Saravanan666/pypi-org huggingface dataset:
Package: pydreamlo
PYDREAMLOSimple,free and easy-to-use Leader Board system usinghttps://dreamlo.com.InstallUse pip to install$pipinstallpydreamloor$pip3installpydreamloor$python-mpipinstallpydreamloor Build from sourceor Copy thesrc/pydreamlofolder to your project directory and import it.Usage:Create a dreamlo url by going tohttps://dreamlo.comFor using this LeaderBoard you need 2urls (private dreamlo urlandpublic dreamplo url)Creating theurlsprivate url: copy theprivate-keygiven by dreamlo and join it with the url.(the protocol may be different)pr_key="http://dreamlo.com/{your_private_key}"private url: copy thepublic-keygiven by dreamlo and join it with the url.(the protocol may be different)pu_key="http://dreamlo.com/{your_public_key}"Usedreamlopyto work with your leader board.frompydreamloimportLeaderBoardpr_key="http://dreamlo.com/{your_private_key}"pu_key="http://dreamlo.com/{your_public_key}"cool_leader_board=LeaderBoard(pr_key,pu_key)The moduledreamlopyis initialized,now you use the methods in the module to perform the operations..add(username,score,time,text)add()is used to add a new user to the leader board.usernameandscoreare necessary parameters.Thetimeis the time taken to finish.(Sorting based on time is available)cool_leader_board.add("some-user",100,10,"user is cool")returns a string "OK" if sucessful.delete(username)delete()is used to delete a specific user from the leaderboard.usernameis the only parameter(Note:only one user can have a specific username)cool_leader_board.delete("some-user").clear()clear()is used to clear the entire leaderboard.cool_leader_board.clear().get(index:int = 0,upto:int = 0,rtype:str = 'json',sort:str='')used to get the leaderboard data.indexdefines the index from where should the results start showing.(default is 0)uptodefines the number of users to return after the index.(default is 0,so it will return the entire leaderboard)rtypedefines the return type of thegetmethod.rtype = "json"rtype = "xml"rtype = "pipe"rtype = "quote"sortis an additional command return the sorted leaderboard based ontimetaken by the usersort='a'for ascending(less time first)sort='d'for descending(greter time first)"""This will return all the leaderboard data starting from index 0 to (index 0 + next 50 spaces) and will return as a "json" and arranges the leaderboard based on time(the user with less time shows at first)."""cool_leader_board.get(0,50,"json",'a').get_new_sorted(index:int = 0,upto:int = 0,rtype:str = 'json',sort:str='')used to retrieve the leaderboard with respect to time score's was added.(same parameter as.get()).get_user(username,rtype)used to get deatils of a specific user.NOTE: This uses dreamlo service and cool-dev-guy is not related with the service,this module is just a python package for using the dreamlo service which was made for unity engine.So use the package at your own risk.
Package: pydreamlo-cool-guy
PYDREAMLOSimple,free and easy-to-use Leader Board system usinghttps://dreamlo.com.Usage:Create a dreamlo url by going tohttps://dreamlo.comFor using this LeaderBoard you need 2urls (private dreamlo urlandpublic dreamplo url)Creating theurlsprivate url: copy theprivate-keygiven by dreamlo and join it with the url.(the protocol may be different)pr_key=http://dreamlo.com/{your_private_key}private url: copy thepublic-keygiven by dreamlo and join it with the url.(the protocol may be different)pu_key=http://dreamlo.com/{your_public_key}Usedreamlopyto work with your leader board.frompydreamloimportLeaderBoardpr_key=http://dreamlo.com/{your_private_key}pu_key=http://dreamlo.com/{your_public_key}cool_leader_board=LeaderBoard(pr_key,pu_key)The moduledreamlopyis initialized,now you use the methods in the module to perform the operations..add(username,score,time,text)add()is used to add a new user to the leader board.usernameandscoreare necessary parameters.Thetimeis the time taken to finish.(Sorting based on time is available)cool_leader_board.add("some-user",100,10,"user is cool")returns a string "OK" if sucessful.delete(username)delete()is used to delete a specific user from the leaderboard.usernameis the only parameter(Note:only one user can have a specific username)cool_leader_board.delete("some-user").clear()clear()is used to clear the entire leaderboard.cool_leader_board.clear().get(index:int = 0,upto:int = 0,rtype:str = 'json',sort:str='')used to get the leaderboard data.indexdefines the index from where should the results start showing.(default is 0)uptodefines the number of users to return after the index.