Saravanan666/pypi-org huggingface dataset:
Package: rnamoip
RNAMoIPSetupRNAMoIP can be installed via Pypi with the following command:pipinstallrnamoipYou will also need ViennaRNA installed locally:wgethttps://www.tbi.univie.ac.at/RNA/download/sourcecode/2_6_x/ViennaRNA-2.6.4.tar.gz
tar-zxvfViennaRNA-2.6.4.tar.gzcdViennaRNA-2.6.4
./configure
make
sudomakeinstallPython Environment (Optional)Use your favorite virtual environment for Python. The Pythonvenvmodule is recommended if you don't have any.To create a Python version withvenv:python3-mvenvrnamoip-envAfterward, you can use that environment with the following command:sourcernamoip-env/bin/activatePython dependenciesTo install the Python dependencies, run the following:pipinstall-rrequirements.txtThe Python bindings are already provided in the requirements file. Please note that RNAMoIP was built using ViennaRNAv2.6.4. For more information, check forViennaRNA Documentation.IP Model SolverMultiple solvers are supported to solve the RNAMoIP equations.CP-SAT (Recommended)Cp-SAT is a free, open-source IP solver from the OR-tools Package, made by Google. For more information, visit their GitHubhere.CBCCBC (Coin-or branch and cut) is a free, open-source IP solver availablehere. It can be useful as an alternative to Gurobi, although considerably slower. It is automatically provided by the MIP python library for 64-bit Intel architecture. For more details, like manual installation, please refer to theMIP doc.Gurobi (Need License)To install, follow the directiveshere. Note that afree academic licensecan be used for a renewable two-month period.How to executeTo execute RNAMoIP, you can run themain.pywith the following command:cdsrc
python-mrnamoip.main--sequence"AAGGUUCC"--structure"........"You can also provide a more detailed configuration file. By default, it will use the base configuration located insrc/data/configuration.json.
You can also run the prediction through thePredictionPython class:# From agrsfromrnamoip.predicterimportPredicterPredicter(rna_sequence='AAGGUUCC',secondary_structure='........',alpha=0.1,).iterate()# With a config file path or dictPredicter(configuration_file='my/path/to/configuration.json').iterate()For more use cases, withconfiguration details, please see theUsage Documentation.Motif DatabasesRNAMoIP supports two types of motif databases:(default) The RIN database, parser of typerin. RNAMoIP already provides a rins database of all local rins.The original RNAMoIP database, parser of typedesc, is availablehere.You need to specify the path of the motif database accordingly in themotifs_pathproperty, and the motif type with theparserproperty. For more info, see theUsage Documentation.ScriptsUseful scripts related to the project can be found under thescripts folder.BenchmarkTo run a batch of multiple prediction RNAMoIP, with all chains that what used in the benchmark.
Note that a dependency (forgi) doesn't support Python 3.11 yet on OSX, so you might need Python 3.10.pipinstall-rrequirements-analysis.txtpython-mrnamoip.multi_batch_analysis--chains_source="../data/chain/chains.json"
Package: rnapykin
Python bindings forrnapkin!:snake: :crab:Rnapkin is a fast, convenient CLI utility for drawing RNAs that produces stylish SVGs.
These Python bindings provide an easy way to use rnapkin's functionality directly from your Python scripts.This is an early implementation that currently only exposes therna2svgfunction.
