Saravanan666/pypi-org huggingface dataset:
Package: dnac-device-list
dnac_device_listdnac_device_list is a Python library that makes your life easier when you want to programatically find out
the location name and location id of any given device that is managed by Cisco DNA Center.InstallationUse the package managerpipto install dnac_device_list.pipinstalldnac_device_listUse Case 1 (Use existing token for authorization)fromdnac_device_listimportdevice_listtoken="eyJhbRciOiJSUzI1NiIsInR5cGI6IkpXVCJ9.eyJzdWIiOiI2MTE2YmI0YWU3YjUwODZiNTLjMTI5ZjQiLCJhdXRoU291cmNlIjoiaW50ZXJuYWwiLCJ0ZW5hbnROYW1lIjoiVE5UMCIsInJvbGVzIjpbIjYxMTZiYjQ4ZTliNTA4NmI1M2MxMjlmMyJdLCJ0ZW5hbnRJZCI6IjYxMTZiYjQ4ZTliNTA4NmI1M2MxMjlmMSIsImV4cCI6MTY4ODQwMzMxMSwiaWF0IjoxNjg4Mzk5NzExLCJqdGkiOiJhNzliMjgwMC04NjdkLTRiZmQtYWJmMy02NjJiOGUzNmY4OTgiLCJ1c2VybmFtZSI6ImFkbWluIn0.hqvLkQL-07Oiwjy_RzEj5b556nlDiNpIZw-78xmEUu9FLIBuE0bWvoLgmK-2AIdAsB2bbPZ61uDmrE4YK__IINDNl6zeK6NfBGSDCzpJ9VvT_ywnLdqSpGfBArcnGcr2Wwa1DRSmGBn5uF7o0SBcE-K2--KneGsIKjZblCAPD4G1F8QwmL_FgNv6cVI-FMdhLxtYuM2pCYpE23oBmHaSIm-0xyPc71vlQiAYbZ1vnQVx64zdVNA5SPvyAvOZUY5YTixhOU0qw3rcABSk0GbVO8jZlE-QJLuC6hhh5LwM6yDnWPekWS7KPqdhXGTAEzPhxNvnAmZlXrY0nrJFJBpkkg"# initializes classdnac=device_list.Dnac(base_url="https://dnac.example.com",token=token,verify=False)# returns 'list of devices'devices=dnac.get_device_list_with_location()Use Case 2 (Use username and password for authorization)fromdnac_device_listimportdevice_list# initializes classdnac=device_list.Dnac(base_url="https://dnac.example.com",username="admin",password="Cisco123",verify=False)# returns 'list of devices'devices=dnac.get_device_list_with_location()Response json (devices variable){"response":[{"reachabilityFailureReason":"string","reachabilityStatus":"string","series":"string","snmpContact":"string","snmpLocation":"string","tagCount":"string","tunnelUdpPort":{},"uptimeSeconds":"integer","waasDeviceMode":{},"serialNumber":"string","lastUpdateTime":"integer","macAddress":"string","upTime":"string","deviceSupportLevel":"string","hostname":"string","type":"string","memorySize":"string","family":"string","errorCode":"string","softwareType":"string","softwareVersion":"string","description":"string","roleSource":"string","location":"string","role":"string","collectionInterval":"string","inventoryStatusDetail":"string","apEthernetMacAddress":{},"apManagerInterfaceIp":"string","associatedWlcIp":"string","bootDateTime":"string","collectionStatus":"string","errorDescription":"string","interfaceCount":"string","lastUpdated":"string","lineCardCount":"string","lineCardId":"string","locationName":"string","managedAtleastOnce":"boolean","managementIpAddress":"string","platformId":"string","managementState":"string","instanceTenantId":"string","instanceUuid":"string","id":"string"}]}ContributingPull requests are welcome. For major changes, please reach out to author via email first.
