Saravanan666/pypi-org huggingface dataset:
Package: erddaputil
ERDDAPUtilERDDAPUtil provides additional tools for managing an ERDDAP installation which focus on:Managing ERDDAP in a Kubernetes environment with high availabilityAutomating the deployment of new datasets and updated files for ERDDAP to serveObtaining statistics from ERDDAP in a more common formatThe tool is divided into four main components:The ERDDAPUtil service (or daemon) which performs management operations.A command line interface for the ERDDAPUtil serviceA web interface for the ERDDAPUtil service that also provides Prometheus metricsAn AMPQ worker service that listens for AMPQ messages and interfaces with the ERDDAPUtil serviceDocumentationInstallationERDDAPUtil can be installed as a Python package viapython -m pip install erddaputil. It
is also available as a Docker imagedfomeds/erddaputil.Visit theQuickstart Guideto obtain
details on getting starting with the tool.For most features, ERDDAPUtil requires access to the ERDDAP and Tomcat directory structures
so that it can access and modify files. It should therefore be installed on the same physical
server or in the same Kubernetes Pod as ERDDAP.FeaturesERDDAP Management FeaturesTrigger dataset reload, including a "badFiles" or a "hard" reloadCompile ERDDAP'sdataset.xmlfile from a directory of XML filesBlock or unblock IP addresses and emails in ERDDAP'sdataset.xmlfileAdd or remove IP addresses from the unlimited requests entry indatasets.xmlScrape ERDDAP'sstatus.htmlpage and turn it into Prometheus statisticsScrape Tomcat's access logs and turn them into Prometheus statisticsRemove old log files from Tomcat and ERDDAPAdditional FeaturesExecute ERDDAP management commands (reloads, compiles, blocks, unblocks) from the command
line or by authenticated HTTP requestDefine clusters of ERDDAP servers and pass all commands executed on one server to all other
servers in the cluster (requires RabbitMQ or Azure Service Bus)
Package: erddapy
erddapyerddapy: ERDDAP + Python.Table of contentsOverviewExampleGet in touchLicense and copyrightOverviewEasier access to scientific data.erddapy takes advantage of ERDDAP's RESTful web services and creates the ERDDAP URL for any request,
like searching for datasets, acquiring metadata, downloading the data, etc.What is ERDDAP?
ERDDAP unifies the different types of data servers and offers a consistent way to get the data in multiple the formats.
For more information on ERDDAP servers please seehttps://coastwatch.pfeg.noaa.gov/erddap/index.html.Documentation and codeThe documentation is hosted athttps://ioos.github.io/erddapy.The code is hosted athttps://github.com/ioos/erddapy.InstallationForcondausers you cancondainstall--channelconda-forgeerddapyor, if you are apipuserspython-mpipinstallerddapyNote that, if you are installing therequirements-dev.txt, theirispackage
is namedscitools-irison PyPI sopipusers must rename that before installing.ExamplefromerddapyimportERDDAPe=ERDDAP(server="https://gliders.ioos.us/erddap",protocol="tabledap",)e.response="csv"e.dataset_id="whoi_406-20160902T1700"e.constraints={"time>=":"2016-07-10T00:00:00Z","time<=":"2017-02-10T00:00:00Z","latitude>=":38.0,"latitude<=":41.0,"longitude>=":-72.0,"longitude<=":-69.0,}e.variables=["depth","latitude","longitude","salinity","temperature","time",]df=e.to_pandas()Get in touchReport bugs, suggest features or view the source code onGitHub.Projects using erddapyargopygliderpygdutilscolocateintake-erddapioos_qcSimilar projectsrerddapimplements a nice client for R that performs searches on a curated set of servers instead of a query per server like erddapy.erddap-python99% of the same functionality as erddapy but with a JavaScript-like API.License and copyrightErddapy is licensed under BSD 3-Clause "New" or "Revised" License (BSD-3-Clause).Development occurs on GitHub athttps://github.com/ioos/erddapy.
Package: erdesktop
Event ReminderDesktop application which helps to finish all tasks in time.To start with this project (development), run the following:# create a virtual environment if required$virtualenv-ppython3venv
$sourcevenv/bin/activate# Install requirements and run the server$pipinstall-rrequirements.txt# if running on Windows machine:$pipinstall-rwindows_requirements.txt

$makeresources
$python./erdesktop/app_main.pyAuthor:Yuriy LisovskiyLicenseThis project is licensed under the GNU General Public License, Version 3 software license - see theLICENSEfile for details.
