Saravanan666/pypi-org huggingface dataset:
Package: eeUtil
eeUtilWrapper for easier data management with Earth Engine python sdkRequires account with access to Google Cloud Storage and Earth Engine.import eeUtil

# initialize from environment variables
eeUtil.init(project='my-project', bucket='my-bucket')

# create image collection
eeUtil.createFolder('mycollection', imageCollection=True)

# upload image to collection
eeUtil.uploadAsset('image.tif', 'mycollection/myasset')
eeUtil.setAcl('mycollection', 'public')
eeUtil.ls('mycollection')

# export image to cloud storage and download
eeUtil.downloadAsset('mycollection/myasset')Installpip install eeUtilDevelopgit clone https://github.com/fgassert/eeUtil.git
cd eeUtil
pip install -e .Nice things?More consistent python bindingsAdds recursivecopy,move,remove,setAcl,createFolder.GEE paths not starting with/,users/projects/are relative to your user root folder (users/<username>orprojects/<project-id>/assets)uploadanddownloadstage files via Google Cloud Storage so you don't have
to.UsageThe easiest way to authorize eeUtil is usingservice account credentials. Once you create a service account and download yourcredentials.jsonset these in your environment.export GOOGLE_APPLICATION_CREDENTIALS=path/to/credentials.jsonInitalize these credentials by callingeeUtil.init().eeUtil.init()If you don't provide credentials to eeUtil.init(), it defaults to reading from credentials from the environment, and attempts to read credentials as saved byearthengine authenticatefor Earth Engine andgcloud auth application-default loginfor Google Cloud Storage.eeUtil.init(service_account=GEE_SERVICE_ACCOUNT, 
            credential_path=GOOGLE_APPLICATION_CREDENTIALS, 
            project=GEE_PROJECT, 
            bucket=GEE_STAGING_BUCKET, 
            credential_json=GEE_JSON)service_accountService account name. For more information on GEE service accounts, see:https://developers.google.com/earth-engine/service_account[default: GEE_SERVICE_ACCOUNT]credential_pathPath to json file containing private key. This orcredential_jsonis required for service accounts.[default: GOOGLE_APPLICATION_CREDENTIALS]projectProject to use for GEE and GCS bucket.[default: GEE_PROJECT or CLOUDSDK_CORE_PROJECT]bucketStorage bucket for staging assets for ingestion. Will create new bucket if none provided.[default: GEE_STAGING_BUCKET]credential_jsonPass json string as alternative tocredential_path.[default: GEE_JSON]
Package: eeval
encrypted-evaluationA Python framework to build client/server applications, where the server hosts models for evaluation over encrypted inputs, then the client can encrypt his model input and send it to the server for evaluation and get back the encrypted result.Features:fire: Hosting models for encrypted evaluation in a RESTful API:cyclone: Client to send encrypted inputs for evaluation in a remote API:zap: CLI utility to encrypt/decrypt, generate keys, and communicate between the client and serverUsageYou can useeevaleither using the CLI or the programming API in Python.CLIThe CLI comes with the Python installation and it contains well documented instruction on how to make the job done. We expect it to be easy to use. If you find some difficulties using it, please open an issue to let us know how can it be better.$eeval
Usage:eeval[OPTIONS]COMMAND[ARGS]...Encryptedevaluationwithhomomorphicencryption

Options:-v,--verboseverboselevel[default:0]--install-completionInstallcompletionforthecurrentshell.--show-completionShowcompletionforthecurrentshell,tocopyitorcustomizetheinstallation.--helpShowthismessageandexit.