to discuss what you would like to change.https://github.com/alekos3/DNAC_Device_LocationLicenseMITAuthorsAlexios Nersessian
email:nersessian@gmail.com
Package: dnachisel
DNA Chisel (complete documentationhere)
is a Python library for optimizing DNA sequences with respect to a set of
constraints and optimization objectives. It comes with over 15 classes of
sequence specifications which can be composed to, for instance, codon-optimize
genes, meet the  constraints of a commercial DNA provider, avoid homologies
between sequences, tune GC content, or all of this at once!DNA Chisel also allows users to define their own specifications in Python,
making the library suitable for a large range of automated sequence design
applications, and complex custom design projects. It can be used as a Python
library, a command-line interface, or aweb application.Example of usefromdnachiselimport*# DEFINE THE OPTIMIZATION PROBLEMsome_sequence=random_dna_sequence(10000)problem=DnaOptimizationProblem(sequence=some_sequence,constraints=[AvoidPattern("BsaI_site"),EnforceGCContent(mini=0.3,maxi=0.7,window=50),EnforceTranslation(location=(500,1400))],objectives=[CodonOptimize(species='e_coli',location=(500,1400))])# SOLVE THE CONSTRAINTS, OPTIMIZE WITH RESPECT TO THE OBJECTIVEproblem.resolve_constraints()problem.optimize()# PRINT SUMMARIES TO CHECK THAT CONSTRAINTS PASSprint(problem.constraints_text_summary())print(problem.objectives_text_summary())Alternatively, DNA Chisel lets you define problems by annotating a Genbank file.
You can also define a problem by annotating directly a Genbank as follows:Seethis pagefor an overview of available specifications.InfosPIP installation:pipinstalldnachisel[reports](you can omit the[reports]suffix if you intend to use dnachisel only
for sequence optimization, without generating figures or PDF reports)Web documentation:https://edinburgh-genome-foundry.github.io/DnaChisel/Github Pagehttps://github.com/Edinburgh-Genome-Foundry/DnaChiselLive demohttp://cuba.genomefoundry.org/sculpt_a_sequenceLicense:MIT, Copyright Edinburgh Genome FoundryMore biology softwareDNA Chisel is part of theEGF Codonssynthetic biology software suite for DNA design, manufacturing and validation.
Package: dnada
DNAdaDNAda is a web application that integrates thej5DNA assembly software with robotic liquid handlers.BackgroundJ5 is a powerful DNA assembly software that can be used to design
and optimize DNA assembly protocols. However, it is not directly compatible with
robotic liquid handlers. DNAda is a web/command-line application
that integrates j5 with robotic liquid handlers by converting a
j5 assembly design into a series of liquid handler compatible instructions.
This enables a user without progamming experience to design DNA assembly
protocols on a user-friendly
canvas,DeviceEditor,
and then convert the design using J5 and subsequently DNAda into a series
of instructions that can be executed on a liquid handler.CLI InstallationNote, it is highly recommended to use a virtual environment to install the dependencies.For example,wget"https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-$(uname)-$(uname-m).sh"bashMambaforge-$(uname)-$(uname-m).shsource~/mambaforge/bin/activate
mambacreate-y-ndnada
condaactivatednada
mambainstall-ypython==3.11pipinstalldnadaAlternatively, setup from the source code by runninggitclonehttps://github.com/JBEI/dnada.gitcddnada/backend/app
pythonsetup.pyinstallNote, there iscurrently a bugin autoprotocol-python. To temporarily resolve this bug until it gets patched, identify the
location of the autoprotocol library identified in your virtual environment and apply the
fix-oligosynthesizeolig-serialization.patch file. For example,cd~/mambaforge/envs/dnada/lib/python3.11/site-packages/
patch-p1<~/dnada/backend/app/fix-oligosynthesizeoligo-serialization.patchQuick StartThere is a sample J5 design file available in theexamples/directory in the github repo.
