Saravanan666/pypi-org huggingface dataset:
Package: pd2img
What can you do with Pd2img?This package allows you to open image files and convert them to a pandas Dataframe
After you are done with your work, you can save the dataframe as an Imagehow to use itEverything you need to knowfrom pd2img import Pd2Img
df = Pd2Img(r"C:\Users\Gamer\Documents\Downloads\WhatsApp Image 2022-04-21 at 5.07.14 PM.jpeg")  # creating an instance
df.to_file_rgb('f:\\testimagefile1.png')  # save the dataframe to an RGB image
df.to_file_rgba('f:\\testimagefile2.png')  # save the dataframe to an RGBA image 
np3 = df.to_numpy_rgb()  # convert the image to an numpy array (RGB, not BGR!)
np4 = df.to_numpy_rgba()  # convert the image to an numpy array (RGBA)

print(df.df)  # printing the dataframe
           y     x  red  green  blue
0          0     0  155    150   144
1          0     1  155    150   144
2          0     2  153    148   142
3          0     3  152    147   141
4          0     4  151    147   138
      ...   ...  ...    ...   ...
1224955  956  1275  189    190   185
1224956  956  1276  189    190   185
1224957  956  1277  189    190   185
1224958  956  1278  189    190   185
1224959  956  1279  189    190   185
Package: pd2slack
pd2SlackThis python project will automatically sync on call PagerDuty services to Slack User Groups.For example if you have an on call schedule such as:It will automatically create a slack user group as followsWith "Sidhartha Premkumar" as the sole member of @backend-oncall.The mapping is done via email matching, this assumes the pager duty email matches the slack email.RunningTo run, all you have to do is:> pip3 install pd2slack
> pd2slack -slackApiKey {SLACK_API_KEY} -pdApiKey {PD_API_KEY} -config {PATH_TO_CONFIG}We also support environment variable, for example:> export SLACK_API_KEY=123
> export PD_API_KEY=123
> pd2SlackDeployingYou can deploy this program by running the processpd2Slackon a schedule (based on how often you want to update). A cron might be the best way to deploySlack token permissions:You will need the following permissions on your slack token:users:read.emailusers:readusergroups:writeusergroups:readCustom Slack UserGroup NameYou can optionally pass-configPathto the command that points to a config (seeexampleConfig.json). This mapping will be used to only sync PagerDuty schedules with the name as a key inserviceMappingwith the slackGroup that is the corresponding value.In the example config we will only attempt to sync pager duty schedules with the nameBackend Pd Namewith the slack alias@slackAliasToUse-oncall.
Package: pd4web
pd4webpd4web: Running PureData Patches in Browsers with Web Audiopd4webempowers you to execute PureData patches directly in web browsers using advanced Web Audio technologies. This tool distinguishes itself from alternative approaches likehvccandWebPdby compiling the source code oflibpd, a feat made possible largely due to the contributions ofclaudeha. Withpd4web, you can compile virtually any PureData vanilla patch, along with a wide list of externals.Acknowledgements* Zack Lee for the GUI interface for patches;
* Jonathan Wilkes, Ivica Ico Bukvic, and the Purr Data team;
* Claude Heiland-Allen for creating [empd](https://mathr.co.uk/empd/) which was super helpful for building the emscripten backend;
* Chris McCormick and Dan Wilcox for the inspiration for the project;
* Miller Puckette and the Pd community for developing and maintaining Pd;Details and DocumentationFor more details and documentation, please visit theDocssection of this project.ContributeContribute to enabling running PureData in WebBrowsers! These are the main areas for your  contributions:Thepd4web/lib/folder, which contains files with special steps for compiling certainexternals/libraries.Thepd4web/src/template.c, used to pd4web to build themain.cfile.Thepd4web/pd4web.py, which configures themain.cfile.ExamplesNameDescriptionLinkAlgorithm IIt is a piece where I usepmpdandplaits~to make Algorithm Music.WebSiteCompiled ILive-Electronics music for Trumpet in developing yet!WebSite
Package: pd9530
Library to use Datalogic(r) PowerScan(r) PD-9530 with USB-COM or RS232 on Windows(r) and UNIXesThe package depends on pySerial for communication and pywin32 for sending keystrokes.PowerScan and DataLogic are registered trademarks of Datalogic ADC. in many countries, including the U.S.A. and the E.U.