Commands:create-contextCreateaTenSEALcontextholdingencryptionkeysand...decryptDecryptasavedtensorencryptEncryptapicklednumpytensorevalEvaluateanencryptedinputonaremotehostedmodellist-modelsListmodelsavailablemodel-infoGetinformationaboutaspecificmodelpingCheckiftheAPIatURLisupserveStarttheAPIserverAPIWe show a basic client/server app where the client send an encrypted input to the server to be evaluated over a linear layer (nothing really useful), more advanced usage can be found on ourexamples section.ServerHere we use the linear layer model which is already implemented for showcasing purposes, otherwise, you should implement your own model by inheriting fromeeval.server.model.Modeland implementing the required methodimporteeval.serverasserverfromeevalimportmodels# register the LinearLayer modelserver.register_model(models.LinearLayer,versions=["0.1"])server.start(host="localhost",port=8000)ClientThe only thing the client need to know is how to encode and encrypt his data, the rest is handled byeeval.client.ClientfromeevalimportClientimporttensealastshostname="localhost"port=8000client=Client(hostname,port)# prepare the TenSEAL contextctx=ts.context(ts.SCHEME_TYPE.CKKS,8192,-1,[60,40,60])ctx.global_scale=2**40ctx.generate_galois_keys()# we know that the model hosted on the server needs a vector of 16 as inputvec=[0.1]*16enc_vec=ts.ckks_vector(ctx,vec)# print some info about the models hosted on the servermodels=client.list_models()print("============== Models ==============")print("")fori,modelinenumerate(models):print(f"[{i+1}] Model{model['model_name']}:")print(f"[*] Description:{model['description']}")print(f"[*] Versions:{model['versions']}")print(f"[*] Default version:{model['default_version']}")print("")print("====================================")# send the encrypted input and get encrypted outputresult=client.evaluate(model_name="LinearLayer",context=ctx,ckks_vector=enc_vec)print(f"decrypted result from the server:{result.decrypt()}")Installation$pipinstalleevalExamplesTBDLicenseGNU General Public License 3.0
Package: eevalue
EEValuesA simple class for dealing with engieering valuesWill print with Si prefix, and has an easy method to get the closest E-series value.>>>fromeevalueimportEEValueasEEV>>>R=EEV(18.91)>>>str(R.E(48,"ceil"))19.60>>>str(EEV(17950.10).E(192,"floor"))17.80k>>>str(EEV('2u2')*2)4.40µ>>>str(EEV('2K1234',precision=4)*2)4.2468k
Package: eeve
A simple, flexible and powerfull event triggerUsagepython-meeveOr from the project folder:python run.pyDefault GUI UsageThe program flow is split in 3 main components:
Actions, triggers and events.Actionsare the execution, they can vary from opening an app to
sending a keystroke to the OS. They arewhathappens.Triggersmake events happen. They usually run in background
and activate events. They arewhenit happens.Eventsare the glue between triggers and actions.
It can contain many triggers and many actions. When
an event is activated, it runs its actions in sequence.
You can add many triggers to an event and every time one of the
added triggers fires, the event is activated and will run all its actions in order.Actions and triggers can also accept arguments, which documentation
can be accessed using the (?) button on the editing page. The
documentation is up to the trigger or action’s developer to write.
However, eeve also shows what arguments the action or trigger accepts
by analyzing the code.Variablescan also be used in actions. They can be from one of the three types:local variables, that live while the event is running and are deleted as soon as the
last action is run. They can be accessed only by the actions inside that single run.
You can access them in a argument by a single $.
Eg: $countevent variables(AKA task variables), that are accessible from any action from the event and are deleted when
eeve stops running or the event is deleted. You can access them by using two $
Eg: $$countglobal variables, that are accessible by any action running, regardless of the
event. They are deleted when eeve stops running. You can access them by using three $
Eg: $$$countInstallationFrom pip:pip install-UeeveFrom source:pip install-e.orpython setup.py installRequirementsCompatibilityOnly tested on windows x64, but should work on any other OS just fine. Actions and triggers, however, have their own compatibilityLicenceMIT LicenceAuthorseevewas written byVictor Marcelino.
Package: eeweather
EEweather— tools for matching to and fetching data from NCDC ISD, TMY3, or CZ2010 weather stations.EEweather comes with a database of weather station metadata, ZCTA metadata, and GIS data that makes it easier to find the right weather station to use for a particular ZIP code or lat/long coordinate.Read the docs.InstallationEEweather is a python package and can be installed with pip.$ pip install eeweatherSupported Sources of Weather DataNCDC Integrated Surface Database (ISD)Global Summary of the Day (GSOD)NREL Typical Meteorological Year 3 (TMY3)California Energy Commission 1998-2009 Weather Normals (CZ2010)FeaturesMatch by ZIP code (ZCTA) or by lat/long coordinatesUse user-supplied weather station mappingsMatch within climate zonesIECC Climate ZonesIECC Moisture RegimesBuilding America Climate ZonesCalifornia Building Climate Zone AreasUser-friendly SQLite database of metadata compiled from primary sourcesUS Census Bureau (ZCTAs, county shapefiles)Building America climate zone county listsNOAA NCDC Integrated Surface Database Station HistoryNREL TMY3 sitePlot maps of outputsContributingDev installation:$ pipenv --python 3.6.4  # create virtualenv with python 3.6.4
$ pipenv install --dev   # install dev requirements with pipenv
$ pipenv install -e .    # install package in editable mode
$ pipenv shell           # activate pipenv virtual environmentBuild docs:$ make -C docs htmlAutobuild docs:$ make -C docs livehtmlCheck spelling in docs:$ make -C docs spellingRun tests:$ pytestRun tests on multiple python versions:$ toxUpload to pypi (using twine):$ python setup.py uploadUse with DockerTo use with docker-compose, use the following:Run a tutorial notebook (copy link w/ token, open tutorial.ipynb):$ docker-compose up jupyterLive-edit docs:$ docker-compose up docsOpen a shell:$ docker-compose run --rm shellRun tests:$ docker-compose run --rm testRun the CLI:$ docker-compose run --rm eeweather --helpNotice Regarding CZ2010 DataThere may be conditions placed on their international commercial use.
They can be used within the U.S. or for non-commercial international activities without restriction.
The non-U.S. data cannot be redistributed for commercial purposes.
Re-distribution of these data by others must provide this same notification.Seefurther explanationhere.
Package: eez-backup
eez-backupAnother convenience wrapper forrestic.InstallYou can simply installeez-backupfrom PyPI viapython-mpipinstalleez-backupSetupeez-backupassumesbackup.ymlto be present in your home directory, thus create it.
You can usetests/demo/config.ymlas a template.Now, you can initialize theresticrepositories by runningbackuprepo-mapinit... and then back up your data by runningbackuprunThat's it!CLI interfaceusage: backup [-h] [-v] [-c] [-r] [-p] {run,repo-map,profile-map} ...

