Saravanan666/pypi-org huggingface dataset:
Package: gtax
GTaxGTaxpython package provides tools for the creation of the GTax sequence-based database. This database includes
one assembly per organism deposited in the NCBI Genomes database. The sequences are organized by 19 taxonomic levels
fromsuperkindomtoclades. Python pickle files are also provided with a graph data structure for the taxonomic
tree.Read the Docs at:https://gtax.readthedocs.io/Current versionThe current public version is available in GCP for download. You need to use your GCP project as this bucket uses Requester Pays option.https://console.cloud.google.com/storage/browser/gtax-database/gsutil -u <you-GCP-project> -m cp -r gs://gtax-database/<latest_version> .The database is comprised of two folder:blastdbandfasta. Theblastdbfolder include the BLAST
indexes for BLAST searches. Thefastafolder includes the FASTA files for the taxonomy groups and two
Python Objects in pickle files (taxonomy.pickleandtaxonomy_groups.pickle) which are used to load
all GTax metadata into theTaxonomy classfromgtax.taxonomyimportTaxonomytaxonomy=Taxonomy(tax_pickle_file='taxonomy.pickle',group_pickle_file='taxonomy_groups.pickle')Output:2464341 taxonomies loaded
bacteria Node: 537498 Sequences: 19435
archaea Node: 14266 Sequences: 798
liliopsida Node: 48464 Sequences: 317
eudicotyledons Node: 153108 Sequences: 1077
viridiplantae Node: 48003 Sequences: 185
fungi Node: 186994 Sequences: 914
arthropoda Node: 912789 Sequences: 2596
neoteleostei Node: 31205 Sequences: 1610
actinopterygii Node: 22514 Sequences: 1258
glires Node: 5490 Sequences: 2346
primates Node: 1101 Sequences: 673
carnivora Node: 783 Sequences: 437
artiodactyla Node: 1200 Sequences: 487
amphibia Node: 13009 Sequences: 122
sauropsida Node: 32051 Sequences: 1476
sarcopterygii Node: 4941 Sequences: 376
chordata Node: 4122 Sequences: 400
eukaryota Node: 194114 Sequences: 896
viruses Node: 234108 Sequences: 14233Public Domain noticeNational Center for Biotechnology Information.This software is a "United States Government Work" under the terms of the United States
Copyright Act. It was written as part of the authors' official duties as United States
Government employees and thus cannot be copyrighted. This software is freely available
to the public for use. The National Library of Medicine and the U.S. Government have not
placed any restriction on its use or reproduction.Although all reasonable efforts have been taken to ensure the accuracy and reliability
of the software and data, the NLM and the U.S. Government do not and cannot warrant the
performance or results that may be obtained by using this software or data. The NLM and
the U.S. Government disclaim all warranties, express or implied, including warranties
of performance, merchantability or fitness for any particular purpose.Please cite NCBI in any work or product based on this material.
Package: gtbook
gtbookThe book can be found athttps://www.roboticsbook.organd has the
following chapters:IntroductionA Trash Sorting
Robot(discrete)A Robot Vacuum
Cleaner(vacuum)Warehouse Robots in
2D(logistics)A Mobile Robot with Simple
Kinematics(diffdrive)Autonomous
Vehicles(driving)Autonomous Drones in
3D(drone)The structure of gtbook mirrors this organization, and then has a few
more support modules for displaying graphs inside notebooks and for
running the code in the book. The gtbook modules are listed above
alongside the chapter.How to useIn the book chapters, we should have a cell that fetches the latest
version using pip:%pipinstall-q-UgtbookThe above automatically installs other libraries on colab, e.g., gtsam
and plotly.You also needs a cell that imports what you need in a particular
section, for example:fromgtbook.displayimportshowfromgtbook.discreteimportVariablesFurther usage examples of these and more functions are given in the
module documentation itself.There are also some command line tools defined in theclimodule.Notes for developmentMostly for Frank as he adds to the library.For version 2 of nbdev in a local conda environment called nbdev2. It
can be re-created withconda env create -f environment.yml.I usedconda install -c fastai nbdevto install nbdev in there as
well, but the github workflow usespip install nbdevso I can just
use one channel.pip install -e .for local install of the remaining modules
specified in the settings.ini fileto preview the docs donbdev_previewto push a new version, usenbdev_prepareand then push.To release a new version:nbdev_bump_versionnbdev_pypi
Package: gtbump
gtbumpgit tag bump: A simple utility to bump and manage semver git tags and generate Markdown changelogs.InstallpipinstallgtbumpUsage# cd to your git repo.# see the last tag.$gtbump--show
notagsfound.Run--inittoaddv0.1.0# add a tag for the first time.$gtbump--init
bumpedv0.0.0->v0.1.0# bump major | minor | patch$gtbump--minor
bumpedv0.1.0->v0.2.0