After installing the DNAda CLI through pip or github, to run DNAda on that design file,
execute:cddnada/examples
dnada_cliexample_j5_output.zipAfter a few seconds you should see a new.ziparchive generated with the
nameautomation_instructions.zip.
Package: dnadigest
Galaxy tool with the following aims:digest DNA into fragments, produce FASTA output of thatplot restriction digests in easy to use SVG formatrun “hypothetical gels” to help biologists understand the output of
these fancy computer thingsoptimise restrictions with multiple genomes in order to easily
determine enzymes for unique resetriction patternsRunningpython bin/digest_dna.py test.fa Bsp6I,Bsp13I,DseDIHistory0.1.0 (2015-03-16)Finished implementation of graphics drawer
Package: dna-features-viewer
DNA Features Viewer is a Python library to visualize DNA features, e.g. from GenBank or Gff files:DNA Features Viewer can plot sequence maps linearly or circularly, with or without nucleotide sequence and amino-acid sequences. The plotter automatically produces clear plots even for sequences with many overlapping features and long labels. The library plays well with Matplotlib and Biopython, and the figures can be saved in different formats (PNG, JPEG, SVG, PDF), e.g. for report generation or LIMS interfaces.InfosPIP installation:pipinstalldna_features_viewerWeb documentation:https://edinburgh-genome-foundry.github.io/DnaFeaturesViewer/Github Pagehttps://github.com/Edinburgh-Genome-Foundry/DnaFeaturesViewerLive demohttp://cuba.genomefoundry.org/plot-sequence-featuresLicense:MIT, Copyright Edinburgh Genome FoundryMore biology softwareDNA Features Viewer is part of theEGF Codonssynthetic biology software suite for DNA design, manufacturing and validation.
Package: dnaio
dnaio processes FASTQ and FASTA filesdnaiois a Python 3.8+ library for very efficient parsing and writing of FASTQ and also FASTA files.
The code was previously part of theCutadapttool and has been improved significantly since it has been split out.Example usageThe main interface is thednaio.openfunction:import dnaio

with dnaio.open("reads.fastq.gz") as f:
    bp = 0
    for record in f:
        bp += len(record)
print(f"The input file contains {bp/1E6:.1f} Mbp")For more, see thetutorialandAPI documentation.InstallationUsing pip:pip install dnaio zstandardzstandardcan be omitted if support for Zstandard (.zst) files is not required.Features and supported file typesFASTQ input and outputFASTA input and outputBAM inputCompressed input and output (.gz,.bz2,.xzand.zstare detected automatically)Paired-end data in two filesInterleaved paired-end data in a single fileFiles with DOS/Windows linebreaks can be readFASTQ files with a second header line (after the+) are supportedLimitationsMulti-line FASTQ files are not supportedFASTQ and BAM parsing is the focus of this library. The FASTA parser is not as optimizedLinksDocumentationSource codeReport an issueProject page on PyPI
Package: dna-kmer
DNA string k-mer generatorExample:def dna_token(dna_string, kmer, step)


dna = "ACTGTCGTACAGTGACCAGTGGTAGT"
    kmerized_dna = dna_token(dna, 5, 1)ACTGTCGTACAGTGACCAGTGGTAGTACTGT CTGTC TGTCG GTCGT TCGTA CGTAC GTACA TACAG ACAGT CAGTG AGTGA GTGAC TGACC GACCA ACCAG CCAGT CAGTG AGTGG GTGGT TGGTA GGTAG GTAGT
Package: dnaMD
do_x3dnagenerates large amount of data and analyzing these data is difficult.
Therefore,dnaMDis developed to analyze data obtained fromdo_x3dna. It contains
set of tools to analyze the data.dnaMDis written in Python and it is also available as Python module.
It can be used in Python scripting for fast and flexible analysis ofdo_x3dnadata.For detailed documentation about the dnaMD, please visitdo_x3dna.
