Saravanan666/pypi-org huggingface dataset:
Package: sgp30
Library to read eCO2and TVOC from theSGP30 sensor. Based on the smbus2 i2c library for ease of use.It should be compatible with both python 2 and 3 but is currently only tested under Python 2.7Quick usage-example:from smbus2 import SMBusWrapper
from sgp30 import Sgp30
import time
with SMBusWrapper(1) as bus:
    sgp=Sgp30(bus,baseline_filename="/tmp/mySGP30_baseline") #things thing with the baselinefile is dumb and will be changed in the future
    print("resetting all i2c devices")
    sgp.i2c_geral_call() #WARNING: Will reset any device on teh i2cbus that listens for general call
    print(sgp.read_features())
    print(sgp.read_serial())
    sgp.init_sgp()
    print(sgp.read_measurements())
    print("the SGP30 takes at least 15 seconds to warm up, 12 hours before the readigs become really stable"
      for i in range(20):
              time.sleep(1)
              print(".",end="")
      print()
       print(sgp.read_measurements())Current design considerations:The class strives to to be light-weight and portable. It is currently a bit to tightly bound to the smbus2 class. In most cases I try to ease of readability rather than purity or speed.Features that are known to be missing (listing in rough order of importance):The handing of baseline values is not that great, it should probably be up to the end user to save and restore them as needed.Write doc-strings for all or at least most methods.reading raw-values.A more “driver like” class that takes care of all chip identification, polling at regular intervals, restoring baseline and so on.Run real hardware tests under Python3Hardware notices:If you have the Adafruit board with built in level shifters and voltage regulator it is should work if you just plug inSDA to pin 3, SCL to pin 5, VCC to pin 17 and GND to pin 20. You should then be able to find the SGP30 an address 0x58 usingi2cdetect -y 1. If you get an error message  you probably need to enable i2c in the kernel usingraspi-config and rebootFeel free to contact me with bugs, questions or issues.
Package: sgp30-driver
sgp30-driverEasy-to-use python driver for theSensirion SGP30multi gas sensorInstallationThe package is available onPyPI. Installation is can be done with your favourite package manager. For example:pipinstallsgp30-driverUsageIn order to initialise the device we need an openSMBusobject.
Depending on the machine that you are running on you may need to provide another bus number or path:fromsgp30importSGP30fromsmbus2importSMBuswithSMBus(1)asbus:device=SGP30(bus=bus)The address of theSGP30defaults to0x58. This is the (fixed) address of the SGP30 devices, so you should
never have to change it. If youdowant to change it, you can provide it likeSGP30(bus=bus, address=0x59).InitialisationAfter every restart the SGP30 has to be initialised:device.initialise()This process can take up to 20 seconds.This process can be sped up by passing recent values of the baseline compensation algorithm: store the result
ofdevice.baselinesomewhere in non-volatile memory, and restore it with:device.initialise(baseline)MeasuringAfter initialisation the device is ready for taking measurements. Themeasure()method returns
anSGP30Measurementobject which has two attributes:equivalent_co2which represents the CO2 concentration
in ppm (parts-per-million) andtvocwhich represents the TVOC (total volatile organic compounds) in ppb
(parts-per-billion).measurement=device.measure()print(f"{measurement.equivalent_co2}ppm CO2,{measurement.tvoc}ppb TVOC")In order to ensure the proper working of the baseline compensation algorithm one should call themeasure()method
in regular intervals of 1 second.Humidity compensationThe SGP30 has on-chip humidity compensation. In order to enable the compensation, you will need to get a
humidity measurement from another sensor, and then set the humidity usingset_humidity():device.set_humidity(15.2)The accepted humidity value is the absolute humidity ing/m3.Alternatively, if only the relative humidity is available:device.set_relative_humidity(humidity=0.5,# 50 %RHtemperature=20,# 20°C)
Package: sgp30-exporter
sgp30-exporterExports air quality readings from Pimoroni SGP30 to Prometheus.This exporter usespimoroni-sgp30to obtain data.Installationpipinstallsgp30-exporterRunningsudosgp30-exporterThis will serve metrics athttp://0.0.0.0:9895/metrics.Note thatsudois required to give SGP30 read-write access to the/dev/i2cinterface.You can make Prometheus scrape these with this scrape config:scrape_configs:-job_name:"sgp30"static_configs:-targets:["<theIPofyourexporterhost>:9895"]labels:location:"bedroom"0.2.1CLI help test assertion less picky about help format.0.2.0Introduced thesgp30-exporterCLI application. Makes it easier to run this exporter.Exporting metrics on port9895by default.0.1.2Bugfix: try to reconnect even if initialization failed.0.1.1Bugfix: reconnect to the SGP30 device on I/O failure.0.1.0Initial release.
Package: sg-pdfparser
SaralGyaan PDF ParserSaralGyaan PDF Parser is a command-line PDF parsing tool which allows you to:-Delete Pages from a PDFMerge PDFsSort Pages of a PDFSplit a PDFInstallationYou can install SaralGyaan PDF Parser fromPyPI:pip install sg-pdfparserThe PDF Parser supports Python 3.6 and above.How to use?The SaralGyaan PDF Parser is a command line application, named pdfparser. To start it you can simply open the terminal, go to the folder containing the PDF file(s) to be parsed and call the program:-$ pdfparser
Welcome to PDF Parser