$gtbump--major
bumpedv0.2.0->v1.2.0# delete the last tag$gtbump--delete-last
deletedv1.2.0# push the last tag upstream(or --push-last=your_remote_name)$gtbump--push-last
pushingv0.3.0toorigin# generate changelog for the latest tag. This can be copy-pasted into GitHub's release description.$gtbump--changelog
changelogforv1.0.0->v1.1.0
-b361292DisplayappversionthesettingsUI
-a3b285fFixBuefynumberinputwidth
-63520d2Mergepullrequest#388 from dunklesToast/chore/update-german-translations-3abac31chore(translations):improvegermantranslations
-3ecac76FixVuelintingissueCheckgtbump --helpfor more options.Licensed under the MIT license.
Package: gt-converter
[![MIT License](https://img.shields.io/apm/l/atomic-design-ui.svg?)](https://github.com/tterb/atomic-design-ui/blob/master/LICENSEs) <a href=”https://github.com/psf/black”><img alt=”Code style: black” src=”https://img.shields.io/badge/code%20style-black-000000.svg”></a>## SageMaker Ground Truth Conversion KitEasily convert Ground Truth outputs into other industry standard formats.## Install dependencies for test` pip install-e.[test] `## Usage` job_name ="gt-converter-demo-job"converter = CocoConverter() converter.convert_job(job_name,output_coco_json_path="output.json")`## Testing` pytest-s`## Formatting` black . `## SecuritySee [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.## LicenseThis library is licensed under the MIT-0 License. See the LICENSE file.
Package: gtd
TestsDownloadsAboutStatusAboutI’ve been using a TODO list for years in paper, inspired by the book “The Personal Software Process”, by Watts S. Humprey. But I read the articleThe Power of the TODO List, byJames Hoodand I decided to implement it in that way.Basically, there are a file per day to write down 3 parts:In progress: This is the most important part: things to be accomplished today.Accomplished: things that were finished today.Backlog: Things to be accomplished in the future.Why to use GTD?Because it is very simple and easy to use. Just install it withpip install gtdand edit the current day withpython-mgtd. That’s it.The format is quite simple. Just the headers “In progress”, “Accomplished” and “Backlog” for these tasks, and each task must start with a hyphen and space(’- ‘).Each day, it will copy the previous file, and:it will remove the ‘Accomplished’ section.it will move to the ‘In progress’ section the tasks from the ‘Backlog’ section that with a due date previous to current date.The ‘Backlog’ section can have a due date, if they starts with[YYYY-MM-DD].Example:In progress:
- do cool things
- do useful things