Package: erd-from-json-table-schema
Does what it says on the tin; creates an entity-relationship diagram from a [JSON Table Schema](https://specs.frictionlessdata.io/table-schema/)Massive thanks to [iburadempa](https://github.com/iburadempa/) for creating [jts_erd](https://github.com/iburadempa/jts_erd), from which this code is derived. jts_erd was designed with Postgres exports in mind; this code assumes a slightly different packaging structure and so probably won’t work for that use case.Development has used Python 3.8.Documentation:https://erd-from-json-table-schema.readthedocs.org/
Package: erdio
ERDioThis is CLI utility to generate editable Draw.io ERD from DBML or updating existing diagram.InstallationYou can install ERDio using pip:pipinstallerdioQuick startAssuming you have already installeddbtanddbterdutility to generate artifacts.Usedbtto generate docs.$dbtdocsgenerate16:15:02Runningwithdbt=1.5.316:15:03Registeredadapter:postgres=1.5.316:15:03Found241models,492tests,4snapshots,0analyses,850macros,0operations,18seedfiles,70sources,0exposures,0metrics,0groups16:15:0316:15:12Buildingcatalog16:15:12Catalogwrittento./target/catalog.jsonThis will create two artifact files contains:manifest.jsonincludes all tests and documentationcatalog.jsonincludes the set of all columns in the databaseUsedbterdto generate DBML from dbt artifacts.$dbterdrun2023-07-2516:16:45,768-dbterd-INFO-Runwithdbterd==1.2.4(main.py:54)2023-07-2516:16:46,359-dbterd-INFO-./target/output.dbml(base.py:75)This will create DBML manifest to be used for diagraming.Create new Draw.io diagram.erdiorun
Package: erdkeys
erdkeysThis are Flying Stone's little tools for converting betweenelrondwallet pem files and json
keystores. Please be aware that the private key is written in plaintext in the pem file. The json
keystores are much safer to use.Use at your own risk and remember: if you run code you haven't read and understood, you can't be
sure that it is not sending me your keys ;-)installingBefore insptalling erdkeys, make sure thatpip3in installed. If you already installederdpy, you should already havepip3.$ pip3 install erdkeysThis will also install a couple of dependencies: the extremely coolcryptographylibrary and a small module to deal with bech32 addresses.usage$ pem2json.py pem_file password$ json2pem.py json_file passwordFor instance, one of myBattle of Nodeswallet keystore iserd1g2ufua664sxjvxmw5hh72he3xy6w4gk9l8e4lvfjeyh8d0jk7gdsfrpdu0.jsonand I need to convert it to pem format for use witherdpy:json2pem.py erd1g2ufua664sxjvxmw5hh72he3xy6w4gk9l8e4lvfjeyh8d0jk7gdsfrpdu0.json mYpAsSwOrDwill produce a fileerd1g2ufua664sxjvxmw5hh72he3xy6w4gk9l8e4lvfjeyh8d0jk7gdsfrpdu0.pemin the same directory. You will get an error in case the keystore is corrupted or you entered the wrong password.When creating a keystore with pem2json, the password must satisfy the same requirements as the officialwallet.licenseMIT
Package: erdos
ERDOS Python InterfaceBuilding from SourceFirst, runpip install maturinto installMaturin,
which aids in building Rust crates with Python bindings.Debug BuildFrom thepython/directory, runmaturin develop.This will build the debug version of the rust backend resulting in more debug messages, faster compile times, and slower performance.Release BuildRunmaturin develop --release.This will build the release version of the Rust backend resulting in less debug messages, slower compile times, and faster performance.Building WheelsTo generate wheels, runmaturin build.This will generate wheels and store them intarget/wheels.For more information, including on building portable wheels that comply with manylinux, seeMaturin's READMEand theMaturin guide.
Package: erebor
ereborErebor is a lightweight key-value store with a Redis-like syntax.InstallationTo install the erebor server:pipinstallereborUsageRun the server like so:$ereborYou can verify erebor is running by connecting to 127.0.0.1:8044.$nclocalhost8044keys[]setfoobar
OK
keys['foo']getfoo
barAPIErebor recognizes the following commands:set   <key> <value>  set a key to a value
    del   <key>          remove a key and its value
    get   <key>          retrieve the value of a key
    keys  [prefix]       return a list of keys starting with prefixConfigurationErebor listens on 127.0.0.1:8044. You can change this by modifying theportvariable at the top of the file.$vim$(whicherebor)You can also change the bind address. However, for security reasons, it is not
recommended to bind on 0.0.0.0 and expose the database to the world.By default, erebor runs in ephemeral mode, where keys are only stored in memory
and not persisted to disk. To run in persistence mode, run with the-poption.