Windows is a registered trademark by Microsoft Corporation
Package: pdal-parallelizer
Some processing on point clouds can be very time consuming, this problem can be solved by using several processes on a machine to run calculations in parallel. The pdal-parallelizer tool will allow you to fully use the power of your machine very simply to put it at the service of your processing.pdal-parallelizer is a tool that allows you to process your point clouds through pipelines that will be executed on several cores of your machine. This tool uses the flexible open-source Python library Dask for the multiprocess side and allows you to use the power of the Point Data Abstraction Library, PDAL to write your pipelines.It also protect you from any problem during the execution. Indeed, as the points clouds treatments can be really long, if something goes wrong during the execution you don’t want to restart this from the beginning. So pdal-parallelizer will serialize each pipeline to protect you from this.Read the documentation for more details :https://pdal-parallelizer.readthedocs.io/InstallationUsing Pippip install pdal-parallelizerUsing Condaconda install -c clementalba pdal-parallelizerGitHubThe repository of pdal-parallelizer is available athttps://github.com/meldig/pdal-parallelizerUsageConfig fileYour configuration file must be like that :{"input":"The folder that contains your input files (or a file path)","output":"The folder that will receive your output files","temp":"The folder that will contains your temporary files""pipeline":"Your pipeline path"}Processing pipelines with APIfrompdal_parallelizerimportprocess_pipelinesasprocessprocess(config="./config.json",input_type="single",timeout=500,n_workers=5,diagnostic=True)Processing pipelines with CLIpdal-parallelizer process-pipelines -c <config file> -it dir -nw <n_workers> -tpw <threads_per_worker> -dr <number of files> -d
pdal-parallelizer process-pipelines -c <config file> -it single -nw <n_workers> -tpw <threads_per_worker> -ts <tiles size> -d -dr <number of tiles> -b <buffer size>Requirements (only for pip installs)Python 3.9+ (eg conda install -c anaconda python)PDAL 2.4+ (egconda install -c conda-forge pdal)
Package: pdal-plugins
PDAL Python plugins allow you to process data with PDAL intoNumpyarrays.
They support embedding Python in PDAL pipelines with thereaders.numpyandfilters.pythonstages.InstallationPyPIPDAL Python plugins are installable via PyPI:pip install pdal-pluginsGitHubThe repository for PDAL’s Python plugins is available athttps://github.com/PDAL/python-pluginsRequirementsPDAL 2.4+Python >=3.7Numpy (egpip install numpy)scikit-build (egpip install scikit-build)
Package: pdan
pdanSummarypdanis a Python library that implements the algorithm ofSkorobogatov, G. et al., 2021for convex polygon decomposition into separate parts depending on the area
requirements.In what followspythonis an alias forpython3.8or any later
version (python3.9and so on).InstallationInstall the latestpip&setuptoolspackages versions:python-mpipinstall--upgradepipsetuptoolsUserDownload and install the latest stable version fromPyPIrepository:python-mpipinstall--upgradepdanDeveloperDownload the latest version fromGitHubrepositorygitclonehttps://github.com/LostFan123/pdan.gitcdpdanInstall dependencies:poetryinstallUsage>>>frompdanimportminimizing_split,Contour,Point,Polygon>>>contour=Contour([Point(0,0),Point(1,0),Point(1,1),Point(0,1)])>>>part,other=minimizing_split(contour,0.5,key=lambdax,y:x.length)>>>assertPolygon(part).area==Polygon(other).area==0.5DevelopmentBumping versionPreparationInstallbump-my-version.Pre-releaseChoose which version number category to bump followingsemver
specification.Test bumping versionbump-my-versionbump--dry-run--verbose$CATEGORYwhere$CATEGORYis the target version number category name, possible
values arepatch/minor/major.Bump versionbump-my-versionbump--verbose$CATEGORYThis will set version tomajor.minor.patch-alpha.ReleaseTest bumping versionbump-my-versionbump--dry-run--verbosereleaseBump versionbump-my-versionbump--verbosereleaseThis will set version tomajor.minor.patch.Running testsPlain:pytestInsideDockercontainer:docker-compose--filedocker-compose.cpython.ymlupBashscript (e.g. can be used inGithooks):./run-tests.shor./run-tests.shcpythonPowerShellscript (e.g. can be used inGithooks):.\run-tests.ps1or.\run-tests.ps1cpython
Package: pdappend
This project is under development.pdappendRunpdappendfrom the command line to append csv, xlsx, and xls files.Installationpip install pdappendUsingpdappendAppend specific filespdappend file1.csv file2.csv file3.csvAppend specific file types in your directorypdappend *.csvAppend allpdappend-compatible files in your directorypdappend .Supported file typescsvxlsxlsx:Not supported in Python 3.6 environments(downgrade toxlrd 1.2.0or convert to.xls)Documentation(TODO)
See thewikifor more onpdappend.ContributingPull requests are welcome!
