Saravanan666/pypi-org huggingface dataset:
Package: ps2ff
ps2ffProduce approximated finite fault distances and variance corrections given
point source information, for example Repi (epcentral distance) to Rjb
(Joyner-Boore distance) or Rrup (closest distance to rupture).Using the results (the API)The command line programs (described below) can be used to generate new
distance adjustments. This package also includes a set of correction factors
for some common conditions (e.g., typical active crustal regions). These
can most easily be used with theinterpolatemodule that contains thePS2FFclass, which enables the use of the tables for arbitrary magnitudes and
epicentral distance values. See theps2ff.interpolatesection of this
package.InstallationIn the base of this repository, runconda create --name ps2ff pip
conda activate ps2ff
pip install -r requirements.txt .You can omit the conda commands if you do not wish to use a conda virtual environment.To run the testspip install pytest
pytest .BackgroundThis code implements the methods descibed by:Thompson, E. M., and C. B. Worden (2017). Estimating rupture distances without
a rupture,Bulletin of the Seismological Society of America.
DOI:https://doi.org/10.1785/0120170174.Running the ProgramsThe primary program isrun_ps2ff, which must be given a configuraiton fileps2ff -w Rjb config_file.iniwhere '-w Rjb' is the 'what' command line argument forrun_ps2ff.
There are example configuration files in theps2ff/configdirectory.Output TablesTheps2ff/tablesdirectory contains example results for some generic seismological
assumptions. The output file name convension is easiest to describe with an
example:Rjb_S14_mechA_ar1p0_seis0_15_Ratios.csvwhere:"Rjb" is the thewhatcommand line argument."S14" is the selectedrup_dim_model."mechA" specifies the rupture mechanism parametermech, where "A" can
be one of "A", "SS", "N", or "R"."ar1p0" is the aspect ratio specified with theARparameter, where the
decimal point is replaced with the letter 'p'."seis0_15" is the range min/max seismogenic depths (in this case 0 to 15
km)."Ratios" is either "Ratios" or "Var" specifying whether the file contains
Rjb- or Rrup-to-Repi ratios, or variances.Each output table starts with six header lines (each beginning with#)
specifying the processing parameters. This is followed by a line
(comma-separated) providing the column headers. The first column, "Repi_km",
is the epicentral distance. The following columns "R(magnitude)" ("R" for
"ratio") or "V(magnitude)" ("V" for "variance) provide the values for a given
Repi and magnitude. The table is intended for bi-variate interpolation, linear
in magnitude and logarithmic in distance. The ratios are Rjb (or Rrup) to Repi.Program Detailsrun_ps2ffproduces tables of Rjb-to-Repi or Rrup-to-Repi ratios and
variances. Example configuration files may be found in ps2ff/config.run_ps2ff_single_eventproduces tables of Rrup-to-Repi and Rjb-to-Repi
ratios and variances for a single event. This means that the magnitdue and
hypocentral depth are available, simplifying the integration. It optionally
tabulates the adjustment factors as a function of backazimuth. An example
configuration file for this program is given intests/config/test_single.ini.
Package: ps2joycln
PS2 Joy ClientUse PlayStation 2 input accessories that cheap "PS2 to USB" dongles don't recognize by dumping gamepad input into UDP packets.This relies on aserverto be running in your PS2 console.Dependencies (will be installed automatically)keyboard>=0.13.5InstallingDownload and installPythonOn a terminal/command prompt, enter:python -m pip install ps2joyclnRunningOn Linux: #python3 -m ps2joycln(yes, as root (unfortunately))On Windows: >python -m ps2joyclnConfigurationIt defaults the locating of the configuration file to~/.config/ps2joycln.ini(or%USERPROFILE%\.config\ps2joycln.ini), on port1469, creating if not exists.The-cCLI switch allows to specify another place, which can be used as profiles.The configuration does not hot-reload. Close the application (Ctrl+Cor whatever) and reopen to apply changes.On Linux, it requires running as root.osu!mania 4k with dance matI personally use the snippet below withDDR skin:[pad2]
dir_up=j
dir_dw=f
dir_lf=d
dir_rg=kReminder: osu!mania 4k is meant to be played with keyboard. It might be an exhausting experience.
Package: ps2mqtt
ps2mqttPython daemon that gets information frompsutilto an mqtt broker for integration withHome Assistant.InstallYou can install ps2mqtt from pypi:$pipinstallps2mqttIf you wish to run ps2mqtt through systemd, download the ps2mqtt.service file from this repository and edit according to your system.Then just copy to systemd path and enable the service before starting:$sudocpps2mqtt.service/etc/systemd/system/