(default is 0,so it will return the entire leaderboard)rtypedefines the return type of thegetmethod.rtype = "json"rtype = "xml"rtype = "pipe"rtype = "quote"sortis an additional command return the sorted leaderboard based ontimetaken by the usersort='a'for ascending(less time first)sort='d'for descending(greter time first)"""This will return all the leaderboard data starting from index 0 to (index 0 + next 50 spaces) and will return as a "json" and arranges the leaderboard based on time(the user with less time shows at first)."""cool_leader_board.get(0,50,"json",'a').get_new_sorted(index:int = 0,upto:int = 0,rtype:str = 'json',sort:str='')used to retrieve the leaderboard with respect to time score's was added.(same parameter as.get()).get_user(username,rtype)used to get deatils of a specific user.
Package: pydream-rocket
# pydream-rocketControl Dream Cheeky USB rocket launchers.  Seehttps://github.com/codedance/Retaliationfor inspiration/source.## Permission Denied errorTo work around this:# You do not have to do this if you’re already in the dialout group
$ sudo usermod -a -G dialout $(whoami)
# Log out and log back in
$ sudo nano /etc/udev/rules.d/99-dreamcheeky-rocket.rules
# Add the following lines:
SUBSYSTEM==”usb”, ATTRS{idVendor}==”2123”, ATTRS{idProduct}==”1010”, MODE=”0666”, GROUP=”dialout”
SUBSYSTEM==”usb”, ATTRS{idVendor}==”0a81”, ATTRS{idProduct}==”0701”, MODE=”0666”, GROUP=”dialout”
# And then run
$ sudo service udev restart
Package: pydrift
Welcome topydrift0.2.15How do we measure the degradation of a machine learning process? Why does the performance of our predictive models decrease? Maybe it is that a data source has changed (one or more variables) or maybe what changes is the relationship of these variables with the target we want to predict.pydrifttries to facilitate this task to the data scientist, performing this kind of checks and somehow measuring that degradation.InstallpydriftWithpip:pip install pydriftWithconda:conda install -c conda-forge pydriftWithpoetrypoetry add pydriftStructureThis is intended to be user-friendly. pydrift is divided intoDataDriftCheckerandModelDriftChecker:DataDriftChecker: searches for drift in the variables, check if their distributions have changedModelDriftChecker: searches for drift in the relationship of the variables with the target, checks that the model behaves the same way for both data setsBoth can use a discriminative model (defined by parent classDriftChecker), where the target would be binary in belonging to one of the two sets, 1 if it is the left one and 0 on the contrary. If the model is not able to differentiate given the two sets, there is no difference!It also existsInterpretableDriftandDriftCheckerEstimator:InterpretableDrift: manages all of the stuff related to interpretability of drifting. It can show us the features distribution or the most important features when we are training a discriminative model or our predictive oneDriftCheckerEstimator: allowspydriftto be used as a sklearn estimator, it works lonely or in a pipeline, like any sklearn estimatorUsageYou can take a look to thenotebooksfolder where you can find one example for genericDriftChecker, one forDataDriftCheckerand other one forModelDriftChecker.Correct Notebooks RenderBecausepydriftuses plotly and GitHub performs a static render of the notebooks figures do not show correctly. For a rich view of the notebook, you can visitnbviewerand paste the link to the notebook you want to show, for example if you want to render1-Titanic-Drift-Demo.ipynbyou have to pastehttps://github.com/sergiocalde94/pydrift/blob/master/notebooks/1-Titanic-Drift-Demo.ipynbinto nbviewer.More InfoFor more info check the docs availablehereMore demos and code improvements will coming,if you want to contribute you can contact me (sergiocalde94@gmail.com), in the future I will upload a file to explain how this would work.
Package: pydrill
pydrillPython Driver forApache Drill.Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageFree software: MIT licenseDocumentation:https://pydrill.readthedocs.org.FeaturesPython 2/3 compatibility,Support for all rest API calls inluding profiles/options/metricsdocs with full list.Mapping Results to internal python types,Compatibility with Pandas data frame,Drill Authentication using PAM,InstallationVersion fromhttps://pypi.python.org/pypi/pydrill:$ pip install pydrillLatest version from git:$ pip install git+git://github.com/PythonicNinja/pydrill.gitSample usagefrom pydrill.client import PyDrill