Package: pdat
PulsarDataToolboxPython package for dealing with PSRFITS files.Free software: MIT LicenseDocumentation:https://PulsarDataToolbox.readthedocs.io.FeaturesThe Pulsar Data Toolbox has tools built for building pulsar data formats. Only
thePSRFITSstandard is currently supported, but if you are interested in
another format submit an issue or a pull request!CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.2.2 (2020-10-13)Fixed issue with version of fitsio, and removed PyUp.0.2.1 (2018-12-17)Fixed Python 2 string bug.0.2.0 (2018-12-17)Second release on PyPI.Added ability to use deal effectively with PSR mode PSRFITS files.Fixed issue with ASCII text.0.1.0 (2017-08-21)First release on PyPI.
Package: pdata
pdataA general-purpose Python library for data analysis and visualization.Modules overviewdatagen: generate simulated data from probability distributionsdirstructure: analyze a directory in a file system and construct Pandas dataframes with data extracted from file names and the directory structuredistributions: estimate parameters of probability distributionsml: helper functionality for machine learning tasks based on Scikit-learnpdutils: utilities for processing of data stored in Pandas dataframestheanoutils: utilities for creation and manipulation of Theano/PyMC3 objectsvisualize: data visualization using Matplotlib
Package: pd-auto-ml
Python MindsDB SDKIt enables you to connect to a midnsDB server and use it in a similar way to mindsb_native.Installpip install mindsdb_sdkExample of usagefrommindsdb_sdkimportSDK# connectmdb=SDK('http://localhost:47334')# upload datasourcemdb.datasources['home_rentals_data']={'file':'home_rentals.csv'}# create a new predictor and learn to predictpredictor=mdb.predictors.learn(name='home_rentals',datasource='home_rentals_data',to_predict='rental_price')# predictresult=predictor.predict({'initial_price':'2000','number_of_bathrooms':'1','sqft':'700'})TestsBefore run tests, change SERVER and CREDENTIAL constants intests/test.py. After that, runpython3 tests/test.pyTest file - is a good place where you can find some examples of api usage.API Reference(WIP)class MindsDB(server: str, params: dict)class DataSources()class DataSource()class Predictors()class Predictor()class Proxy()
Package: pd-aws-lambda
Handle AWS Lambda events.Events are passed to handlers for processing.
Each event is passed to the handler in this order:Handler defined in the eventHTTP events handler (for WSGI applications)SQS events handler (if configured)Default handler (if configured)Logger handler (if no default is defined)Provided Handlerspd_aws_lambda.handlers.wsgi.handler: convert HttpAPI requests to WSGI environs.pd_aws_lambda.handlers.shell.handler: Run shell commands.pd_aws_lambda.handlers.logger.handler: log the received event and context.UsageAddpd_aws_lambdato your application dependencies.poetry add pd_aws_lambdaSet the required environment variables according to your needs in yourPython Deployapplication configuration.# Python path to the WSGI application that will handle HTTP requests.PD_WSGI_APPLICATION=my_django_project.wsgi.application# Python path to the handler for SQS events.PD_SQS_HANDLER=my_custom_handlers.sqs_handler# Python path to the default fallback handler.PD_DEFAULT_HANDLER=my_custom_handlers.default_handlerCustom handlersA handler is a python function that receives aneventand acontextand
does something with them. It can return a value if it makes sense for the type
of event. For example, HttpAPI handlers like the one we use to call your wsgi
application (pd_aws_lambda.handlers.wsgi.handler) should return a dictionary
compatible with theAWS HttpAPIto form an HTTP response.defhandler(event,context):"""
    I handle AWS Lambda invocations.