$sudosystemctlenableps2mqtt.service$systemctlstartps2mqtt.serviceOptionsps2mqtt has several command line options you should use when customizing ps2mqtt.service:-h, --help                                  show this help message and exit
  --config CONFIG                             configuration file, will be created if non existing
  --period PERIOD                             updates period in seconds
  --mqtt-server MQTT_SERVER                   MQTT server
  --mqtt-port MQTT_PORT                       MQTT port
  --mqtt-username MQTT_USERNAME               MQTT username
  --mqtt-password MQTT_PASSWORD               MQTT password
  --mqtt-base-topic MQTT_BASE_TOPIC           MQTT base topic
  --ha-discover-prefix HA_DISCOVER_PREFIX     HA discover mqtt prefix
  --ha-status-topic HA_STATUS_TOPIC           HA status mqtt topicYou can also store all the options in a file, just run all your options plus the--config /etc/ps2mqtt.yamlto store all your parameters in a config file. Next time you run, just use--config /etc/ps2mqtt.yaml.
Package: ps3api
PS3APIPS3 API for TMAPI and CCAPI in python.NoteThis only works on 32 bit python as TMAPI and CCAPI are 32 bit DLLs.ExamplesConnecting and Attachingfromps3apiimportPS3APIPS3=PS3API(PS3API.API_TMAPI)ifPS3.ConnectTarget(PS3.GetDefaultTarget())==False:raiseException("Failed to connect to PS3.")ifPS3.AttachProcess()==False:raiseException("Failed to attach to process.")MemoryReadingPS3.ReadMemory(Address,NumBytes)PS3.ReadInt8(Address)PS3.ReadInt16(Address)PS3.ReadInt32(Address)PS3.ReadInt64(Address)PS3.ReadFloat(Address)PS3.ReadDouble(Address)PS3.ReadString(Address,Encoding="ascii",MaxLength=1024)WritingPS3.WriteMemory(Address,Bytes)PS3.WriteInt8(Address,Value)PS3.WriteInt16(Address,Value)PS3.WriteInt32(Address,Value)PS3.WriteInt64(Address,Value)PS3.WriteFloat(Address,Value)PS3.WriteDouble(Address,Value)PS3.WriteString(Address,Value,Encoding="ascii")Remote Procedure Call (RPC)FunctionPS3.RPC.Enable(0x02539F8)# MW2 1.14CG_BoldGameMessage=PS3.RPC.Function(0x0005EF68)CG_BoldGameMessage.argtypes=[ctypes.c_ulong,ctypes.c_char_p]CG_BoldGameMessage(0,"Hello World!")System Call# Define your ownsys_process_getpid=PS3.RPC.SystemCall(SyscallIndex.SYS_PROCESS_GETPID)sys_process_getpid.ReturnType=[c_ulong]print(sys_process_getpid())# Use builtin definitionsPS3.RPC.Syscalls.sys_process_getpid()Interacting With C API>>>PS3.API.NativeAPI.SNPS3InitTargetComms()<SNReturnCode.SN_S_OK:0>Alternatively>>>fromps3apiimportTMAPIExports>>>C_API=TMAPIExports()>>>C_API.SNPS3InitTargetComms()<SNReturnCode.SN_S_OK:0>Useful ScriptsAssembler>>>fromkeystoneimport*>>>frompwnimport*# for hex dump>>>Keystone=Ks(KS_ARCH_PPC,KS_MODE_64|KS_MODE_BIG_ENDIAN)>>>Encoding,Count=Keystone.asm("li%r3, 0x1234\nblr")>>>print(hexdump(bytes(Encoding)))00000000386012344e800020│8`·4│N··│00000008Disassembler>>>fromcapstoneimport*>>>Capstone=Cs(CS_ARCH_PPC,CS_MODE_64|CS_MODE_BIG_ENDIAN)>>>foriinCapstone.disasm(PS3.ReadMemory(0x10000,0xE0),0x10000):...print("0x%x:\t%s\t%s"%(i.address,i.mnemonic,i.op_str))...0x10000:mflrr00x10004:stdr0,-8(r1)0x10008:stdr30,-0x18(r1)0x1000c:stdr31,-0x10(r1)0x10010:stdur1,-0x200(r1)0x10014:lisr31,0x10050x10018:orir31,r31,0x10000x1001c:lwzr30,0x70(r31)0x10020:cmpwir30,00x10024:beq0x101180x10028:stfsf1,0x178(r1)....
Package: ps3-update-dl
ps3-update-dlDownloads all updates for a given title directly from the PlayStation servers.Installationpipxis the recommended way to install ps3-update-dl.$ pipx install ps3-update-dlAfterwards, the command will be available asps3udl.UsageUsage: ps3udl [-c GAMES_YML_PATH] -o BASE_DIR [TITLE_ID_1 TITLE_ID_2...]