What do you want to do?

1. Delete Pages from a PDF
2. Merge PDFs
3. Sort Pages of a PDF
4. Split a PDF

Press ctrl + C to exit.
Enter your choice (1-4):Delete Pages from a PDFIf you select the option to delete pages, it will ask for the filename followed by '.pdf'Enter your choice (1-4): 1
Delete Pages from a PDF
Enter the name of file with extension(.pdf)Make sure the pdf file exist at the location and once you provide a valid pdf file, it will give you two options:-What do you want to do?
 1. Delete specific pages
 2. Keep Specific pagesBoth the options accept comma separated values of pages or page ranges or both e.g. 1, 2, 3-5 or 1-2 or 2-3, 4-6.
One, thing you need to know that if you use Keep specific pages and change the order like 1-2, 6-4, then it will re-arrange the pages too.Merge PDFsThis options accepts comma separated file names and it will merge the files in the order, it is provided as an input.Sort pages of a PDFSort pages, give you three optionsWhat do you want to do?
1. Reverse order of all the pages
2. Swap Pages
3. Move certain pages to a specific indexThe first one, will simply reverse the order of the pages.The second one will swap two pages, you can input multiple or single swaps e.g. 1-3, 2-7, 8-9, etc.The third one will move the page to a certain page number (not index). It also accepts comma separated values. So 21-2 will move page number 21 to 2 and hence shifting the rest of the page to right.Split a PDFThis gives you two options:-What do you want to do?
 1. Split all the pages
 2. Split specific pagesThe first option will make n splits for n-paged PDF file.The second one will split the pdf into the ranges or pages as provided. e.g. 1, 3, 9-22, will give three split files first page, third page and pages from nine to twenty two.Video Usage GuideYou can also check out ourUsage Guideon Youtube.License© 2020 Udit VashishtThis repository is licensed under the MIT license. See LICENSE for details.
Package: sgpvae
Sparse Gaussian Process Variational AutoencodersThis repository contains the Python implementation of the SGP-VAE, introduced in ourpaper.The main components of the repository are:sgpvae: the implementation of the SGP-VAE and partial inference networks.experiments: code for running the experiments detailed in the paper.data: code for installing the datasets used in the experiments.DependenciesThis code is implemented in Python 3.8.ContactPlease do feel free to use/extend this code for your own research. Indeed, the models insgpvaeare implemented with versatility in mind, so should be easily applied to a wide range of datasets. If you have any questions, or would like to report any issues, please open an issue on the issues tracker or contact me atmca39@cam.ac.uk.
Package: sg.py
# sg.py – a small static site generator## Installation`bash $ pip install sg.py `## UsagePopulate directory with markdown files (they have to end with
.markdown). You can also create arbitrarily nested subdirectories
containing .markdown files.Sg will go recursively through all directories not beginning with an
underscore (“_”) and convert the .markdown files into .html. The
resulting HTML files will be saved into the _site directory, conserving
the directory structure where the .markdown file was found.Put your static content into _static. Files and subdirectories will be
copied into _site without any modifications.## TODOdocument the YAML frontmatterenable layout selection by _layout_foo or so
Package: sgqlc-schemas