    I print the received event and context.
    """print("The event:",event)print("The context:",context)Python Deploy
Package: pdAzTables
PdAzTablesThis is a simple library that makes it easy to get a Pandas DataFrame from a table in Azure Table Storage (Azure Data Lake's Table service)# Import libraryfrompdaztablesimportAzTable# Create service object with login infotable_service=AzTable('Your data lake conn string here')# Get Pandas DataFrame!table_service.get_table('Table name here')Change Log0.0.6 (21/12/2020)(Very unstable!) First basic version of set table. Optional creation.Fix to get_table.0.0.5 (09/12/2020)Added columns and filter parameters to get_table.0.0.4 (08/12/2020)Added list_tables method.Added n_rows to get_table, which will get first n rows.Added a bunch of docstrings.0.0.3 (08/12/2020)Added Manifest so building from source doesnt fail.0.0.2 (08/12/2020)Added keywords, still giving this some form.0.0.1 (04/12/2020)First Release
Package: pdb2af
pdb2af v0.0.20pdb2af uses SIFTS (https://www.ebi.ac.uk/pdbe/docs/sifts/) to download protein structures from the AlphaFold Protein Structure Database that overlap with PDB structures.Installationpdb2af is installed using pip (https://packaging.python.org/en/latest/tutorials/installing-packages/).pip install pdb2afRunning pdb2afpdb2af reads in a text file with PDB IDs. You need to be connected to the internet.pdb2af -i pdb_ids.txtOptions:-itext file with list of PDB IDs-uupdate the SIFTS mapping between PDB IDs and UniProt accession numbersHelpContact Nick Fowler (njfowler.com) for support, queries or suggestions.
Package: pdb2pqr-htmd-propka30
This directory is the home for the [PDB2PQR software](http://www.poissonboltzmann.org/docs/structures-ready/).Some useful information:
* See the [install notes](INSTALL.md) to build pdb2pqr.
* Using pdb2pqr [binaries](BINARY_README.md)
* Latest [changelog](ChangeLog.md)
* For testing the [server](ServerNotes.md) (for developers)Please see the [user guide](http://www.poissonboltzmann.org/docs/pdb2pqr-algorithm-description/) for documentation and the [COPYING file](COPYING) for license information.Please see [programmer’s guide](http://www.poissonboltzmann.org/docs/pdb2pqr-programmers/) for information on working with the PDB2PQR code.
Package: pdb2sql
PDB2SQLpdb2sqlis a Python package that leverage SQL queries to parse, manipulate and process PDB files. It provides:a powerfulpdb2sqlobject to convert PDB data in SQL databasestrcuture transformation functions (rotations, translations...)useful capablities tocalculate structure interface (contact atoms and residues)calculate structure similarity (iRMSD, lRMSD, FNAT, DockQ...)Installationpip install pdb2sqlDocumentationThe documentation of the package alongside small tutorial can be found at :https://pdb2sql.readthedocs.ioQuick Examplepdb2sqleasily allows to load a PDB file in an object. Once loaded, the data can be parsed using SQL queries. To facilitate the adoption of the tool simple methods have been developped to wrap the SQL queries in simple methods. For example obtaining the positions of all carbon, nitrogen and oxygen atoms of chain A from all residues but VAL and LEU, one can use :frompdb2sqlimportpdb2sqlpdb=pdb2sql('1AK4.pdb')atoms=pdb.get('x,y,z',name=['C','N','O'],no_resName=['VAL','LEU'],chainID='A')
Package: pdb4all
pdb4allConvert between common protein pdb formats and namesInstallationRequirespython 3.7+. No additional dependencies are needed.pdb4allis frequently uploaded toPyPI. To install it, execute the following command:pip install pdb4allUsagepdb4all <options> .pdbCurrently supported ForceFields name conventionsAmberCharmmOPLSCurrently supported formats (software)FastaMaestroGROMACSfDynamo
Package: pdb4qt
