Saravanan666/pypi-org huggingface dataset:
Package: arachniclient
arachniclientArachni REST client to control arachni vulnerability scanners.UsageCommand Line Interface (CLI) options may be listed:arachni-client--helpExamplesAdding a scan:arachni-client--url"https://[target server]/"Listing currently running scans:arachni-client--fetchFetching a report from a running or completed scan in a zipped HTML format:arachni-client--report[scanid]--formathtml.zip
Package: arachnio
arachnio4jArachnioclient library for Python 3.10+Getting StartedStep 1. Subscribe 👍First, you'll need to subscribe toan Arachnio product. TheFree Forever Planis just fine for this introduction. Before we head to the next step, you'll need your Base Product URL and one of your Bloblr API Keys.Above is a screenshot of the Subscription Authentication screen, which contains these facts. The Base Product URL is circled in red, and the Blobr API keys in green. Both are redacted for privacy. 🤫Step 2. Pick a Webpage 🔗In this introduction, we will extract structured data from a webpage, so the next step is to pick a webpage to extract. In the spirit of web crawling, we have pickedan article about spidersfor this example. 🕷Step 3. Call Link Extract Endpoint 📢Now that we have our base URL, API key, and parameters, we can call the link extract endpoint!from arachnio import ArachnioClient

# ARACHNIO_BASE_URL and BLOBR_API_KEY are from Step 1
client = ArachnioClient(ARACHNIO_BASE_URL, BLOBR_API_KEY)

# The link is from Step 2
response = client.extractLink(
    "https://www.nytimes.com/2022/08/25/science/spiders-misinformation-rumors.html")
    
entity = response["entity"]