AboutThis package was created so that when usingsgqlc (Simple GraphQL Client)you do not need to create schemas for popular APIs.How to useInstallationYou can install this package either via the Python Package Index (PyPI) or from source.To install usingpip:$ pip install -U sgqlc-schemasImport schema and simple queryfromsgqlc.endpoint.httpimportHTTPEndpointfromsgqlc.operationimportOperationfromsgqlc_schemasimportgithub_schemaop=Operation(github_schema.query_type)op.viewer().login()endpoint=HTTPEndpoint('https://api.github.com/graphql',{'Authorization':f'bearer{token}'})data=endpoint(op)Current schemasGitHubMonday.comContributionThis package welcomes any new contribution. Please createpull requests on GitHub.
Package: sgr-ansi
sgr-ansiawesome SGR ANSI colorful text interface in terminalfull supported in python3.7+, macosxawesome colorful textinstallpipinstallsgr-ansiusageBeware of two rules:styles requirealphabet orderstyles go before colorsabout styles, you can use as many as possible, but colors only the last two will take effectso likeBDISUkrgybmcw, allBDISUwill take effect, but for colors onlycw: cyan on whitewill take effectstyles/colors supportedstylesB: bold, D: dimmed, I: italic, S: strike_through, U: underlinedcolorsk: black, r: red, g: green, y: yellow b: blue, m: magenta, c: cyan, w: whiteimportsgr_ansiasechoecho.BIg()echo.BIg('I love you 3 thousand times')chained callfromsgr_ansiimportChainChain().BIy('Yep,').BIUb('How do you like this?').Bm('\n\t[✔]').BUg('1.').Bg('Y: yes.').Bm('\n\t[✘]').BUr('2.').Br('N: not.').show()run demojust runsgransito check all available styles# after installed sgr_ansi, cli sgransi is availablesgransi-h
Package: sgraph
sgraphsgraph contains data format, structures and algorithms to work with hierachic graph structures.
Typically it is suitable for representing software structures.Installpip install sgraphContributionsThe project is welcoming all contributions.Core OntologyA model,SGraphconsists of a rootSElement, which may have children of the same type (as in XML).
Attribute information can be stored via key-value pairs into them.
TheSElementobjects can be connected together viaSElementAssociationobjects.Example modelnginx model has an nginx root element that represents the main directory.
Inside it, there is a src element. And inside src, there is core.https://github.com/nginx/nginx/tree/master/srcinside core, there are several elements, e.g. nginx.c and nginx.hhttps://github.com/nginx/nginx/blob/master/src/core/nginx.cBecause nginx.c contains #include directive to nginx.h, in the model it is
formulated so that there is a relationship (also called as association) from nginx.c element to nginx.hTo make model more explicit, that particular relationship should be annotated with type "inc" to describe
the dependency type.It is also possible to have other attributes assigned to relationships other than type but typically this is rare.XML formatIn XML dataformat, minimalism is the goal to make it simple and clean. Integers are used as unique identifiers for the elements.
In the example case, the nginx.h element is assigned with ID 2 and the relationship that is inside nginx.c refers this way to nginx.hThis integer reference system has been designed to make the data format highly performing even with 10 million element models.Deps data format - line based simple format for easy scriptingIn Deps data format (usually a .txt file), the above model can be described minimally this way:/nginx/src/core/nginx.c:/nginx/src/core/nginx.h:incAlthough this might seem very compelling data format to use, it is not recommended for very
large models, e.g. 10 million elements.Using the APICreating a simple model:>>> from sgraph import SGraph
>>> from sgraph import SElement
>>> from sgraph import SElementAssociation
>>> x = SGraph(SElement(None, ''))
>>> x
<sgraph.sgraph.SGraph object at 0x7f2efae9ad30>