Set a tracepoint in the Python debugger that works with PyQt4It usesipdbif is availableInstallFrom PyPI:$ pip install pdb4qtOr by downloading the source and running:$ python setup.py installOr, for the latest git version:$ pip install git+git://github.com/nqnwebs/pdb4qt.gitUsageSimply importset_tracefrompdb4qtand call it where you want
to do the breakpoint:from pdb4qt import set_trace; set_trace()Why it’s needed?Standard pdb/ipdb set_trace returns a loop ofQCoreApplication::exec:The event loop is already runningthat disallow to input anything.CreditsIt’s heavily inspired on the answer of the userquarkfromthis stackoverflow’s thread
Package: pdbbasic
PDBBasicBasic Functions for Protein Structure DataInstallpip install pdbbasicUsageimportnumpyasnpimporttorchimportpdbbasicaspdbb# simple PDB file readcoord1=pdbb.readpdb('filename.pdb')# coord1.shape -> (N, 4, 3), N=length, 4=atoms:(N,CA,C,O), 3=coordinates:(x,y,z)# read PDB with information (chain-id, residue-number, residue-type, occupancy, b-factor)coord1,info1=pdbb.readpdb('filename.pdb',with_info=True)# read mmCIF filecoord1,info1=pdbb.readmmcif('filename.cif',with_info=True)# download from PDBcoord1,info1=pdbb.download('7bqd',with_info=True)# calc RMSDca1=coord1[:,1]ca2=pdbb.readpdb('filename.pdb',CA_only=True)rmsd_np=pdbb.rmsd(ca1,ca2)# Kabsch superpositioncoo_sup1,coo_sup2=pdbb.kabsch(ca1,ca2)# torsion angletorsion=pdbb.torsion_angles(coord1)# torsion.shape -> (N, 3), 3=dihedrals:(phi,psi,omega)# distance matrixdistmat_within=pdbb.distance_matrix(ca1)distmat_between=pdbb.distance_matrix(ca1,ca2)# torch Tensor is applicablermsd_torch=pdbb.rmsd(torch.Tensor(ca1),torch.Tensor(ca2))# Frame representation like AlphaFold (translation, rotation)trans,rot=pdbb.coord_to_frame(coord1)# trans.shape -> (N, 3), rot.shape -> (N, 3, 3)frame=trans,rotcoord_recon=pdbb.frame_to_coord(frame)# FAPE (Frame Aligned Position Error)frame1=pdbb.coord_to_frame(coord1)frame2=pdbb.coord_to_frame(coord2)fape=pdbb.FAPE(frame1,frame2)# batched calculation is applicableca_batch1=np.repeat(np.expand_dims(ca1,axis=0),100,axis=0)ca_batch2=np.repeat(np.expand_dims(ca2,axis=0),100,axis=0)bb_batch=np.repeat(np.expand_dims(coord1,axis=0),100,axis=0)rmsd_batch=pdbb.rmsd(ca_batch1,ca_batch2)sup_batch1,sup_batch2=pdbb.kabsch(ca_batch1,ca_batch2)torsion_batch=pdbb.torsion_angles(bb_batch)distmat_batch=pdbb.distance_matrix(ca_batch1)coord_batch=np.repeat(np.expand_dims(coord1,axis=0),100,axis=0)frame_batch=pdbb.coord_to_frame(coord_batch)coord_recon_batch=pdbb.frame_to_coord(frame_batch)fape_batch=pdbb.FAPE(frame_batch,frame_batch)# all against all RMSD calculationrmsd_matrix=pdbb.rmsd_many_vs_many(ca_batch1)Requirementpython3numpypandaspytorcheinops
Package: pdb-clone
FeaturesImplement the most recent Python 3 features of pdb, as defined in the Python 3pdb documentation. The pdb command line interface remains unchanged except for the newdetachandthreadpdb commands.Improve significantly pdb performance. With breakpoints, pdb-clone runs just below the speed of the interpreter while pdb runs 10 to 100 times slower than the interpreter, seePerformances.Extend pdb with remote debugging. A remote debugging session may be started when the program stops at apdb.set_trace_remote()hard-coded breakpoint, or at any time and multiple times by attaching to the process main thread. SeeRemoteDebuggingFix pdb long standing bugs entered in the Python issue tracker, see theNews.Add a bdb comprehensive test suite (more than 70 tests) and run both pdb and bdb test suites.pdb-clone runs the same source code on all the supported versions of Python, which are:Python 3: from version 3.2 onward.Python 2: version 2.7.See also theREADMEand the projecthome page.Report bugs to theissue tracker.UsageInvoke pdb-clone as a script to debug other scripts. For example:$ pdb-clone myscript.pyOr use one of the different ways of running pdb described in thepdb documentationand replace:import pdbwith:from pdb_clone import pdb