This will save the database to a local JSON file called keys.db.Other notesThe erebor API uses vanilla TCP sockets, so you can make API requests usingnetcat.$echo"set home$(catindex.html)"|nc-q0localhost8044OKYou can also talk to erebor programmatically using any language that can speak TCP:importsocket# Setup a socket to the host and port where erebor is running.sock=socket.socket(socket.AF_INET,socket.SOCK_STREAM)sock.connect(("127.0.0.1",8044))deferebor(message):sock.send(message.encode())returnsock.recv(1024).decode().strip()print(erebor("set foo bar"))# OKprint(erebor("get foo"))# bar
Package: erebusfall
erebusfallApply a simple ice-volume correction to marine-isotopeδ18OandδDproxy records, in Python.The correction uses theLR04benthic stack fromLisiecki and Raymo, 2005. The stack is scaled so that theLGM-to-present
change is assumed to be 1.0 ‰ in accordance with the pore-water estimate ofSchrag et al. 1996. The
package is adapted from the ice-volume correction inTierney et al. 2017.ExampleStart by importingerebusfall,numpy:importerebusfallasefimportnumpyasnp...and creating a hypothetical proxy time
series...age_ka=np.arange(0,20,1)proxy=np.random.normal(loc=-2.0,size=len(age_ka))Now we can plug this intoef.icevol_correction()with a few key options:proxy_adjusted=ef.icevol_correction(age_ka,proxy,proxytype='d18o',timeunit='ka')We first plug in the proxy age and proxy values. Theproxytype='d18o'indicates that we're dealing with δ18O. We can setproxytype='dd'for a δD
record. Thetimeunitargument indicates thatage_kais in thousands of
years before present. There are also options for for "years BP" and
"million years BP". The output from the function,proxy_adjusted, is the
corrected isotope proxy as a numpy array.Seehelp(ef.icevol_correction)for more documentation.InstallationYou can install the packagefrom PyPIwithpip install erebusfallIf you want to useconda:conda install erebusfall -c sbmalevDevelopment and SupportSource code ishosted onlineunder an Open
Source license. Please feel free to file anybugs and issuesyou find.
Package: erede-payments
SDK PythonSDK de integração eRedeUtilizandoAutorizando uma transaçãofromeredeimport*store=Store("PV","TOKEN",Environment.sandbox())transaction=Transaction(12345,"Reference")transaction.credit_card("5448280000000007","123","12","2020","Fulano de Tal")transaction.set_additional(3456,12)try:transaction=eRede(store).create(transaction)iftransaction.returnCode=="00":print("Transação aprovada com sucesso. O tid é:{}".format(transaction.tid))exceptRedeErrorase:print("Opz[{}]:{}".format(e.code,e))Por padrão, a transação é capturada automaticamente; caso seja necessário apenas autorizar a transação, o métodoTransaction.capture_transaction(False)deverá ser chamado com o parâmetroFalse:fromeredeimport*store=Store("PV","TOKEN",Environment.sandbox())transaction=Transaction(12345,"Reference")transaction.credit_card("5448280000000007","123","12","2020","Fulano de Tal").capture_transaction(False)try:transaction=eRede(store).create(transaction)iftransaction.returnCode=="00":print("Transação aprovada com sucesso. O tid é:{}".format(transaction.tid))exceptRedeErrorase:print("Opz[{}]:{}".format(e.code,e))Autorizando uma transação com MCC dinâmicofromeredeimport*store=Store("PV","TOKEN",Environment.sandbox())transaction=Transaction(12345,"Reference")transaction.credit_card("5448280000000007","123","12","2020","Fulano de Tal")transaction.mcc("LOJADOZE","22349202212",SubMerchant("1234","Sao Paulo","Brasil"))try:transaction=eRede(store).create(transaction)iftransaction.returnCode=="00":print("Transação aprovada com sucesso. O tid é:{}".format(transaction.tid))exceptRedeErrorase:print("Opz[{}]:{}".format(e.code,e))Autorizando uma transação com identificação de plataformafromeredeimport*store=Store("PV","TOKEN",Environment.sandbox())transaction=Transaction(12345,"Reference")transaction.credit_card("5448280000000007","123","12","2020","Fulano de Tal")transaction.set_additional(1234,12)try:transaction=eRede(store).create(transaction)iftransaction.returnCode=="00":print("Transação aprovada com sucesso. O tid é:{}".format(transaction.tid))exceptRedeErrorase:print("Opz[{}]:{}".format(e.code,e))Autorizando uma transação IATAfromeredeimport*store=Store("PV","TOKEN",Environment.sandbox())transaction=Transaction(12345,"Reference")transaction.credit_card("5448280000000007","123","12","2020","Fulano de Tal")transaction.set_iata("code123","250")try:transaction=eRede(store).create(transaction)iftransaction.returnCode=="00":print("Transação aprovada com sucesso. O tid é:{}".format(transaction.tid))exceptRedeErrorase:print("Opz[{}]:{}".format(e.code,e))
Package: eredesscraper
E-REDES ScraperDescriptionThis is a web scraper that collects data from the E-REDES website and can upload it to a database.