Another convenience wrapper for restic

positional arguments:
  {run,repo-map,profile-map}
                        commands
    run                 run backup and forget for all profiles
    repo-map            run any restic command for all given repositories
    profile-map         run any restic command for all given profiles

options:
  -h, --help            show this help message and exit
  -v, --verbose         log level (disables progress bars if set)
  -c , --config         config file to use, default is ~/.backup.yml
  -r , --repository     repository to use, use all repositories by default, can be used multiple times
  -p , --profile        profile to use, use all profiles by default, can be used multiple times(backup --help)GlossaryRepositories:refer to a target locations for your backups and map 1:1 toresticrepositories.Profiles:define a set of directories/files to be in-/excluded from a backup among other options. Per profile and
backup asnapshotis created.
Package: efaar-benchmarking
EFAAR_benchmarkingThis library enables computation and retrieval of metrics to benchmark a whole-genome perturbative map created by the pipeline.
Metrics that can be computed using this repo are pairwise gene-gene recall for the reactome, corum, and humap datasets which
are publicly available.By default, we do not filter on perturbation fingerprint, although filtering is available through the parameters to thebenchmarkfunction.
We compute the metrics for three different random seeds used to generate empirical null entities.See our bioRxiv paper for the details:https://www.biorxiv.org/content/10.1101/2022.12.09.519400v1Here are the descriptions for the constants used in the code to configure and control various aspects of the benchmarking process:BENCHMARK_DATA_DIR: The directory path to the benchmark annotations data. It is obtained using the resources module from the importlib package.BENCHMARK_SOURCES: A list of benchmark sources, including "Reactome", "HuMAP", and "CORUM".PERT_LABEL_COL: The column name for the gene perturbation labels.PERT_SIG_PVAL_COL: The column name for the perturbation p-value.PERT_SIG_PVAL_THR: The threshold value for the perturbation p-value.PERT_TYPE_COL: The column name for the perturbation type.PERT_TYPE: The specific perturbation type, which is "GENE" by default.WELL_TYPE_COL: The column name for the well type.WELL_TYPE: The specific well type, which is "query_guides".RECALL_PERC_THR_PAIR: A tuple representing the threshold pair (lower threshold, upper threshold) for calculating recall percentages.RANDOM_SEED: The random seed value used for random number generation.RANDOM_COUNT: The number of runs for benchmarking.N_NULL_SAMPLES: The number of null samples used in benchmarking.MIN_REQ_ENT_CNT: The minimum required number of entities for benchmarking.InstallationThis package is installable viapip.pipinstallefaar_benchmarkingReferencesReactome:Gillespie, M., Jassal, B., Stephan, R., Milacic, M., Rothfels, K., Senff-Ribeiro, A., Griss, J., Sevilla, C., Matthews, L., Gong, C., et al. (2022). The reactome pathway knowledgebase 2022. Nucleic Acids Res. 50, D687–D692. 10.1093/nar/gkab1028.CORUM:Giurgiu, M., Reinhard, J., Brauner, B., Dunger-Kaltenbach, I., Fobo, G., Frishman, G., Montrone, C., and Ruepp, A. (2019). CORUM: the comprehensive resource of mammalian protein complexes-2019. Nucleic Acids Res. 47, D559–D563. 10.1093/nar/gky973.HuMAP:Drew, K., Wallingford, J.B., and Marcotte, E.M. (2021). hu.MAP 2.0: integration of over 15,000 proteomic experiments builds a global compendium of human multiprotein assemblies. Mol. Syst. Biol. 17, e10016. 10.15252/msb.202010016.
Package: efaciency