Download all updates for all given titles to the given base directory.
A subdirectory inside the base directory will be created for each title.

Titles are specified via command-line args or the games.yml file or both.

Options:
	-o BASE_DIR, --base-dir BASE_DIR
	The directory that all titles will be downloaded to. It must exist.

	-c GAMES_YML_PATH, --games-yml-path GAMES_YML_PATH
	Path to your RPCS3 games.yml file. All updates for all games listed in this file will be downloaded if specified.

	-f, --force
	Whether to overwrite existing files.

	-h, --help
	Display this message.License© io mintzio@mintz.ccps3-update-dl is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or (at your option) any later version.ps3-update-dl 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 Affero General Public License for more details.You should have received a copy of the GNU Affero General Public License
along with ps3-update-dl. If not, seehttps://www.gnu.org/licenses/.
Package: psa-connected-car-client
PSA Connected Car API ClientAPI client for PSA group connected car service.This is a rework of the wonderfulPSA Car Controllerby@flobz.The goal is to extract the core functionality and provide it as a library to be used by systems like Home Assistant directly, without the need to run a separate server.It builds upon some great libraries:httpxfor the asynchronous REST API requestsauthlibto handle the Oauth2 authenticationmsgspecfor the decoding of the API response into python classespyaxmlparser, a lighter alternative toandroguard, to get the needed information from the PSA android appInstallationpipinstallpsa-connected-car-clientUsageA basic usage of the library can be found attests/demo_cli.py.Simple versionYou can create thePSAClientusing thecreate_psa_clientfunction.frompsa_cccimportcreate_psa_clientasyncdefmain():client=awaitcreate_psa_client(brand,country_code,email,password)The arguments are self-explanatory, but just in case:brandis the car brand; possible values are:PeugeotCitroenDSOpelVauxhallcountry_codeis your 2 letter uppercase country codeemailis the address you used to register to the "MyBrand" apppasswordis - you guessed it - the password for the appBehind the scenes, this function will download the APK of the mobile app, extract the data needed to establish a connection to the PSA servers and save it in a config file.
Subsequent runs of the function will read from that config file, if it exists.You're now ready to use the client to talk to the PSA connected car service!user=awaitclient.get_user()print("User:",user)vehicles=awaitclient.get_vehicles()print("Vehicles:",vehicles)vehicle_id=vehicles[0].idvehicle=awaitclient.get_vehicle(vehicle_id)print("First vehicle:",vehicle)alerts=awaitclient.get_vehicle_alerts(vehicle_id)print("Vehicle alerts:",alerts)status=awaitclient.get_vehicle_status(vehicle_id)print("Vehicle status:",status)maintenance=awaitclient.get_vehicle_maintenance(vehicle_id)print("Vehicle maintenance:",maintenance)print("Vehicle position:",status.last_position.geometry.coordinates,"last updated at",status.last_position.properties.updated_at,)Customizable storagethecreate_psa_clientfunction accepts two optional parameters for choosing where to store the configuration and the auth tokens:cache_storageaccepts any implementation of theCacheStorageprotocol.
The library comes with theSimpleCacheStorageclass that stores the files inside the given directory.