It takes an RNA fold inrnapkincompliant format and returns the corresponding
SVG as a string.Installationpip install rnapykinQuick Examplefromrnapykinimportrna2svggorgeous_rna="""UUAUAGGCGAUGGAGUUCGCCAUAAACGCUGCUUAGCUAAUGACUCCUACCAGUAUCACUACUGGUAGGAGUCUAUUUUUUU.....(((((......)))))......(((....)))....((((((((((((((....))))))))))))))........."""# rna / theme / rotation in degrees / background opacity / horizontal flip / vertical flipsvg=rna2svg(gorgeous_rna,"dark",0,1.,False,False)# do with it what you want. Save it, embed it in HTML, whatevs c:withopen("gorgeous_rna.svg","w")asf:f.write(svg)
Package: rnasa
rnasaGene Expression Level Calculator for RNA-seqInstallation$pipinstall-UrnasaDependent commands:pigzpbzip2bgzipsamtools(andplot-bamstats)javafastqctrim_galoreSTARrsem-prepare-referencersem-refseq-extract-primary-assemblyrsem-calculate-expressionDocker imagePull the image fromDocker Hub.$dockerimagepulldceoy/rnasaUsageCalculate gene expression levelsinput filesoutput filesFASTQ (Illumina)TSV (or GCT)Download and process resource data.$rnasadownload--genome=GRCh38--dest-dir=/path/to/refCalculate TPM (transcripts per million) values from FASTQ files.$rnasacalculate\--workers=2\--dest-dir=/path/to/output\/path/to/ref/GRCh38\/path/to/sample1_fastq_prefix\/path/to/sample2_fastq_prefix\/path/to/sample3_fastq_prefixThe command search for one (single-end) or two (paired-end) input FASTQ files by prefix.Standard workflow:Trim adapterstrim_galoreMap reads and calculate TPM valuesSTARrsem-calculate-expressionCollect QC metricsfastqcsamtoolsExtract TPM values from RSEM results files, and consolidate them into TSV files.$rnasaextract--dest-dir=./path/to/output/rsemIf--gctis passed,rnasa extractcreates output files in GCT format.Runrnasa --helpfor more information.
Package: rnaseeker
RNAseekerRNA-seq scripts and librariesJosh Tompkinjtompkin-dev@proton.mehttps://github.com/jtompkin/rnaseekerInstall with pippip3installrnaseekerCommand line programsgo_filter: Filter gProfiler output and format for Revigornaseekergo-filter[-h][-v][-cTERM_COLUMN][-dIN_DELIMITER][-oOUT_FILE][-pPVAL_COLUMN][-iID_COLUMN][-sOUT_DELIMITER][--no-format][--header][-fFILTER_TERMS][--filter-fileFILTER_PATH]gProfiler_filefasta_filter: Filter fasta sequences by length and 'N' contentrnaseekerfasta-filter[-h][-oOUT_PATH][-lLINE_LENGTH]fasta_pathminimum_basepairsfasta_split: Split fasta/fastq filesrnaseekerfasta-split[-h][-v][-iINPUT][-f{fasta,fastq}][-s][-p[PREFIX]][--header-prefix[REGEX]][-dDIRECTORY][-eEXTENSION]numberPython librariessequencesequence_io: Manipulate sequence files and store sequence information
Package: rnaseqc
RNA-SeQC Python utilitiesThis module contains utility code for RNA-SeQCInstallingFrom pip:pip install rnaseqcFrom the git repo:pip install -e python(Invoke from root of git repo)UsageThis does not install a console entrypoint. You can invoke the utilities in one of three ways:From the main module:python3 -m rnaseqc ...Calling the target module:python3 -m rnaseqc.example ...Calling scripts directly:python3 python/rnaseqc/example.pyUtilitiesThernaseqcmodule contains 5 main utilities. To get more help with each utility,
invoke the utility with the-hor--helpoptionAggregationAggregates RNA-SeQC outputs from multiple samplespython3 -m rnaseqc aggregate [-h] [--parquet] [-o OUTPUT_DIR] results_dir prefixJupyter NotebooksCreates a jupyter notebook with several figures for comparing samplespython3 -m rnaseqc notebook [-h] [-t TPM] [-i INSERT_SIZE] [-c COHORT] [-d DATE] metrics outputFiguresGenerates figures from an aggregated RNA-SeQC metrics tablepython3 -m rnaseqc report [-h] [--tpm TPM] [--insert-size INSERT_SIZE] [--cohort COHORT] [--output-dir OUTPUT_DIR] [--dpi DPI] metrics prefixInsert Size distributionsGenerates a BED file with intervals used by RNA-SeQC for estimating a sample's insert size distributionpython3 -m rnaseqc insert-size [-h] [--min-length MIN_LENGTH] [--min-mappability MIN_MAPPABILITY] [--output-dir OUTPUT_DIR] gtf_path mappability_bigwig prefixExon remappingConvert exon names in an*.exon_reads.gctfile from RNA-SeQC 2.X.X to match names