efaciencyA package to simplify working withEFAblocks and settlement periods in the GB electricity trading system.InstallationThis package can be installed via pip:$pipinstallefaciencyExamplesSettlement periodsDefine a settlement period and get the corresponding half-hour datetime.>>>fromdatetimeimportdate>>>fromefaciencyimportSettlementPeriod>>>sp=SettlementPeriod(settlement_date=date(2023,7,1),settlement_period=24)>>>sp["ts"]datetime.datetime(2023,7,1,11,30,tzinfo=<DstTzInfo'Europe/London'BST+1:00:00DST>)Get the corresponding EFA information and settlement information for a given timestamp.>>>fromdatetimeimportdatetime>>>fromefaciencyimportSettlementPeriod>>>sp=SettlementPeriod(ts=datetime(2023,7,1,11,30))>>>sp{'settlement_date':datetime.date(2023,7,1)'settlement_period':24,'ts':datetime.datetime(2023,7,1,11,30,tzinfo=<DstTzInfo'Europe/London'BST+1:00:00DST>),'efa_date':datetime.date(2023,7,1),'efa_block':4,}Create half-hourly range for all SPs in between two dates.>>>fromdatetimeimportdate>>>fromefaciencyimportsettlement_period_range>>>sp_range=settlement_period_range(...from_efa_date=date(2023,7,1),...to_efa_date=date(2023,7,2),...)>>>sp_range[0]{'settlement_date':datetime.date(2023,6,30)'settlement_period':47,'ts':datetime.datetime(2023,6,30,23,0,tzinfo=<DstTzInfo'Europe/London'BST+1:00:00DST>),'efa_date':datetime.date(2023,7,1),'efa_block':1}EFA blocksDefine EFA blocks and get the corresponding start and end datetimes.>>>fromdatetimeimportdate>>>fromefaciencyimportEFABlock>>>efa=EFABlock(efa_date=date(2023,7,1),efa_block=3)>>>efa["start_ts"].strftime("%Y-%m-%d%H:%M")'2023-07-01 07:00'>>>efa["end_ts"].strftime("%Y-%m-%d%H:%M")'2023-07-01 11:00'Create a range of all EFA blocks between two dates.>>>fromdatetimeimportdate>>>fromefaciencyimportefa_block_range>>>efa_range=efa_block_range(date(2023,7,1),date(2023,7,2))>>>efa_range[0]{'efa_date':datetime.date(2023,7,1),'efa_block':1,'start_ts':datetime.datetime(2023,6,30,23,0,tzinfo=<DstTzInfo'Europe/London'BST+1:00:00DST>),'end_ts':datetime.datetime(2023,7,1,3,0,tzinfo=<DstTzInfo'Europe/London'BST+1:00:00DST>),}ContributionPlease make a pull request or log an issue on GitHub.LicenseCode is released as free software under the MIT License (seeLICENSEfile).
Package: efaqa-corpus-raw
心理咨询问答原始语料库，仅限研究用途。心理咨询问答原始语料库（以下也称为“本数据集”，“本语料库”）是为应用人工智能技术于心理咨询领域制作的高品质语料，语料是爬取心理咨询领域公开的网站的数据，经过整理和脱敏制作而成。消息总文本字符数四千四百多万，具体说明见下。https://github.com/chatopera/efaqa-corpus-raw
Package: efaqa_corpus_zh
Emotional First Aid Dataset, 心理咨询问答语料库Welcome据我们所知，这是心理咨询领域首个开放的QA语料库：该语料库的内容由现实世界的用户提出，高质量的答案由心理咨询专业人士或网友提供。
所以这是一个具有真正价值的语料，而不是玩具。该语料库可用于训练聊天机器人。
另一方面，这种语料库的其他用法也是可能的。
例如，通过分类标记，训练模式识别不同咨询问题。欢迎任何进一步增加此数据集的想法。阅读详细文档
Package: eFatura
eFaturaVergi veya TC Kimlik Numarasından E-Fatura Mükellefiyet Sorgusu🚀 KurulumPyPI (Lib - CLI - UI)# YüklemekpipinstalleFatura# Güncellemekpipinstall-UeFaturaFlatHub (UI)# Yüklemekflatpakinstallflathuborg.KekikAkademi.eFatura# Çalıştırmakflatpakrunorg.KekikAkademi.eFatura📝 KullanımLibfromeFaturaimporte_faturaprint(e_fatura("11111111111"))# Vergi Numarası veya TC Kimlik Numarası>>True|FalseCLIeFatura11111111111# » [~] 11111111111 Numarası E-Fatura Mükellefi Değildir..UIeFaturaGUI# veyaflatpakrunorg.KekikAkademi.eFaturaKendiniz Paketlemek İsterseniz(genişletmek için tıklayın!)Python# Depoyu Çekhttps://github.com/keyiflerolsun/eFatura.gitcdeFatura# Gerekli Ortamları Kurpipinstall-Upipsetuptoolswheel# Paketi Yüklepipinstall.# Artıkları Temizlerm-rfbuild*.egg-info# ÇalıştıreFatura# CLIeFaturaGUI# GUI# Paketi KaldırpipuninstalleFaturaFlatPak# Depoyu Çekgitclonehttps://github.com/keyiflerolsun/eFatura.gitcdeFatura# Gerekli Dosyaları AlmvShared/*.yml.&&mvShared/SRC.# Gerekli Ortamları Kurflatpakremote-add--if-not-existsflathubhttps://flathub.org/repo/flathub.flatpakrepo