Package: dnanew
DNA AUDIT TOOLDNA Audit tool helps you to check whether the application built on AWS is following the AWS Well-Architected framework by validating it against
various AWS services security requirements and the best practices. Generates report to validate the security requirements and security best practices.AWS Hardening Standards & Best Practiceshttps://codaglobal.atlassian.net/l/cp/UP1BxJTrAWS Tagging Standardshttps://codaglobal.atlassian.net/l/cp/oj0NgsdbAWS Naming Standardshttps://codaglobal.atlassian.net/l/cp/s99nYLECAudit tool setupThe project basically uses boto client to connect to the aws services.Update the session credentials in the terminal.Specify the region name if you need to perform the audit for services in a specific region by mentioning the region name as argument while running the program.If no region is specified us-east-1 is taken as default region and audit checks are performed for the services in us-east-1.If you need to check tags. Update the Config.Json file by mentioning the tags in the account tags provided.Audit Tool ExecutionCreating Virtual Environmentpython3 -m venv venvActivating the virtual environmentsource venv/bin/activateInstalling the dependencies in the virtual environmentpip install -r requirements.txtRun the following commandpython3 src/main.py --region {region_name}Test Cases ExecutionnosetestsFinal ReportThe overall report is provided as a HTML document.sample report
Package: dnaold
DNA AUDIT TOOLDNA Audit tool helps you to check whether the application built on AWS is following the AWS Well-Architected framework by validating it against
various AWS services security requirements and the best practices. Generates report to validate the security requirements and security best practices.AWS Hardening Standards & Best Practiceshttps://codaglobal.atlassian.net/l/cp/UP1BxJTrAWS Tagging Standardshttps://codaglobal.atlassian.net/l/cp/oj0NgsdbAWS Naming Standardshttps://codaglobal.atlassian.net/l/cp/s99nYLECAudit tool setupThe project basically uses boto client to connect to the aws services.Update the session credentials in the terminal.Specify the region name if you need to perform the audit for services in a specific region by mentioning the region name as argument while running the program.If no region is specified us-east-1 is taken as default region and audit checks are performed for the services in us-east-1.If you need to check tags. Update the Config.Json file by mentioning the tags in the account tags provided.Audit Tool ExecutionCreating Virtual Environmentpython3 -m venv venvActivating the virtual environmentsource venv/bin/activateInstalling the dependencies in the virtual environmentpip install -r requirements.txtRun the following commandpython3 src/main.py --region {region_name}Test Cases ExecutionnosetestsFinal ReportThe overall report is provided as a HTML document.sample report
Package: dnaold1
DNA AUDIT TOOLDNA Audit tool helps you to check whether the application built on AWS is following the AWS Well-Architected framework by validating it against
various AWS services security requirements and the best practices. Generates report to validate the security requirements and security best practices.AWS Hardening Standards & Best Practiceshttps://codaglobal.atlassian.net/l/cp/UP1BxJTrAWS Tagging Standardshttps://codaglobal.atlassian.net/l/cp/oj0NgsdbAWS Naming Standardshttps://codaglobal.atlassian.net/l/cp/s99nYLECAudit tool setupThe project basically uses boto client to connect to the aws services.Update the session credentials in the terminal.Specify the region name if you need to perform the audit for services in a specific region by mentioning the region name as argument while running the program.If no region is specified us-east-1 is taken as default region and audit checks are performed for the services in us-east-1.If you need to check tags. Update the Config.Json file by mentioning the tags in the account tags provided.Audit Tool ExecutionCreating Virtual Environmentpython3 -m venv venvActivating the virtual environmentsource venv/bin/activateInstalling the dependencies in the virtual environmentpip install -r requirements.txtRun the following commandpython3 src/main.py --region {region_name}Test Cases ExecutionnosetestsFinal ReportThe overall report is provided as a HTML document.sample report