if entity["entityType"]=="webpage" and entity["webpageType"]=="article":
    print(entity["title"]);
    # Spiders Are Caught in a Global Web of Misinformation
Package: arachno
Utility to orchestrate coroutines via DSL.Example{"actions":{"target":{"operation":"search-api.get_product","args":{"product_id":"${product_id}"},"defines":{"product-category":"result.category","product-price":"result.price"},"options":{"timeout":"1s"}},"target-account":{"operation":"accounts-repository.get","args":{"account_id":"${account_id}"},"defines":{"favorite-categories":"${account.favorite-categories}"},"options":{"timeout":"1s"}},"product-selector":{"operation":"product-stats.calculate_params","args":{"input":{"category":"${target.product-category}","country":"${target.product-price}","segment":"Germany"},"jitter_percent":10},"defines":{"output-args":"value"}},"similar-products":{"operation":"search-api.search","args":{"product_codes":"${product-selector.output-args}","categories":{"oneof":"${target-account.favorite-categories}"}},"options":{"timeout":"600ms"}}}}
Package: arackpy
arackpyis a web spider used to crawl and scrape web pages. It can be
helpful in the event you quickly need some data from a site without the hassle
of having to sign up and go through hoops for getting access to the information
you need.Requirementsarackpycurrently supports Python 2.7 and 3.6+ out of the box. Depending on
the data you want to extract, future releases will require one or more of the
dependencies below to be installed to support the various backends:BeautifulSoupSeleniumrequestsstemfake_useragentInstallationFor the vanillaarackpyinstall do a simple pip install:pip install arackpyThe following packages may also be installed:pip install bs4, selenium, requests, stem, fake_useragentQuickstartOpen up your favorite python text editor and type the following:# hello_spider.pyfrom __future__ import division     # for python 2.7from arackpy.spider import Spiderclass HelloSpider(Spider):“””A simple spider in just five lines of working code”””start_urls = [”https://www.python.org”]def parse(self, url, html):“””Extract data from the raw html”””
print(“Crawling url, %s” % url)if __name__ == “__main__”:print(“Press Ctrl-c to stop crawling”)
spider = HelloSpider()
spider.crawl()Run the program using:python hello_spider.pyNotePress Ctrl-c to terminate crawling.
Package: aracnid-api
Aracnid APIThis package contains custom wrappers around a variety of Web App APIs.Getting StartedThese instructions will get you a copy of the project up and running on your local machine for development and testing purposes.PrerequisitesThis package supports the following version of Python:Python 3.10 or laterInstallingInstall the latest package using pip. (We prefer poetry.)$ poetry install aracnid-apiEnd with an example of getting some data out of the system or using it for a little demoRunning the testsExplain how to run the automated tests for this system$ python -m pytestUsageTODOAuthorsJason Romano-AracnidSee also the list ofcontributorswho participated in this project.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: aracnid-config
Aracnid ConfigThis is a custom configuration class that uses MongoDB as the backeng database.Getting StartedThese instructions will get you a copy of the project up and running on your local machine for development and testing purposes.PrerequisitesThis package supports the following version of Python. It probably supports older versions, but they have not been tested.Python 3.10 or laterInstallingInstall the latest package using pip.$pipinstallaracnid-configEnd with an example of getting some data out of the system or using it for a little demoRunning the testsExplain how to run the automated tests for this system$python-mpytestUsageTODOAuthorsJason Romano-AracnidSee also the list ofcontributorswho participated in this project.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: aracnid-logger
Aracnid LoggerThis is a simple customization of the Python Logging System.Getting StartedThese instructions will get you a copy of the project up and running on your local machine for development and testing purposes.PrerequisitesThis package supports the following version of Python. It probably supports older versions, but they have not been tested.Python 3.10 or laterInstallingInstall the latest package using pip.$ pip install aracnid-loggerEnd with an example of getting some data out of the system or using it for a little demoRunning the testsExplain how to run the automated tests for this system$ python -m pytestUsageTODOAuthorsJason Romano-AracnidSee also the list ofcontributorswho participated in this project.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: aracnid-utils
Aracnid UtilitiesThis package contains utilities that I use frequently.Getting StartedThese instructions will get you a copy of the project up and running on your local machine for development and testing purposes.PrerequisitesThis package supports the following version of Python. It probably supports older versions, but they have not been tested.Python 3.10 or laterInstallingInstall the latest package using pip.$pipinstallaracnid-utilsEnd with an example of getting some data out of the system or using it for a little demoRunning the testsExplain how to run the automated tests for this system$python-mpytestUsageTODOAuthorsJason Romano-AracnidSee also the list ofcontributorswho participated in this project.LicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: aradf
PDF TO TEXT CONVERTERconvertPDFto TXT.InstructionsInstall:pip install aradfInstall Tesseract, include arabic training data in the installation from:https://github.com/UB-Mannheim/tesseract/wikiconvert PDF to TXT:fromaradfimportconvertor# get the text, it also saves txt file to the same directory of the pdftxt=convertor.pdf_to_txt('path/to/pdf_file')
Package: arakneed
ArakneedA common use targeted concurrent crawler foranydirected graph. It's designed to be easy to use.It's an adequate practice to organize your crawler code instead of a spider library or framework.Why this since there's scrapy .etc?Because they are not supposed to crawl my pictures on my laptop but I want to crawl them like a spider.Arakneed can be used to traverse any directed graph, including a directory on your computer to collect pictures or collecting someone's all Github Gists... And anything looks like directed graph.Though it can also be used to crawl a website like a tranditional spider.UsageInstall as dependency:pipinstall-UarakneedOr you can clone the repo and work right in place within filecrawler.py:gitclonehttps://github.com/arakneed/crawler.gitHow does it work?Any vertex spotted by the spider will be scheduled as atask. The only thing you need to do is to define how to handle the tasks.importasynciofrompathlibimportPathimportreimportaiohttpfromarakneedimportCrawler,Taskasyncdefresolver(task:Task,response:aiohttp.ClientResponse):iftask.type=='page':r=awaitresponse.text()return[Task('image',group[1])forgroupinre.compile(r'<img.+?src=\"(.+?)\".*?>').finditer(r)ifgroup[1].endswith('.jpg')orgroup[1].endswith('.png')orgroup[1].endswith('.svg')]iftask.type=='image':image_path=Path('~/Downloads/gh-images',task.key.split('/')[-1]).expanduser()ifnotimage_path.parent.is_dir():image_path.parent.mkdir()image_path.touch()image_path.write_bytes(awaitresponse.content.read())asyncio.run(Crawler().run(Task('page','https://github.com'),resolver))This code downloads all images it founds on Github. I believe it explains what does the business code look like.ExamplesCrawl a websiteCollect pictures in a local driverAbstract Syntax Tree analyzerMISCBe careful with circles in the directed graph if you are customizing the scheduler/spider. The framework always checks whether all corresponding vertices are resolved recursively of every vertex to know when could it have a relax :)This paradigm is not distributed. Though you can take a glance of it through Redis based vertices resolving check, but the task is locked as soon as it's resolved, you cannot resolve a task on several machines simultaneously.DevelopmentA branch calleddevis recommended for common development.Useful commands:install poetrycurl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | pythonsource $HOME/.poetry/envinstall dependenciespoetry installrun testspoetry run pytestlintpoetry run flake8 --max-line-length=120 --statistics
Package: aranet4-graph
Graph data file(s) from an aranet4 sensorThearanet4-graph(python) program takes a YAML input file for
configuration that allows loading and graphing of a CSV file that has
been exported from the aranet4 phone app.  The YAML configuration
supports specifying thefileto load,beginandendtimestamps
to limit the graph to and a set ofmarkersfor having arrows that
point at the graph.  Each marker can be a simple string, or may be a
dictionary and alabeland ay_offsetthat sets the vertical
offset (default 400) of the label and arrow length and ax_offset(in seconds) for the horizontal offset (default 0).Example:input:2022-11-05-smf-to-lhr.csvoutput:2022-11-05-smf-to-lhr.pngbegin:"2022-11-0408:23PDT"markers:"2022-11-0409:00PDT":"athome""2022-11-0411:30PDT":"SMFgate""2022-11-0412:20PDT":label:"boarding"y_offset:600"2022-11-0413:05PDT":label:"takingoff"y_offset:-200h_offset:-1800"2022-11-0413:55PDT":"inflight""2022-11-0416:14MDT":"landing""2022-11-0416:45MDT":"DENUnitedclub""2022-11-0417:45MDT":"atnextgate"end:"2022-11-0418:45MDT"Installationpipx install aranet4-graphor
pip install aranet4-graphExample outputFor a more complete read about analyzing a week-long trip using an
aranet4 and this software, refer to my
[https://www.isi.edu/~hardaker/news/20221106-ietf-c02-analysis/][personal
news article about measuring CO2 levels during IETF-115].Source codehttps://github.com/hardaker/aranet4-graph
Package: arango
Driver forArangoDB REST APIinrerface,arangodb.orgInstallationpip install arangoUsageTo start work withArangoDBtry following example:from arango import create