Package: pdbcs
pdb for setuptools console scriptsUsingA console script installed by setuptools is a thin wrapper that loads
the defined entry point and invokes it. pdbcs uses the console script
name to load the entry point itself and invoke the debugger. The
debugger automatically stops on the first line of the main function of
the console script.$ pdbcs /Users/dhellmann/Envs/pdbcs/bin/pdbcs
> /Users/dhellmann/Devel/pdbcs/pdbcs/pdbcs/main.py(11)main()
-> parser = argparse.ArgumentParser()
(Pdb)
Package: pdbdownload
A Python script to download PDB files associated with a Portable Executable (PE).FeaturesDownload PDB symbols frommsdl.microsoft.com.Process a single or a batch of PortableExecutable (PE) files.Installationpdbdownload is available onPyPi:python3 -m pip install pdbdownloadUsage$ ./pdbdownload.py -h
usage: pdbdownload.py [-h] (-f PE_FILE | -d PE_DIR) [-S SYMBOLS_DIR] [-v]

Description message

optional arguments:
  -h, --help            show this help message and exit
  -f PE_FILE, --pe-file PE_FILE
  -d PE_DIR, --pe-dir PE_DIR
  -S SYMBOLS_DIR, --symbols-dir SYMBOLS_DIR
                        Output dir where symbols will be downloaded.
  -v, --verbose         Verbose mode. (default: False)ExampleTo recursively download the PDBs of all executables in a folder, use:pdbdownload -d . -S .ContributingPull requests are welcome. Feel free to open an issue if you want to add other features.
Package: pdbeccdutils
pdbeccdutilsA set of python tools to deal with PDB chemical components definitions.
for small molecules, taken from thewwPDB Chemical Component DictionaryandwwPDB The Biologically Interesting Molecule Reference DictionaryThe tools use:RDKitfor chemistry. Presently tested with2022.09.4GEMMIfor parsing cif files.scipyfor depiction quality check.numpyfor molecular scaling.networkxfor bound-molecules.Please note that the project is under active development.Installation instructionspdbeccdutilsrequires RDKit to be installed.
The official RDKit documentation hasinstallation instructions for a variety of platforms.
For linux/mac OS this is most easily done using the anaconda python with commands similar to:conda create -n rdkit-env rdkit python=3.9conda activate rdkit-envOnce you have installed RDKit, as described above then install pdbeccdutils using pip:pip install pdbeccdutilsFeaturesgemmi CCD read/write.Generation of 2D depictions (No image availablegenerated if the flattening cannot be done) along with the quality check.Generation of 3D conformations.Fragment library search (PDBe hand currated library, ENAMINE, DSI).Chemical scaffolds (Murcko scaffold, Murcko general, BRICS).Lightweight implementation ofparity methodby Jon Tyzack.RDKit molecular properties per component.UniChem mapping.TODO listAdd more unit/regression tests to get higher code coverage.Further improvements of the documentation.DocumentationThe documentation depends on the following packages:sphinxsphinx_rtd_thememyst-parsersphinx-autodoc-typehintsNote thatsphinxneeds to be a part of the virtual environment, if you want to generate documentation by yourself.
Otherwise it cannot pickrdkitmodule.sphinx_rtd_themeis a theme providing niceReadtheDocsmobile friendly style.Generate.rstfiles to be included as a part of the documentation. Inside the directorypdbeccdutils/docrun the following commands to generate documentation.Alternatively, use themyst-parserpackage to get the Markdown working.Use the following to generate initial markup files to be used by sphinx.  This needs to be used when adding another sub-packages.sphinx-apidoc -f -o /path/to/output/dir ../pdbeccdutils/Use this to re-generate the documentation from the doc/ directory:make html