Package: dnaold90
DNA AUDIT TOOLDNA Audit tool helps you to check whether the application built on AWS is following the AWS Well-Architected framework by validating it against
various AWS services security requirements and the best practices. Generates report to validate the security requirements and security best practices.AWS Hardening Standards & Best Practiceshttps://codaglobal.atlassian.net/l/cp/UP1BxJTrAWS Tagging Standardshttps://codaglobal.atlassian.net/l/cp/oj0NgsdbAWS Naming Standardshttps://codaglobal.atlassian.net/l/cp/s99nYLECAudit tool setupThe project basically uses boto client to connect to the aws services.Update the session credentials in the terminal.Specify the region name if you need to perform the audit for services in a specific region by mentioning the region name as argument while running the program.If no region is specified us-east-1 is taken as default region and audit checks are performed for the services in us-east-1.If you need to check tags. Update the Config.Json file by mentioning the tags in the account tags provided.Audit Tool ExecutionCreating Virtual Environmentpython3 -m venv venvActivating the virtual environmentsource venv/bin/activateInstalling the dependencies in the virtual environmentpip install -r requirements.txtRun the following commandpython3 src/main.py --region {region_name}Test Cases ExecutionnosetestsFinal ReportThe overall report is provided as a HTML document.sample report
Package: dnaold91
DNA AUDIT TOOLDNA Audit tool helps you to check whether the application built on AWS is following the AWS Well-Architected framework by validating it against
various AWS services security requirements and the best practices. Generates report to validate the security requirements and security best practices.AWS Hardening Standards & Best Practiceshttps://codaglobal.atlassian.net/l/cp/UP1BxJTrAWS Tagging Standardshttps://codaglobal.atlassian.net/l/cp/oj0NgsdbAWS Naming Standardshttps://codaglobal.atlassian.net/l/cp/s99nYLECAudit tool setupThe project basically uses boto client to connect to the aws services.Update the session credentials in the terminal.Specify the region name if you need to perform the audit for services in a specific region by mentioning the region name as argument while running the program.If no region is specified us-east-1 is taken as default region and audit checks are performed for the services in us-east-1.If you need to check tags. Update the Config.Json file by mentioning the tags in the account tags provided.Audit Tool ExecutionCreating Virtual Environmentpython3 -m venv venvActivating the virtual environmentsource venv/bin/activateInstalling the dependencies in the virtual environmentpip install -r requirements.txtRun the following commandpython3 src/main.py --region {region_name}Test Cases ExecutionnosetestsFinal ReportThe overall report is provided as a HTML document.sample report
Package: dnaplotlib2
DNAplotlibDNAplotlib is a library that enables highly customizable visualization of individual genetic constructs and libraries of design variants. It can be thought of in many ways as matplotlib for genetic diagrams. Publication quality vector-based output is produced and all aspects of the rendering process can be easily customized or replaced by the user. DNAplotlib is capable of SBOL Visual compliant diagrams in addition to a format able to better illustrate the precise location and length of each genetic part. This alternative "traced-based" visualization method enables direct comparison with nucleotide-level information such as RNA-seq read depth or other base resolution measures. While it is envisaged that access will be predominantly via the programming interface, several easy to use text-based input formats can be processed by a command-line scripts to facilitate broader usage. DNAplotlib is cross-platform and open-source software released under the OSI OSL-3.0 license.If you make use of DNAplotlib in any publications, we kindly ask that the following paper is cited:Der