flatpakremote-add--if-not-existsflathub-betahttps://flathub.org/beta-repo/flathub-beta.flatpakrepo
flatpakupdate&&flatpakupgrade
flatpakinstallflathuborg.gnome.{Platform,Sdk}//44# Paketleflatpak-builder--user--install--force-cleanbuild-dirorg.KekikAkademi.eFatura.yml# Artıkları Temizlerm-rf.flatpak*.vscodebuild-dir&&find.|grep-E"(__pycache__|\.pyc|\.pyo$)"|xargsrm-rf# Çalıştırflatpakrunorg.KekikAkademi.eFatura# Paketi Kaldırflatpakuninstallorg.KekikAkademi.eFatura📝 Proje Sahibi✅kmprens/CheckEinvoice🌐 Telif Hakkı ve LisansCopyright (C) 2023 bykeyiflerolsun❤️️GNU GENERAL PUBLIC LICENSE Version 3, 29 June 2007Koşullarına göre lisanslanmıştır..♻️ İletişimBenimle iletişime geçmek isterseniz,Telegram'dan mesaj göndermekten çekinmeyin;@keyiflerolsun💸 Bağış Yap☕️ Kahve Ismarla@KekikAkademiiçin yazılmıştır..
Package: efa-utils
efa_utilsCustom utility functions for exploratory factor analysisInstallationInstall with pip:pipinstallefa_utilsFunctionsefa_utils.reduce_multicollFunction to reduce multicollinearity in a dataset (intended for EFA). Uses the determinant of the correlation matrix to determine if multicollinearity is present. If the determinant is below a threshold (0.00001 by default), the function will drop the variable with the highest VIF until the determinant is above the threshold. Requires statsmodels package.efa_utils.kmo_checkFunction to check the Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) and Bartlett's test of sphericity for a dataset. Requires statsmodels package. Main use is to print a report of total KMO and item KMOs, but can also return the KMO values.efa_utils.parallel_analysisFunction to perform parallel analysis to determine the number of factors to retain. Requires matplotlib.efa_utils.iterative_efaFunction to perform iterative exploratory factor analysis. Runs EFA with an iterative process, eliminating variables with low communality, low main loadings or high cross loadings in a stepwise process. If parallel analysis option is to be used, requires matplotlib.efa_utils.print_sorted_loadingsPrint strongly loading variables for each factor. Will only print loadings above load_thresh for each factor.efa_utils.rev_items_and_returnTakes an EFA object and automatically reverse-codes (Likert-scale) items where necessary and adds the reverse-coded version to a new dataframe. Returns the new dataframe.efa_utils.factor_int_reliabilityTakes a pandas dataframe and dictionary with name of factors as keys and list of variables as values. Prints results for the internal reliability for each factor. Requires reliability package.
Package: efb-gpg-middleware
Module ID:blueset.gpgA middleware for EH Forwarder Bot that encrypts and
decrypts messages using GnuPG.This middleware simply encrypts outgoing messages with
recipients’ registered public key, and decrypt incoming
messages with your own secret key.All encrypted messages should be and will be ASCII
armored. All messages that was not successfully
encrypted/decrypted will be delivered untouched.This middleware only encrypt/decrypt text messages.
Other types of messages are kept untouched.DependenciesEH Forwarder Bot >=2.0GnuPGAn imported key pair that is used to decrypt incoming
messagesGetting StartedMake sure you have access to a public key server
of your choice using thegpginstalled.Have at least one key pair registered in local GPG.Install this middleware:pip3 install efb-gpg-middlewareCreate a config file in your current EFB profile:<PATH_TO_EFB_PROFILE>/blueset.gpg/config.yaml:# Signature of your own key pair (required)
key: BD6B65EC00638DC9083781D5D4B65BB1A106200A