Accomplished:
- do minor stuff

Backlog:
- [2049-02-31] Take on the worldRoadmapGTDis fully usable. In the near future it should be able to generate statistics and reports with the activity.
Package: gtdb-itol-decorate
gtdb-itol-decorateCreates iTOL files for tree decoration, given a set of GTDB genomes.Installationpipinstallgtdb-itol-decorateUsageNote: The taxonomy file is available from the GTDB data repository.gtdb_itol_decorate/path/to/tree.tree/path/to/taxonomy.tsv/path/to/output
Package: gtdblib
gtdb-libAn abstraction of objects, files, and third-party tools used by the GTDB. Not intended for public use.The library is under active development and the API will change frequently, it is strongly recommended to
specify a specific version when using it.InstallationPython >= 3.6 is required.python-mpipinstallgtdbContributingCommit guidelinesThis project usesSemantic VersioningandConventional Commitsto automatically generate release notes usingSemantic Release.
If you are using PyCharm, thenGit Commit Templatewill be useful.
Package: gtdb-precurate
GTDB Precurategtdb_precurateis an internally used tool used that provides automatic pre-curation of GTDB trees.Installationgtdb_precurate is available on PyPI and can be installed with pip:pipinstallgtdb_precurateUsageAfter a successful install, thegtdb_precuratecommand should be available.The following positional arguments are required:metadata- This is the path to the metadata file, it should contain a header as the first line.
The only requirement is that it has the following columns:formatted_accessionandncbi_wgs_formatted.red_dict- This is the path to the RED dictionary output by PhyloRank.red_decorated_tree- This is the path to the scaled RED decorated output by PhyloRank.out_directory- This is the path to the directory where the output files will be written.The following optional arguments are available:--min-bootstrap- This is the minimum bootstrap value to consider a node to be supported. Default: 95.0.--debug- This enables debug logging. Default: False.
Package: gtdbtk-db-download
GTDB-Tk Database DownloadMinimal toolkit for downloading the GTDB-Tk database to disk.This isnot the recommended wayto download the GTDB-Tk reference database, please seeherefor the reccomended method.This softare may be useful for users who are experiencing intermittent connection errors, or slow download speeds.📚 RequirementsThis software requires Python >=3.8 and makes use of the following packages:requeststqdmtyper⚙️ InstallationIn a new virtual environment, or conda environment that is running Python >=3.8, simply run:python-mpipinstallgtdbtk_db_download🚀 UsageFor a complete list of options, run:gtdbtk_db_download --helpExample usage downloading to the/tmp/dbdirectory:gtdbtk_db_download/tmp/db--threads10Example output[2023-06-16 13:51:41] - gtdbtk_downloader v1.0.0
[2023-06-16 13:51:41] - Creating output directory.
[2023-06-16 13:51:41] - Loading R214 manifest
[2023-06-16 13:51:42] - Creating queue
[2023-06-16 13:51:42] - Downloading files
[2023-06-16 16:00:00] - Done.
Package: gtdb-validation-tk
GTDB Validation ToolkitThis toolkit provides functionality for validation the GTDB Taxonomy. It is primarily intended to be used by the GTDB curation team, but has been made available in case others find it useful.InstallThe simplest way to install this package is through pip:sudo pip install gtdb_validation_tkPackage updatesPyPIpython3setup.pysdistwheel
python3-mtwineuploaddist/*AnacondaClone thehttps://github.com/Ecogenomics/ace-condarepository on a CentOS server.Create a newmeta.yaml,similar to previous versions(adding any new dependencies, the version number, and the SHA256 hash from pypi.org)Build and upload the package according to the instructions inace-conda.Update the server modulefiles according to theACE wikiCiteIf you find this package useful, please cite this git repository (https://github.com/Ecogenomics/gtdb_validation_tk)CopyrightCopyright © 2019 Donovan Parks. See LICENSE for further details.
Package: gt-defect-dojo
THIS API WRAPPER IS DEVELOPE BY MEpSeeclients and api wrappers in the docs <https://defectdojo.github.io/django-DefectDojo/integrations/api-v2-docs/#clients--api-wrappers>_ for alternativesDefectDojo APIA Python API wrapper forDefectDojo <https://github.com/OWASP/django-DefectDojo>_, an AppSec and Security Vulnerability Management tool.This package implements API functionality available within Dojo.Quick StartSeveral quick start options are available:Clone the repository: :code:git clone https://github.com/DefectDojo/defectdojo_apiInstall with pip (not recommended): :code:pip install git+https://github.com/DefectDojo/defectdojo_api#masterIf you are testing the api locally make sure to set the PYTHONPATH. export PYTHONPATH=/path/totheapi/defectdojo_api:$PYTHONPATHExample.. code-block:: python# import the package
from defectdojo_api import defectdojo

# setup DefectDojo connection information
host = 'http://localhost:8000/'
api_key = 'your_api_key_from_DefectDojo'
user = 'admin'

# instantiate the DefectDojo api wrapper
dd = defectdojo.DefectDojoAPI(host, api_key, user, debug=False)

# If you need to disable certificate verification, set verify_ssl to False.
# dd = defectdojo.DefectDojoAPI(host, api_key, user, verify_ssl=False)

# Create a product
prod_type = 1 #1 - Research and Development, product type
product = dd.create_product("API Product Test", "This is a detailed product description.", prod_type)

if product.success:
    # Get the product id
    product_id = product.id()
    print "Product successfully created with an id: " + str(product_id)