Since there is no exposed interface to the data, this web scraper was developed as approach to collect it programatically.
A high-level of the process is:The scraper collects the data from the E-REDES website.A file with the energy consumption readings is downloaded.[ Optional ] The file is parsed and the data is uploaded to the selected database.[ Optional ] A feature supporting only the insertion of "deltas" is available.This package supports E-REDES website available at time of writing 23/10/2023.
The entrypoint for the scraper is the pagehttps://balcaodigital.e-redes.pt/login.InstallationThe package can be installed using pip:pipinstalleredesscraperConfigurationUsage is based on a YAML configuration file.config.ymlholds the credentials for the E-REDES website and
the database connection. Currently,only InfluxDB is supportedas a database sink.Templateconfig.yml:eredes:# eredes credentialsnif:<my-eredes-nif>pwd:<my-eredes-password># CPE to monitor. e.g. PT00############04TW (where # is a digit). CPE can be found in your bill detailscpe:PT00############04TWinfluxdb:# url to InfluxDB.  e.g. http://localhost or https://influxdb.my-domain.comhost:http://localhost# default port is 8086port:8086bucket:<my-influx-bucket>org:<my-influx-org># access token with write accesstoken:<token>UsageCLI:ersconfigload"/path/to/config.yml"# get current month readingsersrun-dinfluxdb# get only deltas from last month readingsersrun-wprevious-dinfluxdb--delta# get readings from Mayersrun-wselect-dinfluxdb-m5Docker:# get readings from May# docker argsdockerrun--rm-vconfig.yml:/config.yml\# latest `ers` imageghcr.io/rf-santos/eredesscraper:latest\# calling `ers`ersrun-wcurrent-dinfluxdbPython:fromeredesscraper.workflowsimportswitchboardfrompathlibimportPath# get deltas from current month readingsswitchboard(name="current",db="influxdb",config_path=Path("./config.yml")ydelta=True)# get readings from May 2023switchboard(name="select",db="influxdb",config_path=Path("./config.yml"),month=5,year=2023)FeaturesAvailable workflows:current: Collects the current month consumption.previous: Collects the previous month consumption data.select: Collects the consumption data from an arbitrary month parsed by the user.Available databases:influxdb: Loads the data in an InfluxDB database. (https://docs.influxdata.com/influxdb/v2/get-started/)RoadmapAdd workflow for retrieving previous month data.Add workflow for retrieving data form an arbitrary month.Build CLI.Containerize app.Documentation.Add CI/CD.Add logging.Add tests.Add runtime support for multiple CPEs.ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.LicenseSeeLICENSEfile.