drill = PyDrill(host='localhost', port=8047)

if not drill.is_active():
    raise ImproperlyConfigured('Please run Drill first')

yelp_reviews = drill.query('''
  SELECT * FROM
  `dfs.root`.`./Users/macbookair/Downloads/yelp_dataset_challenge_academic_dataset/yelp_academic_dataset_review.json`
  LIMIT 5
''')

for result in yelp_reviews:
    print("%s: %s" %(result['type'], result['date']))


# pandas dataframe

df = yelp_reviews.to_dataframe()
print(df[df['stars'] > 3])History0.3.4 (2017-04-24)Updated pypi listing long_description0.3.3 (2017-04-24)Fix pypi installation0.3.2 (2017-04-18)Support for dtype on to_dataframe0.3.1 (2017-03-06)Support for Drill Authentication using PAM0.3 (2017-02-15)requests response encoding (utf-8)support Python 3.6 support0.1.1 (2016-05-21)Anaconda requirements fixed0.1.0 (2016-05-19)First minor releaseUpdated docs0.0.2 (2016-04-24)First release on PyPI.Implementation of metrics/storage/options/statsBuilds are tested by docker container with Apache Drill runningsupport for pandas with ResultQuery.to_dataframe0.0.1 (2015-12-28)Project start
Package: pydrill_dsl
pyDrill-dslPythonic DSL forApache Drill.Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud StorageFree software: MIT licenseDocumentation:https://pydrill_dsl.readthedocs.org.FeaturesUses Peewee syntaxSupport for all storage pluginsSupport for drivers PyODBC and pyDrillSample usagefrom pydrill_dsl.resource import Resource

class Employee(Resource):
    first_name = Field()
    salary = Field()
    position_id = Field()
    department_id = Field()

    class Meta:
        storage_plugin = 'cp'
        path = 'employee.json'


Employee.select().filter(salary__gte=17000)

Employee.select().paginate(page=1, paginate_by=5)


salary_gte_17K = (Employee.salary >= 17000)
salary_lte_25K = (Employee.salary <= 25000)
Employee.select().where(salary_gte_17K & salary_lte_25K)

Employee.select(
    fn.Min(Employee.salary).alias('salary_min'),
    fn.Max(Employee.salary).alias('salary_max')
).scalar(as_tuple=True)