This is the storage used in thesimple versionabove, and uses the current working directory as storage.token_storageaccepts any implementation of theTokenStorageprotocol.
Again, the library has aMemoryTokenStorageclass that keeps the token in memory (it is never written to disk).
This is the default token storage for thesimple versionabove.frompathlibimportPathfrompsa_cccimportSimpleCacheStoragefrompsa_cccimportMemoryTokenStoragefrompsa_cccimportcreate_psa_clientasyncdefmain():storage=SimpleCacheStorage(Path(__file__).parent)token_storage=MemoryTokenStorage()client=awaitcreate_psa_client(brand,country_code,email,password,storage,token_storage)# do whatever you want with client...
Package: ps_alchemy
ps_alchemyps_alchemyis extension forpyramid_sacrudwhich provides SQLAlchemy models.Look how easy it is to use:Base=declarative_base()DBSession=scoped_session(sessionmaker(extension=ZopeTransactionExtension()))classPageTree(Base):__tablename__='pages'id=Column(Integer,primary_key=True)config.include('ps_alchemy')config.include('pyramid_sacrud',route_prefix='admin')config.registry.settings['pyramid_sacrud.models']=('webpages',[PageTree,])For more docs seehttp://ps-alchemy.rtfd.orgSupport and DevelopmentTo report bugs, use theissue trackerWe welcome any contribution: suggestions, ideas, commits with new futures,
bug fixes, refactoring, docs, tests, translations etcIf you have question, contact mesacrud@uralbash.ruor IRC channel #sacrudLicenseThe project is licensed under the MIT license.
Package: psalpsdtools
psalpsdtoolspsalpsdtoolsis a file maintenance Python package tool designed specifically for the Livestock and Poultry Statistics Division to streamline file management and updating processes. This comprehensive package provides a user-friendly interface and a robust set of functionalities to efficiently organize, manipulate, and validate data files. From data cleaning and merging to filtering and report generation, this package offers a reliable solution to enhance productivity and ensure only accurate information are produced. Furthermore, this package is continuously evolving with ongoing development, promising future enhancements and additional functionalities to cater to the evolving needs of the division.FeaturesSome of the features include:Electronic Data Review Worksheet (EDRW)Lookup and copying of values from the Supply-Disposition worksheetPasting values to the EDRW output fileGeneration of output files by province, based on user specified inputs which includes:regioncommodityyearBuilt-in Functionsget_regions- returns a list of regions.get_provinces- returns a list of provinces of a given region.RequirementsPython 3.8 or later with allrequireddependencies installed. To install run:pip install psalpsdtoolsUsageEDRW Updating- Pre-requisites (for Chicken)baseFoldershould contain the S-D file.insidebaseFolder, a folder namedSourcesmust exist, containing the regional folders and the provincial files inside.Provincial EDRW source files should have .xlsm extensionsCurrently, source filename is expected to be "cc" +province name+ "_year", e.g.08 Agusan del Norte_23.xlsm- Example code:from psalpsdtools import Edrw

# Specify Region
regName = 'Caraga'

# Specify quarter
# Used in identifying which worksheet to paste the copied values from the S-D file.
qtr = 'Q1'

# Specify folder location of Sources and Final files.
# The S-D file should also be found here.
baseFolder = 'D:/EDRW/Q1'