>>> x.to_deps(fname=None)

>>> e1 = x.createOrGetElementFromPath('/path/to/file.x')
>>> e2 = x.createOrGetElementFromPath('/path/to/file.y')
>>> x.to_deps(fname=None)
/path
/path/to
/path/to/file.x
/path/to/file.y

>>> x.to_xml(fname=None)
<model version="2.1">
  <elements>
  <e n="path" >
    <e n="to" >
      <e n="file.x" >
      </e>
      <e n="file.y" >
      </e>
    </e>
  </e>
</elements>
</model>

>>> ea = SElementAssociation(e1, e2, 'use')
>>> ea.initElems()  # ea is not connected to the model before this call.
>>> x.to_deps(fname=None)
/path/to/file.x:/path/to/file.y:use
/path
/path/to
>>>

>>> x.to_xml(fname=None)
<model version="2.1">
  <elements>
  <e n="path" >
    <e n="to" >
      <e n="file.x" >
        <r r="2" t="use" />
      </e>
      <e i="2" n="file.y" >
      </e>
    </e>
  </e>
 </elements>
</model>Current utilizationSoftagramuses it for building up the information model about the
analyzed software.
Package: sgRNAble
sgRNAblesgRNAbleis a tool for high-throughput design of sgRNA libraries targeting selected genes or whole genomes, while considering both on-target binding potential and off-target effects of a given sgRNA in a user-defined genome.Basic Usagesgrnable -t TARGET_SEQUENCE.fasta -g GENOME_SEQUENCE.fasta
          [GENOME_SEQUENCE.fasta ...] [-a AZIMUTH_CUTOFF]
          [-c COPY_NUMBER [COPY_NUMBER ...]]
          [-o OUTPUT_DIR] [-p PURPOSE]
          [-th NUM_THREADS] [-m MAX_MEMORY] [-v]DocumentationAll documentation for the current release is accessible through thesgRNAble wiki.AuthorsSiddarth RaghuvanshiAhmed AbdelmoneimAvery NoonanContactNeed something? Please contact Professor Steven Hallam and Avery Noonan at:shallam@mail.ubc.caandavery.noonan@ubc.caReferencesFarasat, I., & Salis, H. M. (2016). A Biophysical Model of CRISPR/Cas9 Activity for Rational Design of Genome Editing and Gene Regulation.PLOS Computational Biology,12(1), e1004724. doi:10.1371/journal.pcbi.1004724Doench, J. G., Fusi, N., Sullender, M., Hegde, M., Vaimberg, E. W., Donovan, K. F., . . . Root, D. E. (2016). Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9.Nature biotechnology,34(184). doi:10.1038/nbt.3437
Package: sgs
SGSIntroductionThis library provides a pure Python interface for the Brazilian Central Bank’sTime Series Management System (SGS)api.
It works with Python 3.5 and above.SGS is a service with more than 18,000 time series with economical and financial information.
This library is intended to make it easier for Python programmers to use this data in projects of
any kind, providing mechanisms to search for, extract and join series.QuickstartAccess time series data withsgsis very simpleBegin by importing thesgsmodule:importsgsNow, let’s try to get a time serie. For this example, let’s get the
“Interest rate - CDI” time serie in 2018, wich has the code 12.CDI_CODE=12ts=sgs.time_serie(CDI_CODE,start='02/01/2018',end='31/12/2018')Now, we have a Pandas Series object calledts, with all the data and
the index representing the dates.ts.head()2018-01-020.0264442018-01-030.0264442018-01-040.0264442018-01-050.0264442018-01-080.026444Feature SuportGet time serie data with an one-liner usingsgs.time_serieCreate a dataframe from a list of time series codes withsgs.dataframeSearch time series by text or code withsgs.search_tsGet metadata from all the series in a dataframe usingsgs.metadataSupport to search and metadata in English and PortugueseAutomatic retryAutomatic cached requestsInstallationTo install, simply use pip:$pipinstallsgsDocumentationComplete documentation is available athttps://pysgs.readthedocs.io/en/stable/.
Package: sg-sesame
SG SesameOpen ports in Security Groups for your current IP addressInstallationInstall globally usingpipx:pipx install sg-sesameUsageQuickstartJust install and run:sg-sesame --port 22 --addAfter the first run, you can omit the--addflag:sg-sesame --port 22.If you have more than one Security Group with a rule for port 22, you will be asked to choose from a list.Advanced usage$ sg-sesame --help