# creation of resource can be done without creation of class:
employee = Resource(storage_plugin='cp', path='employee.json',
                    fields=('first_name', 'salary', 'position_id', 'department_id'))History0.0.2 (2016-05-19)First release on PyPI.Uses Peewee syntaxSupport for all storage pluginsSupport for drivers PyODBC and pyDrillBuilds are tested by docker container with Apache Drill running0.0.1 (2016-02-18)Initial release on github.
Package: pydriosm
PyDriosmPyDriosm is an open-source tool that provides an effortless way to download and accessOpenStreetMap(OSM) data in popular file formats, such asshapefileandprotobuf binary format(PBF), which are freely available fromGeofabrikandBBBike. Additionally, the package offers a comprehensive solution for convenient I/O operations and efficient storage capabilities for parsed OSM data withinPostgreSQLdatabases. This means that users can easily read from and write to PostgreSQL databases, enabling efficient data manipulation, querying, and other essential tasks. Whether you are a researcher, practitioner, or simply interested in working with OSM data, PyDriosm is a valuable tool to streamline your workflow and enhance your experience.InstallationTo install the latest release of PyDriosm fromPyPIviapip:pipinstall--upgradepydriosmPlease also refer toInstallationfor more information.Quick startFor a comprehensive guide with practical examples, please check out thequick-start tutorial. This tutorial showcases how to use the package for various tasks, such as downloading, parsing, and performing storage I/O operations on OSM data using a PostgreSQL database.DocumentationThe full PyDriosm documentation [HTML] [PDF], which includes more detailed examples, is hosted onReadTheDocs.LicensePyDriosm is licensed underGNU General Public License v3.0or later (GPLv3+).The freeOpenStreetMapdata, which is used for the development of PyDriosm, is licensed under theOpen Data Commons Open Database License(ODbL) by theOpenStreetMap Foundation(OSMF).AcknowledgementThe development of PyDriosm, including the example code that demonstrates how to use the package, heavily relies on freely availableOpenStreetMapdata. The author would like to express sincere gratitude to all theOpenStreetMap contributorsfor their invaluable contributions in making this data accessible to the community.Cite asFu, Q. (2020). PyDriosm: an open-source tool for downloading, reading and PostgreSQL-based I/O of OpenStreetMap data. Zenodo.doi:10.5281/zenodo.4281194@software{qian_fu_pydriosm_4281194,author={Qian Fu},title={{PyDriosm: an open-source tool for downloading, readingand PostgreSQL-based I/O of OpenStreetMap data}},year=2020,publisher={Zenodo},doi={10.5281/zenodo.4718623},url={https://doi.org/10.5281/zenodo.4281194}}(Please also refer to the export options fromZenodoto reference the specific version of PyDriosm as appropriate.)ContributorsQian Fu🌱💻🧪📖
Package: pydrip
Python Drip ClientThis python drip client is maintained by Matthew Clarkson fromPaper Planes, a data driven digital marketing agency based in Brisbane, Queensland Australia.InstallationTo install this package runpip install pydrip.UsageTo use this package, simply import and initialize the DripClient from python-drip as follows:frompydripimportDripClientdrip=DripClient(token=YOUR_ACCESS_TOKEN,account_id=YOUR_ACCOUNT_ID)# Get Subscribersstatus,data=drip.subscribers()subscribers=data['subscribers']# Create a Subscribersubscriber={'subscribers':{[{'email':'test@test.com'}]}}drip.create_or_update_subscriber(subscriber)About 90% of the API is covered.TodoDocumentationTest it ;)
Package: pydrive-cli