as reported by RNA-SeQC 1.1.9python3 -m rnaseqc legacy-exons gct gtf
Package: rnaseqdata
ernav2_seqdataA new data type known as SeqData is designed for RNA-seq data analysis. The data type is designed for data integration from various sources and dimensions:Expression of RNA is measured by read counts of transcripts. A typical bioinformatics pipeline of mRNA-seq determines reads counts (RC) of transcripts. The RCs are typically 2-D table, of which samples are in rows, and transcripts (or genes) are in columns, or in the reverse. After that, the RC table would be normalized as FPM or FPKM or somewhere else by a certain normalized method. The next, co-founding factors among samples would be removed using a certain method namely DESEQ2 or EdgeR etc. Moreover, those data would be transformed into various table, namely log, or partitioned into some subset. Bioinformatician should manage all those data sets during statistical anlaysis.Biological scientists may be more care about significance of mRNA-seq data analysis, and what those significance reveals. In this case, sample informations, or patient information, or features of samples (namely single cells) shall be considered. Moreover, aside from transcript ID or Gene ID, other annotations would be integrated, for example, genomic annoations namely chromosome locus, protein annotations namely domain identification would be integrated, too. Those annoation data may not be used in statistical process, but really needed for further study.SeqData is tree structure. The root contains data of phenotypes and annotations. Each node contains various attributes including X in m x n, and var (statistical aggregations). Nodes inherite the attributes of the root nodes. Data of children nodes is determined by those of parent nodes.installationIt is convenient to install the repository using pip. The package could be found atPythone Package Index.pip install --upgrade rnaseqdataDevelopmentgit clone git@github.com:Tiezhengyuan/ernav2_seqdata.git
cd ernav2_seqdatacreate virtual environmentvirtualenv venv
source venv/bin/activate
pip install -r requirements.txtUnit testingpytest tests/unittestsquick tourialIn Python3from rnaseqdata import RootData, SeqData
import numpy as np
import pandas as pdCreate SeqDataroot = RootData()
c = SeqData(root)
c.put_data('test', np.eye(3), root)
c.to_df('test)0    1    2
 0  1.0  0.0  0.0
 1  0.0  1.0  0.0
 2  0.0  0.0  1.0
Package: rnaseqflow
What Is It?An open-source Python library to make preprocessing of RNAseq files more convenientCircleCI build status:TravisCI build status:Complete documentation available onRead the DocsCopyright and LicenseFor the complete copyright and licensing information see LICENSECopyright 2015 Justin PalpantThis file is part of the RNAseqflow program.RNAseqflow is free software: you can redistribute it and/or modify it under the
terms of the GNU General Public License as published by the Free Software
Foundation, either version 3 of the License, or (at your option) any later
version.RNAseqflow is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
PARTICULAR PURPOSE. See the GNU General Public License for more details.You should have received a copy of the GNU General Public License along with
RNAseqflow. If not, seehttp://www.gnu.org/licenses/.
Package: rnaseqhs