Package: eren
erenThis library contains Hive helper methods for PySpark users.This README is a good way to learn about the Hive metastore for PySpark, even if you're not going to use this library directly.Hive metastore backgroundThe Hive metastore contains information on tables, where the data is located, and the schema of the data.Registering tables in the Hive metastore is a great way to make nice Spark workflows for an organization.  You can setup your Spark cluster to automatically regsiter all your organization's tables, so users can spin up clusters and immediately start querying the data with SQL syntax.Suppose you have a table calledimportant_customersand a database analyst that would like to query this table to generate a report for the accounting department on a weekly basis.  If theimportant_customerstable is registered in the Hive metastore, then the analyst can spin up a Spark cluster and run their queries, without having to worry about where the underlying data is stored or the schema.How this library helpsThis library contains helper methods to make it easier to manage your Hive metastore.  You can use this libray to easily determine if a Hive table is managed, unmanaged, or non-registered for example.You can also use this library to register Hive tables that are not currently in the metastore.This library makes common Hive tasks for PySpark programmers easy.Hive managed vs unmanaged vs non-registered tablesHive managed tables are registered in the Hive metastore and have paths that are managed by Hive.  Here's an example of how to create a managed table.This table stores data in XX.Hive Parquet vs Delta Lake tablesWorking with Hadoop File System from PythonErenalso provides a top level interface for working with any implementation of HadoopFileSystem (ibcluding S3, HDFS/DBFS and Local File System).fromerenimportfs# spark: SparkSessionhdfs=fs.HadoopFileSystem(spark,"hdfs:///data")# returns an instance for access to HDFSs3fs=fs.HadoopFileSystem(spark,"s3a:///bucket/prefix")# returns an instance for access to S3local_fs=fs.HadoopFileSystem(spark,"file:///home/my-home")# return an instance for access to LocalFSGlob FilesYou can list files and directories on remote file system:list_of_files=hdfs.glob("hdfs:///raw/table/**/*.csv")# list all CSV files recursively inside a folder on HDFSRead/Write UTF-8 stringsYou can read and write UTF-8 strings from/to remote file system. But be carefully! This method is extremely slow compared to regularspark.read. Do not use this for reading/writing data!importjsonhdfs.write_utf8("hdfs:///data/results/results.json",json.dumps({"key1":1,"key2":3}),mode="w")json.loads(hdfs.read_utf8("hdfs:///data/results/results.json"))CommunityBlogsSemyon Sinchenko: Working With File System from PySpark
Package: erepapi
=============================erepapi=============================.. image:: https://badge.fury.io/py/erepapi.png:target: http://badge.fury.io/py/erepapi.. image:: https://pypip.in/d/erepapi/badge.png:target: https://crate.io/packages/erepapi?version=latestUnofficial python wrapper for erepublik apiFeatures--------* Simple access to api.erepublik.com* Class based objects for Citizens, Regions, Countries, Battles, Country Regions* Python 2 and 3 supported.* pip installer* No 3rd party dependencies* Examples provided for all classesLicense (MIT)--------Copyright (c) 2013 Nikola KovacevicPermission is hereby granted, free of charge, to any person obtaining a copy ofthis software and associated documentation files (the "Software"), to deal inthe Software without restriction, including without limitation the rights touse, copy, modify, merge, publish, distribute, sublicense, and/or sell copies ofthe Software, and to permit persons to whom the Software is furnished to do so,subject to the following conditions:The above copyright notice and this permission notice shall be included in allcopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS ORIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESSFOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS ORCOPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHERIN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR INCONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.Documentation-------------The full documentation is at http://erepapi.rtfd.org.History-------0.1.0 (2013-09-25)++++++++++++++++++* First release on PyPI.
Package: erequests
ERequests allows you to use Requests with Eventlet to make asyncronous HTTP
Requests easily.ERequests is a port to Eventlet of Kenneth Reitz’s grequests (https://github.com/kennethreitz/grequests) though
it doesn’t provide the same API these days.UsageUsage is simple:import erequests

urls = [
    'http://www.heroku.com',
    'http://tablib.org',
    'http://httpbin.org',
    'http://python-requests.org',
    'http://kennethreitz.com'
]Create a set of unsent Requests:>>> rs = (erequests.async.get(u) for u in urls)Send them all at the same time:>>> list(erequests.map(rs))
[<Response [200]>, <Response [200]>, <Response [200]>, <Response [200]>, <Response [200]>]NOTE: When sending multiple requests at the same time with map/imap, if any of them results in an error, the exception
object is returned.InstallationInstallation is easy with pip:$ pip install erequests
Package: eresponse
EResponseThis is a simple package to form json response easily.Usagefromeresponseimportnew_success_message,new_error_messagedefexample():try:res={"key":1}returnnew_success_message("Success text",test=res)exceptExceptionase:returnnew_error_message("Error text")What it looks like in responseSuccess{"ok":true,"message":"Success text","test":{"key":1}}Error{"ok":false,"error":"Error text"}
Package: eresponses
EResponseThis is a simple package to form json response easily.Usagefromeresponseimportnew_success_message,new_error_messagedefexample():try:res={"key":1}returnnew_success_message("Success text",test=res)exceptExceptionase:returnnew_error_message("Error text")What it looks like in responseSuccess{"ok":true,"message":"Success text","test":{"key":1}}Error{"ok":false,"error":"Error text"}