#List Products
products = dd.list_products()

if products.success:
    print(products.data_json(pretty=True))  # Decoded JSON object

    for product in products.data["objects"]:
        print(product['name'])  # Print the name of each product
else:
    print products.messageMore examplesavailable <https://github.com/aaronweaver/defectdojo_api/tree/master/examples>_ on Github.Supporting information for each method available can be found in thedocumentation <https://defectdojo-api.readthedocs.io>_.Bugs and Feature RequestsHave a bug or a feature request? Please first search for existing and closed issues. If your problem or idea is not addressed yet,please open a new issue <https://github.com/aaronweaver/defectdojo_api/issues/new>_.Copyright and LicenseLicensed under MIT <https://github.com/aaronweaver/defectdojo_api/blob/master/LICENSE.txt>_.
Package: gt-dicom-connector
gt-dicom-connectorgt-dicom-connector is a python library to retiev and send data to dicom nodesInstallationUse the package managerpipto install gt-dicom-connector.pipinstallgt-dicom-connectorCurrently gt-dicom-connector supports python 3.6 and 3.7.ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: gtdownloader
GTdownloaderGTdownloader is a geographical tweets downloading tool that leverages theTwitter APIto retrieve tweets with geographical information and store them in easy accessformats like .csv and .shp.InstallationpipUse the package managerpipto install gtdownloader.pipinstallgtdownloadercondaAlternatively, install gtdownloader from the conda-forge channel by running the following command:condainstall-cconda-forgegtdownloaderTwitter keysTo set up your twitter keys file you need to have a developer  account with access to the full-archivesearch. If you plan to use this as part of academic research, you can apply for researcheraccess to the API atTwitter Academic Research access.After loging into your developer account, copy the consumer key, the consumer secret and the bearer token into a .yamlfile in the following way:search_tweets_v2:endpoint:https://api.twitter.com/2/tweets/search/allconsumer_key:YOUR_CONSUMER_KEYconsumer_secret:YOUR_CONSUMER_SECRETbearer_token:YOUR_BEARER_TOKENGet startedfromgtdownloaderimportTweetDownloader# create downloader using Twitter API credentialsgtd=TweetDownloader(credentials='twitter_keys.yaml')# get a batch of 400 tweets in english containing the word "tornado"# between the dates 07/23/2022 and 07/29/2022gtd.get_tweets('tornado',lang='en',max_tweets=400,start_time='07/23/2022',end_time='07/29/2022')# accessing tweets data framegtd.tweets_df.head()ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.GitHubLicenseMIT
Package: gtempco2
gtempco2gtempco2 is a PyPI application to display global temperature and co2 of land and ocean with NOAA datasets.NOAA monthly datasets on the global temperature of land and ocean and the global co2 will be automatically downloaded.gtempco2 is to plot a graph for a user-specified time period with two lines representing global temperature and global CO2 levels. The graph includes first-order regression lines with coefficients and R-squared values.To install gtempco2, use the following pip command.$ pip install gtempco2To run gtempco2, the user-specified time period such as start-date and end-date is needed to plot a graph of the global temperature and co2 from start-date to end-date.The format of them is as follows.For example, 1958-03 indicates March 1958 when NOAA started the measurement of the global co2.$ gtempco2
enter start_date: e.g. 1960-04
co2 measurement started from 1958-03
yyyy-mo: 1960-06
enter end_date: e.g. 2023-04
yyyy-mo: 1965-06
start_date= 1960-06 end_date= 1965-06The system will ask the start-date and end-date. The result will be shown and saved in the directory as follows.
Package: gtexquery
GTExQuery:class: tip