rnaseqhs=========overview---------rnaseqhs can do bioinformatics analysis for RNA_seq data and generate clean BAM/SAM result from HISAT2, GTF result from Stringtie and featureCounts result.rnaseqhs is available under the terms of the MIT license (see the file ``LICENSE``)pre-requirements-----------------1. 'gzip','fastx_trimmer','fastqc','cutadapt','fastq_quality_filter','hisat2','stringtie','samtools (v1.3.1)','bedtools (v2.19.1)' in $PATH.2.  hisat2 built genome index, transcriptome index, and gtf.Installation-------------1. tar zxvf rnaseqhs-<version>.tar.gz2. cd rnaseqhs-<version>3. python setup.py install --userUsage------1. use it as module in python console ::>>>import rnaseqhs>>>rnaseqhs.rnaseqhs.main(<Arguments>)Arguments are ::>>>rnaseqhs.rnaseqhs.main(NDIR,OUTDIR,PHRED,QCCHECK,TRIM,LASTKEEP,RMADAPT, LADAPTER, RADAPTER,OVERLAP,MINLEN,REMOVEN,NCUTOFF,FILTQ,MINQ,PMINQ,QCSTAT,MAPPING,HISAT2INDEX,ORIENTATIONS,RNASTRANDNESS,GTF,RAWCOVER,GENOMEBED,WINDOWSIZE])2. use it as command line in bash ::<installed-path>/rnaseqhsb <options>Options are ::usage: rnaseqhs [-h] [-i INDIR] [-o OUTDIR] [-P PHRED] [-Q QCCHECK] [-T TRIM][-l LASTKEEP] [-r RMADAPT] [-L LADAPTER] [-R RADAPTER][-O OVERLAP] [-m MINLEN] [-N REMOVEN] [-c NCUTOFF] [-F FILTQ][--minQ MINQ] [--pminQ PMINQ] [-q QCSTAT] [-M MAPPING][--hisat2index HISAT2INDEX] [--orientations ORIENTATIONS][--rnastrandness RNASTRANDNESS] [--gtf GTF][--drawCover DRAWCOVER] [--genomebed GENOMEBED][--windowsize WINDOWSIZE]optional arguments:-h, --help            show this help message and exit-i INDIR, --indir INDIRfastq files path-o OUTDIR, --outdir OUTDIRoutput path-P PHRED, --phred PHREDphred score used in platform [33]-Q QCCHECK, --qccheck QCCHECKdo quality check [true]-T TRIM, --trim TRIM  trim given fastq short reads as --lastkeep defined-l LASTKEEP, --lastkeep LASTKEEPwith "trim" option, last bases to keep-r RMADAPT, --rmadapt RMADAPTremove adapter [true]-L LADAPTER, --ladapter LADAPTERleft adapter [AGATCGGAAGAGC]-R RADAPTER, --radapter RADAPTERright adapter [AGATCGGAAGAGC]-O OVERLAP, --overlap OVERLAPIf the overlap between the read and adapter is shorterthan the overlap length, the read will NOT bemodified. [6]-m MINLEN, --minlen MINLENDiscard trimmed reads that are shorter than "minlen"[75]-N REMOVEN, --removeN REMOVENremove "N" bases [true]-c NCUTOFF, --Ncutoff NCUTOFFwith "removeN" option, N cutoff [0.1]-F FILTQ, --filtQ FILTQFilters sequences based on quality [true]--minQ MINQ           Minimum quality score to keep [20]--pminQ PMINQ         Minimum percent of bases [80]-q QCSTAT, --qcStat QCSTATgenerate QC statistic plot for seq-M MAPPING, --mapping MAPPINGread mapping [true]--hisat2index HISAT2INDEXhisat2 index--orientations ORIENTATIONSorientations--rnastrandness RNASTRANDNESSrna strandness--gtf GTF             gtf file for annotation--drawCover DRAWCOVERcoverage of genome region [true]--genomebed GENOMEBEDcoverage genome bed file--windowsize WINDOWSIZEcoverage window size [500000]Links-----* `Project homepage <https://git-r3lab.uni.lu/zhi.zhang/rnaseqhs>`_* `Github page <https://git-r3lab.uni.lu/zhi.zhang/rnaseqhs>`_written by Zhi Zhang.
Package: rnaseqmixture
RNAseqmixtureA python module to correct (ajust/deconvolute) for contamination of primary cell RNAseq with
other cell types (eg. Macrophages).No RNAseq of primary cells is pure - there are always other cell types sequenced within your sample.
Given your purest sample(s) (=reference) and samples consisting just of the likely contaminations, this module
attempts to correct for the contamination.How much contamination is present is assessed based on a number of genes that are specific
for your contamination - they should not show any expression in the pure reference.For details see,
Reinartz, Finkernagel et al., Genome Biol . 2016 May 23;17(1):108. doi: 10.1186/s13059-016-0956-6.
A transcriptome-based global map of signaling pathways in the ovarian cancer microenvironment associated with clinical outcome
Package: rna-seq-tools
seq_toolsa short python tool for working with sequences in dataframeshow to installpipinstallrna_seq_toolshow to useseq_toolsis a python package that contains a few functions for working with sequences in
dataframes. If there is a single sequence results are printed. If input is a csv then a new csv is
created with the results. Default output is "output.csv" but can be changed with the-oflag.$seq_tools--help
Usage:seq_tools[OPTIONS]COMMAND[ARGS]...asetscriptstomanipulatesequencesincsvfiles

Options:--helpShowthismessageandexit.