# USAGE:NAME: accountDESCRIPTION: handle multiple accounts of google drive and switch between accounts.-l : list all accounts added to pyDrive-a : add an account to pyDrive-s : switch to a different account, provide email id-i : print account info of the current account-S : switch to shared folder of the current account-P : switch to mydrive folder of the current accountNAME: lsDESCRIPTION: List  information  about  the FILEs (the current directory by default).-m : display mime type of each file.NAME: rmDESCIPTION: Delete files from the drive account.-r : recursively delete all files in the folder-e : empty trashNAME: getDESCRIPTION: download a file or folder from the drive account-e : export the file as pdf.-d : specify the download location. By default ~/DriveDownloads—std-out : print the contents of the file to standard output instead of downloading.NAME: putDESCRIPTION: upload a file or folder to the drive account–std-in : upload the content from standard input to drive accountNAME: shareDESCRIPTION: share a file or folder to the given email account-r : read only permission-w : write only permission
Package: pydrivedol
pydrivedolpydrive (googledrive) with a simple (dict-like or list-like) interfaceTo install:pip install pydrivedolA basic Google Drive persister implemented with the pydrive library.
Keys must be names of files.**** Authentication ***
Drive API requires OAuth2.0 for authentication.Go to APIs Console (https://console.cloud.google.com/cloud-resource-manager) and make your own project.Search for ‘Google Drive API’, select the entry, and click ‘Enable’.Select ‘Credentials’ from the left menu, click ‘Create Credentials’, select ‘OAuth client ID’.Now, the product name and consent screen need to be set -> click ‘Configure consent screen’ and follow the instructions.
Once finished:Select ‘Application type’ to be Web application.Enter an appropriate name.Inputhttp://localhost:8080for ‘Authorized JavaScript origins’.Inputhttp://localhost:8080/for ‘Authorized redirect URIs’.Click ‘Save’.Click ‘Download JSON’ on the right side of Client ID to download client_secret_.json.
see:https://pythonhosted.org/PyDrive/quickstart.htmlfor details.Rename the file to “client_secrets.json” and place it in your working directory.>>>frompydriveimportGoogleDrivePersister>>>s=GoogleDrivePersister()>>>k='foo'>>>v='bar'>>>for_keyins:...dels[_key]>>>len(s)0>>>s[k]=v>>>s[k]'bar'>>>s.get(k)'bar'>>>len(s)1>>>list(s.values())['bar']>>>kinsTrue>>>dels[k]>>>kinsFalse>>>len(s)0
Package: pydrivelist
Drive List PathsThis small script application when run will create a json file of paths in a Google Drive to their associated identifiers.  This was primarily created to serve a small set of conference websites with a fair number of PDF files.  These conferences use a static site generator, and it was easier to reference links to their paths within the Google drive than by their identifiers.InstallationThis script can be installed via pip:python -m pip install pydrivelist.The script requiresPyDrive2.  The Drive API must be enabled in order for this to work with instructutions located at thePyDrive2 documentation.  Quoting from the current documentation (as of November 2021):Go to APIs Console and make your own project.Search for ‘Google Drive API’, select the entry, and click ‘Enable’.Select ‘Credentials’ from the left menu, click ‘Create Credentials’, select ‘OAuth client ID’.Now, the product name and consent screen need to be set -> click ‘Configure consent screen’ and follow the instructions. Once finished:Select ‘Application type’ to be Web application.Enter an appropriate name.Inputhttp://localhost:8080/for ‘Authorized redirect URIs’.Click ‘Create’.Click ‘Download JSON’ on the right side of Client ID to download client_secret_.json.The downloaded file has all authentication information of your application. Rename the file to “client_secrets.json” and place it in your working directory.
Package: pydriver
What is PyDriver?PyDriver is a Python (2.7, 3.x) framework for training and evaluating object detectors
and classifiers in road traffic environment. It aims at researchers experimenting
with learning based 3D object detection, classification and tracking.What can I do with PyDriver?PyDriver helps you with following tasks:read data from standard datasets (currently integrated:KITTI)reconstruct 3D scene from stereo images, detect/remove ground plane, restrict viewport etc.detect 3D keypoints and extract 3D feature descriptorstrain classifiers available inscikit-learn(support vector machines, decision trees and many more)visualize point clouds, extracted keypoints and detections usingPoint Cloud Libraryevaluate produced detections with respect to dataset ground truthOf course, you can write your own modules and enhancements such as interfaces to