Usage: sg-sesame [OPTIONS]

Options:
  --port INTEGER     [required]
  --note TEXT        Description of the rule to be added/updated. If omitted,
                     the machine hostname will be used.

  --add / --no-add   If not specified, will try to update an existing rule
                     that has matching `note`, `port` and `protocol`.
                     Otherwise will add a new rule.

  --group-name TEXT  If specified, the rule will be added to the Security
                     Group with this name. Otherwise will prompt the user to
                     select a SG.

  --protocol TEXT    Protocol to use for the rule  [default: tcp]
  --profile TEXT     AWS profile to use  [default: default]
  --region TEXT      AWS Region to connect to
  --help             Show this message and exit.CreditsThis package was created with Cookiecutter and thecs01/cookiecutter-pypackageproject template.Cookiecuttercs01/cookiecutter-pypackage
Package: sgs-utils
sgs-utils is a collection of python libraries that allows to manipulate SGS related files, especially the input and output ofshogen.Requirementa compatible shell (bashis ok,dashis not)awk,sortlibsbmlpython 2.7(optional:pip)sgs-utilspython-libsbml(≥ 5.12.0)networkxshogenpyasp(= 1.3.x, the python 2.7 branch of pyasp)How to installWhen installingsgs-utils, all needed python depencies will be automatically installed.WarningIf you have already installed a version ofpyaspsomewhere in your system (system wide, user wide or virtualenv installation) and you when to install sgs-utils (and shogen) elsewhere, thesetup.pyscript may not download and install theclaspandgringobinaries in the new installation.
This problem is related to the way setuptools and pip manage the installation cache. There is no automatic workaround.You can check thatclaspandgringobinaries are installed by looking if they exist in thepyaspbinary directory which is something like${PYTHONPATH}/lib/python2.7/site-packages/pyasp-1.3.x-py2.7.egg/pyasp/bin/.A solution to solve this issue is to reinstall pyasp with the--no-cache-diroption that force pip and setuptools to ignore the cache.pipinstallpyasp==1.3.3--user--ignore-installed--no-cache-dirAlternatively, you can compileclaspandgringo3or download their binaries fromhereand copy/link them respectively asclaspandgringofiles in the pyasp binary directory.Install with pippipinstall--usersgs-utilsManual installDownloadsgs-utils-x.yz.tar.gzFrom thepypi websiteand then do the following commands.tarxvfsgs-utils-x.yz.tar.gzcdsgs-utils-x.yzpythonsetup.py--userinstallcd..rm-rsgs-utils-x.yzAcknowledgementThis work was supported by grants Fondap 15090007, Basal program PFB-03 CMM, IntegrativeBioChile INRIA Assoc. Team, ANR-10-BLANC-0218 and CIRIC-INRIA Chile (line Natural Resources).
Package: sgtpy
SGTPy is an open-source python package of SAFT-VR-Mie and SAFT-Gamma-Mie Equations of State (EOS).
SGTPy allows to work with pure fluids and fluid mixtures, additionally the fluids
can be modeled considering association, cross-association and polar contributions.
SGTPy was built on top of phasepy’s phase equilibrium and Square
Gradient Theory (SGT) functions. These functions were updated to speed-up
calculations of associative mixtures.SGTPy relies on Numpy, SciPy and PhasePy.
Package: sgtpyutils