Commands:addaddasequenceto5' and/or 3'eccalculatetheextinctioncoefficientforeachsequenceedit-distancecalculatetheeditdistanceofalibraryfoldfoldrnasequencesmwcalculatethemolecularweightforeachsequencerccalculatereversecomplementforeachsequenceto-dnaconvertrnasequence(s)todnato-dna-templateconvertrnasequence(s)todnatemplate,includesT7...to-fastageneratefastafilefromcsvto-opoolgenerateoligopoolfilefromcsvto-rnaconvertrnasequence(s)todnatranscribeconvertdnasequence(s)tornatrimtrim5'/3'endsofsequencesaddAdds a sequence to the 5' and/or 3' end of a sequence.$seq_toolsadd-p5"AAAA""GGGGUUUUCCCC"SEQ_TOOLS.get_input_dataframe-INFO-readingsequenceGGGGUUUUCCCC
SEQ_TOOLS.handle_output-INFO-output->
nameseq
sequenceAAAAGGGGUUUUCCCC
Name:0,dtype:objectecCalculate the extinction coefficient for each sequence.$seq-toolsec"GGGGUUUUCCCC"SEQ_TOOLS.get_input_dataframe-INFO-readingsequenceGGGGUUUUCCCC
SEQ_TOOLS.handle_ntype-INFO-determiningnucleicacidtype:RNA
SEQ_TOOLS.handle_output-INFO-output->
nameseq
sequenceGGGGUUUUCCCC
extinction_coeff109500Name:0,dtype:objectedit-distanceCalculate the edit distance of a library. On average how different each sequence
is from the rest of the library.seq-toolsedit-distancetest/resources/test.csv
SEQ_TOOLS.edit_distance-INFO-editdistance:17.666666666666668foldFold rna sequences.$seq-toolsfold"GGGGUUUUCCCC"SEQ_TOOLS.get_input_dataframe-INFO-readingsequenceGGGGUUUUCCCC
SEQ_TOOLS.handle_output-INFO-output->
nameseq
sequenceGGGGUUUUCCCC
structure((((....))))mfe-5.9
ens_defect0.38
Name:0,dtype:objectto-dnaConvert all sequences to DNA i.e. replace T with U.$seq_toolsto-dna"GGGGUUUUCCCC"SEQ_TOOLS.get_input_dataframe-INFO-readingsequenceGGGGUUUUCCCC
SEQ_TOOLS.to_dna-INFO-convertedsequence:GGGGTTTTCCCCother non commandlinestructure representationfromseq_toolsimportSequenceStructurestruct=SequenceStructure("GGGGUUUUCCCC","((((....))))")
Package: rnasieve
RNA-SieveRNA-Sieve is a method for the deconvolution of bulk cell samples via single-cell RNA expression data.Associated WorkOur preprint is currently available athttps://www.biorxiv.org/content/10.1101/2020.10.01.322867v1.If you find RNA-Sieve useful, please cite our work at:RNA-Sieve: A likelihood-based deconvolution of bulk gene expression data using single-cell referencesDan D. Erdmann-Pham, Jonathan Fischer, Justin Hong, Yun S. SongbioRxiv 2020.10.01.322867; doi:https://doi.org/10.1101/2020.10.01.322867InstallationFor Python 3, we recommend that you installrnasieveviapip.$pip3installrnasieveExample UsageFor example usage, please referencethe example Jupyter notebookfor Python 3 usage,
orthe Mathematica notebookfor Mathematica usage.The core algorithm is calledfind_mixtures/findMixtureswhich takes in a vector of bulk expressions to be deconvolved and reference matrices of means, variances, and sample counts.
Currently, only the Python library takes allows for multiple bulks to be jointly deconvolved with a single set of reference matrices.
Package: rnaspace
The platform allows running in an integrated environment a varietyof ncRNA gene finders, to explore results with dedicated tools for
comparison, visualization and edition of putative ncRNAs and to
export them in various formats (FASTA, GFF, RNAML).Seehttp://rnaspace.orgto have an idea of an open web site
without user authentification.rnaspacerequiresCherryPyandCheetah.
Package: rnavelocity-genericdiff
cs207-FinalProject (Group #35)Group MembersTop Coder Kitty MLTamilyn	Chen (Top Coder)Kar-Tong Tan (Kitty)Mark Lock (ML)Packagesgenericdiff - forward mode automatic differentiationrnavelocity - tool to determine rna velocityFor documentation and vignettes (how to use) please consult the docs folderBadgesTravisCodecov
Package: rnaviewparser
rnaviewparseris a simple parser forRNAVIEW_ filename.pdb.out files... _RNAVIEW:http://ndbserver.rutgers.edu/ndbmodule/services/download/rnaview.html.. _ply:https://www.dabeaz.com/ply/"It usesply_ for the lexing/parsing bit and python dataclasses to store the data.