This repository houses the code, tests, etc.,
that run the nuts and bolts of the Snakemake pipeline
[GTExSnake][GTExSnake]GTExSnake is a fully concurrent pipeline for querying
transcript-level GTEx data in specific tissues.
This package handles all the code needed for
multithreading,
data handling,
and file manipulation necessary for so-said pipeline.If you find the project useful,
leaves us a star ongithub!If you want to contribute,
please see theguide on contributingMotivationThere are a number of circumstances where transcript level expressed data for a
specific tissue is highly valuable.
For tissue-dependent expression data,
there are few resources better than GTEx.
In this case, themedianTranscriptExpressionquery provides the necessary data.
It returns the median expression of each transcript for a gene in a given tissue.As the code and tests necessary to handle the multithreading and data grew,
maintaining both the pipeline and the source code in a single repository
became quite the challenge.
To help alleviate this,
it was decided to refactor the source code into its own repository,
allowing both the pipeline and the code to more easily adhere to best practices.Further InformationFor more information about the source code,
see ourdocumentationon ReadTheDocs.
You can learn more about the pipeline this code supportshere.
Package: gtf2seq
gtf2seqMotivation: Although tools like snpEFF have been developed for annotating and predicting the effects of variants, there is a lack of tools to show the variants in gene sequences. In order to enable research-ers to easily extract sequences from GFF files with annotations of genomic features, we developped gff2seq to fill this gap.Results: Gff2seq, an open-source toolkit, can extract genomic sequences and visualize the genomic features in word document.InstallationInstall using pip (recommended)pip install gtf2seqInstall yourselfgit clone https://github.com/caoliru/gff2seq.git
pip3 install pyfaidx==0.5.9.5
pip3 install pysam==0.16.0.1
pip3 install python-docx==0.8.10
pip3 install PyVCF==0.6.8Usageusage: gtf2seq.py [-h] -g GTF -f FASTA -t TRANSCRIPTID_LIST [--vcf VCF]
                  [--sample SAMPLE] [--exclude_intron] [-o OUTPUT]

optional arguments:
  -h, --help            show this help message and exit
  -g GTF, --gtf GTF     Genome annotation file in GTF format
  -f FASTA, --fasta FASTA
                        Genome sequences in FASTA format
  -t TRANSCRIPTID_LIST, --transcriptid_list TRANSCRIPTID_LIST
                        List of transcript IDs
  --vcf VCF             VCF files with snpEff annotation.
  --sample SAMPLE       Sample/individual ID if you want to output genotypes in the sequence for a                                               specific sample/individual.
  --exclude_intron      Exclude intron sequences in the output
  -o OUTPUT, --output OUTPUT
                        Output file in Word formatExample using test datagtf2seq.py -g test/test.gtf -f test/Zea_mays.B73_RefGen_v4.part.fa -t test/target_transcript_id.txt --vcf test/Mo17_snp.snpEff.part.vcf.gz --sample Zea_mays_Mo17 -o test.docx
Package: gtfo
Searching for flights is amazingly painful.If a first world problem leads to debilitating mental instability, is it
now not a first world problem anymore?Save me…Usage$gtfoJFKJNBorfromgtfoimportroundtriproundtrip().departing("JFK").returning("JNB").open()Flights API UsageThis module is not intended to be used programmatically. Google has aQPX Flights APIfor this
purpose, but it has some prerequisites to gain access to it, and limits
when using it.This module literally is just to programatically generate the URLs for
human-centric searches, so that you can then open them in a browser.
Package: gtfparse
gtfparseParsing tools for GTF (gene transfer format) files.Example usageParsing all rows of a GTF file into a Pandas DataFramefromgtfparseimportread_gtf# returns GTF with essential columns such as "feature", "seqname", "start", "end"# alongside the names of any optional keys which appeared in the attribute columndf=read_gtf("gene_annotations.gtf")# filter DataFrame to gene entries on chrYdf_genes=df[df["feature"]=="gene"]df_genes_chrY=df_genes[df_genes["seqname"]=="Y"]Getting gene FPKM values from a StringTie GTF filefromgtfparseimportread_gtfdf=read_gtf("Transcripts.gtf",column_converters={"FPKM":float})gene_fpkms={gene_name:fpkmfor(gene_name,fpkm,feature)inzip(df["seqname"],df["FPKM"],df["feature"])iffeature=="gene"}
Package: gtfparse-transcript-transformer
Temporary fix for gtfparse to work with polars>0.16, based onhttps://github.com/y9c/gtfparsegtfparseParsing tools for GTF (gene transfer format) files.Example usageParsing all rows of a GTF file into a Pandas DataFramefromgtfparseimportread_gtf# returns GTF with essential columns such as "feature", "seqname", "start", "end"# alongside the names of any optional keys which appeared in the attribute columndf=read_gtf("gene_annotations.gtf")# filter DataFrame to gene entries on chrYdf_genes=df[df["feature"]=="gene"]df_genes_chrY=df_genes[df_genes["seqname"]=="Y"]Getting gene FPKM values from a StringTie GTF filefromgtfparseimportread_gtfdf=read_gtf("Transcripts.gtf",column_converters={"FPKM":float})gene_fpkms={gene_name:fpkmfor(gene_name,fpkm,feature)inzip(df["seqname"],df["FPKM"],df["feature"])iffeature=="gene"}