# Passphrase to the key pair (optional)
password: test

# Trust all key in the local stoage
# (optional, default: true)
always_trust: true

# Path to the GPG binary
# (optional, default: search from $PATH)
binary: /usr/bin/gpg

# Preferred public key server
# (optional, default: pgp.mit.edu)
server: pgp.mit.eduHow to useSend commands as text messages in chats to interact with
the middleware. All command messages will not be
delivered to slave channel.gpg`infoorgpg`show: Show the key fingerprint used for this chat.gpg`search query: Search for a key from the key server.gpg`bind fingerprinthex: Use key for specified fingerprint for a chat.gpg`clear: Do not encrypt messages sent to this chat.When you have told the middleware to use a key for a chat,
it will encrypt all your text messages sent to this chat with
the key specified.The middleware will try to decrypt all incoming text messages
with GnuPG regardless of settings, and only update the message
if the decryption is successful.FootnoteIf you find this module not as useful, don’t be disappointed. This is just
a demo to show you what you can do with EFB Middlewares.Experimental localization supportGPG Middleware supports localized user interface prompts
experimentally, by setting the locale environmental variable
(LANGUAGE,LC_ALL,LC_MESSAGESorLANG) to one
of oursupported languages. Meanwhile, you can help to
translate this project into your languages onour Crowdin page.
Package: efb-link-preview-middleware
LinkPreview: A middleware for EFBNoticeMiddleware ID:catbaron.link_previewLinkPreviewis a middleware for EFB to generqate link preview for the first url contained by the message.For url refering to an image, the image should be sent as preview.Add\npat the begining of message to avoid link preview for current message.You need to useMessageBlockeron top ofEFB. Please check the document and install EFB first.DependensePython >=3.6EFB >=2.0.0b15beautifulsoup4InstallInstallgit clone https://github.com/catbaron0/efb-link_preview-middleware
cd efb-link_preview-middleware
sudo python setup.py installRegister to EFB
Followingthis documentto edit the config file. The config file by default is~/.ehforwarderbot/profiles/default. It should look like:master_channel: foo.demo_master
slave_channels:
- foo.demo_slave
- bar.dummy
middlewares:
- foo.other_middlewares
- catbaron.link_previewYou only need to add the last line to your config file.Restart EFB.