What?sgtpyutils is python module for common utils.InstallpipinstallsgtpyutilsUsage日志处理fromsgtpyutils.loggerimportloggerlogger.debug('调试')logger.info('信息')logger.warning('警告')时间处理fromsgtpyutils.datetimeimportDateTime# 当前时间print(DateTime())# 2023-09-19 14:50:43.570560+08:00# 指定日期print(DateTime('2023-09-19'))# 2023-09-19 00:00:00+08:00# 指定时间print(DateTime('2023-09-19 14:50:43'))# 2023-09-19 14:50:43+08:00# 指定时间戳print(DateTime(1695106243000))# 2023-09-19 14:50:43+08:00# 指定时间及时区print(DateTime('2023-09-19T14:50:43+07:00'))# 2023-09-19 14:50:43+07:00# 计算时间差print((DateTime('2023-09-20')-'2023-09-19').total_seconds())# 86400.0print((DateTime('2023-09-20')-60*1000))# 2023-09-19 23:59:00+08:00# 获取相对时间print(DateTime('2023-09-20').toRelativeTime('2023-09-20 14:23'))# 14小时前print(DateTime('2023-09-20 10:00:00').toRelativeTime('2023-09-20 10:01:00'))# 1分钟后print(DateTime('2023-01-20 10:00:00').toRelativeTime())# xxx年前Status
Package: sgtree
Simple Genome Tree (SGTree)v0.1 05/19/2019Simple Genome Tree (SGTree) is a computational pipeline for fast and easy construction of phylogenetic trees from a set of user provided genomes and a set of phylogenetic markers, in a taxonomic framework of de-replicated reference genomes. SGTree identifies conserved phylogenetic marker proteins and evaluates additional copies of markers derived from either duplications, horizontal gene transfer or contamination, to build a phylogenetic tree based on the concatenated alignment of selected marker proteins.SetupActivate conda environment and run sgtreeFirst clone the git repository.  (cHdNmkqqNNrQNa9Kvux6)Make sure you have anaconda installed, you can install it here.https://www.anaconda.com/distribution/#download-sectionDepending on your OS, choose the osxenv.txt for mac or the ubuntu-env.txt file for Ubuntu or linux.Next run (where spec-file.txt is either ubuntu_env or osxenv):condacreate--namesgtree_env--filespec-file.txtsourceactivatesgtree_env(orcondaactivatedependingonyourversion)Run SGTreeRun sgtree with the provided set of query genomes and models for testing,
user can control the number of CPUs used by the computer, the minimum percentage of
models with hits for a genome to be considered as part of the dataset as well as a directory with reference genomes.
Genomes from the query genomes directory and the reference genomes directory will be colored red and grey respectively.# test examplepython3sgtree.pytestgenomes/Chloroflexihmms/UNI56--num_cpus8# general examplepython3sgtree.py<genomesdirectory><modelsdirectory>--num_cpus<integer>--percent_models<integer>--ref<referencegenomesdirectory>For running sgtree_final.py, please make a ref_concat folder wherever you want to store reference db runs.python3sgtree_final.pytestgenomes/Chloroflexihmms/UNI56sgtree/references_concat--num_cpus10--save_dirsgtree/test--refsgtree/testgenomes/chlorrefpython3sgtree_final.py<genomesdirectory><modelsdirectory><referencesdirectory>--num_cpus<integer>--percent_models<integer>--ref<referencegenomesdirectory>## Important note
1. Genomes must have the header format as follows: 

``` bash
	>IMG2684622718|2685462912
	MLCAFAEEEAKIAETVGKVATELKVKKLLSDFATKEGEEHISTYNKIAMTAKAEGYADIEAMLCAFAEEEAKLQKLwhere the first field before the pipe contains the genome identifier which matches the filename base, and the second field a unique protein identifier.
Package: sgtslaughter
This is a package that has useful machine vision for use with CarsCHANGE LOGRELEASE 10.0.0.1  (7/27/2021)First Release\RELEASE 20.0.0.2 –> 7/27/2021Just wanted to test some things outreally didn’t don anything\-RELEASE 3
-0.0.0.3–> 7/27/2021
-Just wanted to test some things out
-really didn’t don anything