# Specify S-D filename
# IMPORTANT! Only .xlsm or .xlsx extensions are accepted
sdFile = 'SD Q1 2023.xlsm'

# Commodity code i.e. 08=chicken, 09=duck, etc.
commcode = '08'

# Year
yr = '23'

# Call an instance of the Edrw package
myedrw = Edrw()

# Run update_sources with the parameters
myedrw.update_sources(regName,qtr,baseFolder,sdFile,commcode,yr)Built-in Functionsget_regionsExample code:from psalpsdtools import PhRegPrv

philippines = PhRegPrv()
regions = philippines.get_regions()

for region in regions:
    print(region)get_provincesExample code:from psalpsdtools import PhRegPrv

# Specifiy a region
regname = 'Caraga'

philippines = PhRegPrv()
provinces = philippines.get_provinces(regname)

for province in provinces:
    print(province)ContributeIssue Tracker:github.com/tondiaz/psalpsdtools/issuesSource Code:github.com/tondiaz/psalpsdtoolsLicenseThe project is licensed under the MIT license.
Package: psamm
PSAMM is an open source software that is designed for the curation and analysis
of metabolic models. It supports model version tracking, model annotation, data
integration, data parsing and formatting, consistency checking, automatic gap
filling, and model simulations.SeeNEWSfor information on recent changes. Themasterbranch
tracks the latest release while thedevelopbranch is the latest version in
development. Please apply any pull requests to thedevelopbranch when
creating the pull request.InstallUsepipto install (it is recommended to use aVirtualenv):$pipinstallpsammDocumentationThe documentation for PSAMM is available atRead the Docs.Citing PSAMMIf you use PSAMM in a publication, please cite:Steffensen JL, Dufault-Thompson K, Zhang Y. PSAMM: A Portable
System for the Analysis of Metabolic Models. PLOS Comput Biol. Public
Library of Science; 2016;12: e1004732.10.1371/journal.pcbi.1004732.Software licenseThis program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.You should have received a copy of the GNU General Public License
along with this program.  If not, see <http://www.gnu.org/licenses/>.SeeLICENSE.
Package: psanalyzer
psanalyzerThis tool supports 2 commands:build- it walks current work dir recursively, finds all files and dirs, calculates their hash and collects various info about every file/dir. Output is sqlite3 database.Default db path is${PWD}/psanalyzer.sqlite3. You can open it with any sqlite3 tool and query it by yourself.query- it runs hardcoded SQL queries against sqlite3 database.runpsanalyzer query --helpto get a list of supported queriesExample:$cdproject
$psanalyzerbuildTotalfilesfound:2056Totaldirsfound:333Processingfiles:100%|██████████████████████████████████████████|2056/2056[00:00<00:00,6991.67files/s]Processingdirs:100%|█████████████████████████████████████████████|333/333[00:00<00:00,7816.48dirs/s]Success!Nowrunqueries:
psanalyzerqueryduplicates--formatcsv>output.csv