your custom dataset or implement novel feature descriptors. The point of PyDriver
is to provide a basic pipeline for object detection which you can enhance with your
own algorithms without reimplementing the routine stuff.Which licence does PyDriver use?PyDriver is subject to the MIT licence.How do I install PyDriver?PyDriver installation documentationWhere are the docs?PyDriver documentationWhere is the source?The most current development version is available here:http://github.com/lpltk/pydriver
Package: pydriveV3
PyDriveV3 is a wrapper module for Google drive API v3 enabling easy server to server communication.
In order to use PydriveV3 with your application you need a Google service account. Please follow stepshereto create a service account.RequirementsPythonDeveloper account in googleService account key jsonInstallation$ pip install pydriveV3Sample usagefrom pydriveV3 import Clientclient = Client(‘service_credentials.json’)files = client.get_all_files()DocumentationPleasevisitfor documentationContributionPull requests are welcome.
Package: pydriveways
This is Driveways by Andres Canas, Dylan Fay, Henry Parker, Zack Saadioui.DrivewaysDrivewaysInstallation from PyPI:pip install pydrivewaysrunmyserverallowed hosts = ['0.0.0.0', '10.0.2.2'] for mobile #comment out in settings.py if needed for other web port***GDAL libraries must be installed on device$ sudo aptitude install gdal-bin libgdal-dev$ sudo aptitude install python3-gdal$ sudo aptitude install binutils libproj-devInstalling APKAPK is stored under "Realeases" on GitHubInstall APK on device after server is runningTested on device running api 27 (Android 8.1 Oreo)#Git Repohttps://github.com/andrescanas01/driveways.gitResourcesSimplest Git TutorialDjango API ListDjango TutorialsAPI'sDjango CalendarDjango MapDjango FormsDRIVEWAYSEnter destination and be shown available driveways to park nearbyUser can list their available parking spaces to earn extra incomeDriveways is meant to offer private parking.\Features / Planning#TODO: Finish FeaturesMap Functionality: Google API'sObject MarkersPrice/(day,timeframe), location, time,Search Functionalityaddress searchdistance functionBuyer PortalSeller Portal-   Make Listing (Update DB):
-   Cost, Time, AddressSign in PageAccount DetailsPaymentAccount InformationLater features:User TestingLater: Todo.
Package: pydrobert-gpyopt
# pydrobert-gpyoptUtilities to streamline GPyOpt interfaces for ML## How to useGPyOpt is incredibly powerful, but a tad clunky. This lightweight packageprovides two utilities in ``pydrobert.gpyopt`` to make things easier. Thefirst, ``GPyOptObjectiveWrapper``, wraps a function for use in GPyOpt. Thesecond, ``bayesopt``, takes a wrapper instance and a``BayesianOptimizationParams`` instance and handles the optimization loop.Here's an example:``` pythondef foo(a, d, b, **kwargs):r = a ** d + bweirdness = kwargs['weirdness']if weirdness == 'flip':r *= -1elif weirdness == 'null':r = 0return rwrapped = GPyOptObjectiveWrapper(foo)wrapped.set_fixed_parameter('b', 1.)  # 'b' will always be 1wrapped.set_variable_parameter('a', 'continuous', (-1., 1.))  # a is real# btw [-1,1] incwrapped.set_variable_parameter('d', 'discrete', (0, 3))  # d is an int# btw [0, 3] incwrapped.add_parameter('weirdness')  # we can add new parameters as dynamic# keyword args if the method has a **# parameterwrapped.set_variable_parameter(  # weirness one of the elements in the list'weirdness', 'categorical', ('flip', 'null', None))params = BayesianOptimizationParams(seed=1,  # setting this makes the bayesian optimization deterministic# (assuming foo is deterministic)log_after_iters=5,)best = bayesopt(wrapper, params, 'hist.csv')```If you provide a history file to read/write from, optimization can beresumed after unexpected interrupts. There are a lot of options to ``bayesopt``that are listed in ``BayesianOptimizationParams``.## InstallationGPyOpt currently does not have a Conda build, so pydrobert-gpyopt is availablevia PyPI and source install.``` bashpip install pydrobert-gpyopt```