repository, the license you receive to my code
is from me and not my employer. (Facebook)
Package: jld
This library contains the following utilities:MindMeistermindmaps Backup command line: for exporting mindmaps fromMindMeisterin FreeMind formatEventManager script interfaceDeliciousAPI & Backup command line utilityGliffyAPI & Backup command line utilityCommand-Line toolspypre(preprocessor based onMako, e.g. useful for pre-processing Apache config files)nsvn(nuke svn: removes svn directories, e.g. useful under Windows where .dot files are difficult to handle)trns(Transmission Bittorent client e.g. useful for auto-stopping downloads & post-processing)Cross-platform registry (Windows: uses the win32 registry, Linux: uses a filesystem path)UpdatesFollow project news onTwitteror subscribe to theRSSfeed.Changelog0.0.39* better exception handling for all command line tools: trns.py used to hang cron when web service wasn’t available0.0.38* mm: Corrected missing information message when performing ‘auth’ command
Package: jldaws
OverviewThis package contains a collection of Amazon Web Service related scripts e.g.jldsqsjob : wait for stdin trigger, dequeue msg(s) from SQS Q#1, send to stdout, requeue to SQS Q#2, delete msg(s) from Q#1jlds3upload : automated file upload to S3jlds3download : automated file download from S3jldrxsqs : receive from an SQS queue to JSON/string stdout (with optional stdin trigger)jldtxsqs : transmit on SQS JSON/string from stdinjldleader: distributed leader election protocol managerjlds3up  : simple file upload to s3 with functionality to delete ‘old’ filesjlds3list : listing files in an S3 bucketjldsdb: list, create and delete operations on SDBjldsdbget: retrieve entries in SDBjldsdbinsert: insert records in SDBjldsdbbatchinsert: batch insert records in SDB from fileThe philosophy behind these scripts is:simplicity  : each script only does 1 thingreporting   : status & error reporting through stderr and (optionally) JSON stdoutdata driven : object in from src ==> object out to dstdata flow   : piping through stdin / stdoutScripts can easily be “composed” through standard Linux piping :jldrxsqs @config1.txt | some_other_command | jldtxsqs @config2.txtThe data format used is JSON.ConfigurationCan be performed through options on the command line or using a file (use a leading@).HistoryChanges history can be found at the project page:https://github.com/jldupont/jldaws
Package: jldc
jldcSimplify usingJSON Linesfiles alongsidepython dataclass(PEP-557)
objects, with convenient one-line reads/writes.usageImport the library and save/load lists of dataclasses or dictionaries with a single line.fromjldc.coreimportload_jsonl,save_jsonlfromdataclassesimportdataclass@dataclassclassPerson:name:strage:intsave_jsonl("people.jsonl",[Person("Alice",24),Person("Bob",32)])data=load_jsonl("people.jsonl",[Person])print(data)installationInstall directly from GitHub, using pip:pipinstalljldcUse themlextra to encode/decode thenumpy.ndarraytype:pipinstalljldc[ml]developmentFork and clone the repository code:gitclonehttps://github.com/itsluketwist/jldc.gitOnce cloned, install the package locally in a virtual environment:python-mvenvvenv

.venv/bin/activate

pipinstall-e".[dev,ml]"Install and use pre-commit to ensure code is in a good state:pre-commitinstall

pre-commitautoupdate

pre-commitrun--all-filestestingRun the test suite using:pytest.
Package: jlddk
Overview--------This package contains a collection of 'robots'.Each 'robot' is implemented with logging on stderr and processing result is output on stdout as either string or JSON.Robots------* jldbolus: move processed subdirectories* jldstrpkg: stdin --> formatter --> stdout* jldwebscraper : extract anchor links from a web page* jldfilter : filter stdin through a Python module, output on stdout* jldcomp : compare 2 filesystem paths for difference in files* jldfcomp : compare globs of files* jldcat: 'cat' files to stdout, 1 per line with format 'filename	contents'* jlduncat: Receive from stdin "key	contents" and write to key[.ext]* jldjsoncat : 'cat' files to stdout by encapsulating them in JSON objects* jldwebdl : gated web page download, source links contained in file system path* jldinotify : path change notification over JSON/stdout* jldfetcher : web page fetcher which takes instructions from stdin* jldfilelist : list path files using include/exclude filter, JSON/stdout output* jldclock : 1 second interval clock with min,hour,day markers* jldpclean : kills processes left to pid=1* jldtaskctl : task controller* jldostr : outputs a string on stdout @ regular interval, pass-through for stdin-->stdout* jldstatsubdirs: periodic status information on sub-dirs of path (JSON output & pass-through stdin-->stdout)* jlddebouncer: debounces {key:value} pairs (JSON output & pass-through stdin-->stdout)* jldarun : runs "agents"* jldrun : periodically run a python callable* jldtouch: receive filename from stdin, 'touch' filename in destination path* jldsplitter: a semi customizable file splitterConfiguration-------------Can be performed through options on the command line or using a file (use a leading `@`).
Package: jl-exp-deconv
jl_exp_deconvThis module trains on known experimental pure-component spectra
in order to deconvolute unknown mixture spectra.Licensejl_exp_deconvis licensed under the terms of the MIT license. See the file
“LICENSE” for information on the history of this software, terms & conditions
for usage, and a DISCLAIMER OF ALL WARRANTIES.All trademarks referenced herein are property of their respective holders.Copyright (c) 2019–, Joshua Lansford, The University of Delaware.
Package: jlibs
Supported operations (using Boto3)AWSAthenaSQL query (results auto-saved to S3; optional download to local disk)EC2List of AMIList of InstancesMiscellaneous (non-Boto3)FileCSVSaving of results (i.e. lists) to CSVCacheSaving of results (i.e. lists) to a file-based cacheLoading of data from file-based cacheDocumentationhttps://john.mariquit.com/projects/jlib/
Package: jl-logger
jl-loggerA JupyterLab logging extension.RequirementsNode.jsJupyterLab >= 3.0InstallTo install the extension, execute:pipinstalljl-loggerUninstallTo remove the extension, execute:pipuninstalljl-loggerUsageClick Logger button in  toolbar.Input log filename.Or Check W&B and jl-logger can automatically extract run name and autocomplete filename.Execution result is logged to specified filename.NOTE:
 If you activate jl-logger without specifying filename, execution result is logged to [yyyyMMddHmm].log.