$psanalyzerqueryduplicates--formatcsv
path,hash,size_bytes,type
.venv\Scripts\pip.exe,314bc6d461c15eab5ce073d44e735efceb8ac76f6182e626effd20f56a97ee47,108412,file
.venv\Scripts\pip3.10.exe,314bc6d461c15eab5ce073d44e735efceb8ac76f6182e626effd20f56a97ee47,108412,file
.venv\Scripts\pip3.exe,314bc6d461c15eab5ce073d44e735efceb8ac76f6182e626effd20f56a97ee47,108412,file
.venv\Scripts\pip-3.10.exe,314bc6d461c15eab5ce073d44e735efceb8ac76f6182e626effd20f56a97ee47,108412,file
.venv\Scripts\wheel.exe,2908e4480db497f164d0a157b62baa8f8875a5f5f192f2c3337b1b0654581386,108399,file
.venv\Scripts\wheel3.10.exe,2908e4480db497f164d0a157b62baa8f8875a5f5f192f2c3337b1b0654581386,108399,file
.venv\Scripts\wheel3.exe,2908e4480db497f164d0a157b62baa8f8875a5f5f192f2c3337b1b0654581386,108399,file
.venv\Scripts\wheel-3.10.exe,2908e4480db497f164d0a157b62baa8f8875a5f5f192f2c3337b1b0654581386,108399,file
.venv\Lib\site-packages\setuptools\cli.exe,75f12ea2f30d9c0d872dade345f30f562e6d93847b6a509ba53beec6d0b2c346,65536,file
.venv\Lib\site-packages\setuptools\cli-32.exe,75f12ea2f30d9c0d872dade345f30f562e6d93847b6a509ba53beec6d0b2c346,65536,file
.venv\Lib\site-packages\setuptools\gui-32.exe,5c1af46c7300e87a73dacf6cf41ce397e3f05df6bd9c7e227b4ac59f85769160,65536,file
.venv\Lib\site-packages\setuptools\gui.exe,5c1af46c7300e87a73dacf6cf41ce397e3f05df6bd9c7e227b4ac59f85769160,65536,file
.venv\Lib\site-packages\setuptools\_vendor\packaging\specifiers.py,fb76a36790a442b8cd5b91fc34f8ef095d91060afec3dc1c60175bf248cf05f8,39046,file
........Does not depend on GIT.Cross-platform. If something doesn't work it's a bug.
Package: psankey
<img src=”https://github.com/mandalsubhajit/psankey/blob/master/pSankey.png” width=”100”># psankey - A module for plotting Sankey flow diagrams in PythonInspired byd3-sankeypackage for d3js (https://github.com/d3/d3-sankey)## Brief descriptionIn data science, we often require to visualize flows in the form of a Sankey diagram. This module helps with that. Usage is very straightforward and customizable.Note:Does not work for cyclical graphs.## Getting started### InstallationDirectly from the source - clone this repo on local machine, open the shell, navigate to this directory and run:` python setup.py install `or through pip:` pip install psankey `### DocumentationPlease visit [https://github.com/mandalsubhajit/psankey]
Package: psap
psapCLI interface for the PSAP classifier. PSAP implements a RandomForest approach to predict the probability of proteins to mediate protein phase separation (PPS). Initially, a set of protein sequences is annotated with biochemical features which are subsequently used to train a RandomForest (scikit-learn) classifier. The trained classifier is afterwards exported to json format and can be used to predict the llps class probability (PSAP_score) for unseen protein sequences.The default model was trained on thehuman reference proteomewith a list of literature curated PPS proteins for positive class labeling. Both can be found in /data.Publication| Mierlo, G., Jansen, J. R. G., Wang, J., Poser, I., van Heeringen, S. J., & Vermeulen, M. (2021). Predicting protein condensate formation using machine learning. Cell Reports, 34(5), 108705.https://doi.org/10.1016/j.celrep.2021.108705.Free software: MIT licenseGetting Started1.Install psappippipinstallpsapcondacondainstallbioconda::psap2.Train classifierpsaptrain-f/path/to/peptide-trainingset.fasta-l/path/to/known/pps-proteins.txt(optional)-o/path/to/output/directory(optional)The trained RandomForest classifier will be exported to json format and stored in the output directory.3.Predict llps scorepsappredict-f/path/to/peptide-testset.fasta-m/path/to/model.json(optional)-o/path/to/output/directory(optional)psap loads the default classifier stored in/data/modelwhen no model is provided with-m.
An example peptide fasta file can be found in thepsap/data/testsetfolder.4.Annotate peptide sequences (optional)psapannotate-f/path/to/peptide.fasta-l/path/to/known/pps-proteins.txt(optional)-o/path/to/output/directory(optional)Manually annotate a peptide fasta with biochemical features. This step is included in train and predict.CreditsThis package was adapted from thecookiecutterand theaudreyr/cookiecutter-pypackageproject template.
Package: psas_packet
ReusablePortland State Aerospace Societytelemetry
packet encoder, decoder, documentation, and other tools.Documentationhttp://psas-packet-serializer.readthedocs.orgInstallpip install psas_packetDevelopInstall locally in a virtual env:python setup.py installDo work and test:python setup.py testLicenseThis program 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.

This program 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.