It allows an export to CSV files.It works with Python 3.7.:Author: Maria Climent-Pommeret (Chopopope)
:License: MIT License
:Homepage:https://gitlab.climent-pommeret.red/Chopopope/rnaviewparserInstallatingPlease install in a virtual environment that uses Python3.7 by typing::pip install rnaviewparserUsage exampleConsider this::In[1]: from rnaviewparser import rnaviewparser

In[2]: basepairs = rnaviewparser.RnaviewParser("~/playground/tr0001.pdb.out").parse()

In[3]: factory = basepairs.generate_interactions()

In[4]: wh = factory["W/H"]

In[5]: wh.pretty()
Out[5]:
+------------------+-------------+-------+
| Interaction type | Orientation | Total |
+------------------+-------------+-------+
|       std        |     cis     |   0   |
|       std        |    trans    |   0   |
+------------------+-------------+-------+

In[6]: basepairs.csv("/tmp/foo.csv")

In[7]: ww = factory["W/W"]

In[8]: ww.find_interaction_by_position(8)
Out[8]:
(1,
 [BasePair(orientation='cis', position_1=1, position_2=72, base_1='G', base_2='C', interaction_type='+/+')])
Package: rna-voila
rna_majiq and rna_voilaThis is a placeholder package to reserve the pypi name and prevent confusion when installing the "majiq" and "voila" packages created by the
Biociphers Lab for quantification and visualization of RNA splicing from RNA-seq data. You most likely didn't mean to install this package
from pypi. Please seehttps://majiq.biociphers.org/for the full download and installation instructions of "majiq" and "voila"
Package: rnbgrader
RNBGrader - utilities for grading R Markdown notebooksUtilities for grading notebooks inR
MarkdownNotebooks can beR
notebooksorJupyter
notebooksconverted to R Markdown withJupytextQuickstartSee the tests for examples.Installationpip install rnbgraderCodeSeehttps://github.com/matthew-brett/rnbgraderReleased under the BSD two-clause license - see the fileLICENSEin the source distribution.travis-cikindly
tests the code automatically under Python versions 3.6 through
3.8.The latest released version is athttps://pypi.python.org/pypi/rnbgraderTestsR requirementsYou need the R kernel installed for the tests.On Mac:brew install libgit2 harfbuzz fribidiOn Debian / Ubuntu:sudo apt install -y libgit2-dev libharfbuzz-dev libfribidi-devOn any platform:Rscript -e "install.packages(c('repr', 'IRdisplay', 'crayon', 'pbdZMQ', 'devtools'))"
Rscript -e "devtools::install_github('IRkernel/IRkernel')"
Rscript -e "IRkernel::installspec()"The restInstallrnbgraderInstall the test requirements:pip install -r test-requirementsRun the tests with:pytest rnbgraderSupportPlease put up issues on thernbgrader issue
tracker.
Package: rnc2rng
Converts RELAX NG schemata in Compact syntax (rnc) to the equivalent schema
in the XML-based default RELAX NG syntax. Dependencies:Python 3.x (tested with 3.7, 3.8, 3.9)rplyFeedback welcome onGitHub. Please consider funding continued maintenance of this
project throughPatreonorGitHub Sponsors.Historyrnc2rng was originally written byDavid Mertzin 2003 and published as part
of a collection of files around RELAX NGon his siteinto the Public Domain.Hartmut Goebelpublished it as a package on PyPI to make it easier to access.
It was mirrored on GitHub byDustin J. Mitchellin 2010 after he fixed some
bugs.Timmy Zhuforked his repository and contributed further enhancements.
Recently, I (Dirkjan Ochtman) was interested in playing with RELAX NG Compact
and started making further updates. I asked Hartmut for maintainership on PyPI
and received it. While I cannot promise many updates, I should be responsive to
bug reports and (especially!) pull requests.How to installThe usual should work:$sudopipinstall.Getting started$python-mrnc2rngtest.rnc>test.rngLicenseAll of the code is released under MIT License.
Package: rncryptor
Python implementation ofRNCryptorInstallation$pipinstallrncryptorUsageimportrncryptordata='...'password='...'# rncryptor.RNCryptor's methodscryptor=rncryptor.RNCryptor()encrypted_data=cryptor.encrypt(data,password)decrypted_data=cryptor.decrypt(encrypted_data,password)assertdata==decrypted_data# rncryptor's functionsencrypted_data=rncryptor.encrypt(data,password)decrypted_data=rncryptor.decrypt(encrypted_data,password)assertdata==decrypted_dataTesting$tox$tox-epy27# test using only Python2.7$tox$(nproc)# run tests using all processesAn actual command can be found intox.ini, but basically it’s a commonpy.testwith a bunch of plugins.