B.S., Glassey E., Bartley B.A., Enghuus C., Goodman D.B., Gordon D.B., Voigt C.A., Gorochowski T.E., "DNAplotlib: programmable visualization of genetic designs and associated data",ACS Synthetic Biology, 2016. (DOI: 10.1021/acssynbio.6b00252)DependenciesNumPymatplotlibpySBOL (optional)InstallationThe DNAplotlib library is contained within thednaplotlib.pyfile in thelibdirectory and requires Python 2.6 and matplotlib 1.2 or newer. To install add the location of this file to yourPYTHONPATHand you are good to:import dnaplotlibGetting StartedWe provide an extensive gallery of use cases for DNAplotlib in thegallerydirectory. Click on a thumbnail below to go directly to the example code:Genetic Designs and AnnotationNew Part Types and RegulationTrace-based RenderingDynamics and EvolutionVariant Libraries
Package: dnaseq-genbit
GenBitOperate on DNA/RNA genetic sequences using a computer, the same way protein biosynthesis would happen within a cell. For instance, a given DNA sequence can be converted into an RNA sequence, and then an amino acid sequence. The full name of the protein then generated can also be found. You can also find the complentary genetic sequence, of the non-coding strand involved.Coming SoonThe ability to randomly mutate sequencesRandomly generate sequencesFinding the non-chemical name of the protein, and its functionalityBuilding a system of proteins that can work together (protein simulations)UsageInstall the package withpip install dnaseq-genbit. Now, it can be imported withimport genbit, and you now have access to all the methods in GenBit. Sequences are represented by strings, and it is these strings that are operated on.Exampleimportgenbitaa_seq='VLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYRXXVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHFDLSHGSAQVKGHGKKVADALTNAVAHVDDMPNALSALSDLHAHKLRVDPVNFKLLSHCLLVTLAAHLPAEFTPAVHASLDKFLASVSTVLTSKYRXXVHFTAEEKAAVTSLWSKMNVEEAGGEALGRLLVVYPWTQRFFDSFGNLSSPSAILGNPKVKAHGKKVLTSFGDAIKNMDNLKPAFAKLSELHCDKLHVDPENFKLLGNVMVIILATHFGKEFTPEVQAAWQKLVSAVAIALAHKYXXVHFTAEEKAAVTSLWSKMNVEEAGGEALGRLLVVYPWTQRFFDSFGNLSSPSAILGNPKVKAHGKKVLTSFGDAIKNMDNLKPAFAKLSELHCDKLHVDPENFKLLGNVMVIILATHFGKEFTPEVQAAWQKLVSAVAIALAHKYXX'# Amino Acid Sequencerna_seq=genbit.amino_to_rna(aa_seq)# RNA Sequencewords_amino_seq=genbit.chemical_name_amino_chain(aa_seq)# Chemical Name of Amino Acid Sequencedna_seq=genbit.chemical_name_to_dna(words_amino_seq)# DNA Sequencecodon_dna_seq=genbit.codons(dna_seq)# Codon Sequence
Package: dna-serpent
SerpentExplore DNA data with SerpentSerpent is an exploration into DNA and RNA sequences, nucleotide
bases, codons, amino acids and genome data.Tools providedWork with FASTA files and sequencesserpent cat: concatenate and print FASTA filesserpent find: find FASTA files in directoriesserpent find -s: find and print FASTA sequences in files and directoriesConvert dataserpent encode: Convert data intobase 64encoded representationserpent decode: Map codons into numbers 0...64Analyse and plot FASTA data visuallyserpent fft: plot FFTs on DNA and RNA sequencesserpent hist: plot histogram statisticsserpent image: visualise DNA and RNA data as imagesserpent seq: plot sequence count statisticsStatisticsserpent codons: Print codon statisticsserpent pep: Print peptide statisticsSeeserpent -hfor all subcommands andserpent <subcommand> -hfor options!MotivationI have wanted to explore DNA data in order to to learn and maybe
invent some compression algorithms for DNA data for about two decades.
Package: dnassembly
# DNAssemblyYet another DNA manipulation package, except this one does exactly what I wantDNAssembly is a framework that lets you do your cloning as you would in the wet lab, but on your computer. In place of
colorless liquids in test tubes, DNAssembly will take your plasmid files in your favorite format (Genbank, Snapgene)
and run them through an assembly protocol to produce fully annotated cloning products. All input sequences are verified
to avoid common cloning pitfalls.DNAssembly is initially implemented to perform Modular Golden Gate Cloning as described in “A Highly Characterized Yeast
Toolkit for Modular, Multipart Assembly” (Lee et al. 2013).