# create connection to database
conn = create(db="test")
conn.database.create()

# create collection with name `test_collection`
conn.test_collection.create()

# create document
conn.test_collection.documents.create({"sample_key": "sample_value"})

# get first document
doc = conn.test_collection.documents().first
# get document body
doc.body

# get all documents in collection

for doc in conn.test_collection.query.execute():
  print doc.idFor more details please readDocumentationSupported Python interpreters and versions:cPython 3.3cPython 2.7PyPy 1.9SupportedArangoDB versions:1.4xDeveloped byMaksym KlymyshynChangelog0.2.0Added support for multiple databases0.1.8Added support ofbulk inserts
Package: arango3-doc-manager
Getting StartedThis package is a document manager formongo-connectorthat targetsArangoDBversions 3.x and keeps ArangoDB in
sync withMongoDB.InstallationArangoDB 3.xFor use with an ArangoDB 3.x server, install with pip:pip install arango3-doc-managerDevelopmentYou can also install the development version of arangodb3-doc-manager manually:git clone https://github.com/Innoplexus-Consulting-Services/arango3-doc-manager.git

python setup.py installYou may have to run pip with sudo, depending on where you’re installing and
what privileges you have.Running the testsClone the arago3-doc-manager Github repositorygit clone https://github.com/Innoplexus-Consulting-Services/arango3-doc-manager.gitGo to arango3-doc-manager/tests/cd arango3-doc-manager/tests/Run testspython test_arango3-doc-manager.pySetting up ArangoDB AuthenticationArangoDB runs with authentication by default.Use connector_arango_auth command for below mentioned Authentication
related operations:Set Authconnector_arango_auth set

source ~/.bashrcReset Authconnector_arango_auth reset

source ~/.bashrcDisable Authconnector_arango_auth flush

source ~/.bashrcVerify Auth credentials by issuing the following command on termianl:Verify username:~$echo $USER_ARANGOVerify password:~$echo $PASSWD_ARANGOTest via command linemongo-connector -m localhost:27017 -t localhost:8529 -d arango3_doc_managerAuthorsPrashant Patil,Innoplexus.Suyash Masugade,Innoplexus.
Package: arango-datasets
arango_datasetsPackage for loading example datasets into an ArangoDB Instance.fromarangoimportArangoClientfromarango_datasetsimportDatasets# Datasets requires a valid database objectdb=ArangoClient(hosts='http://localhost:8529').db("dbName",username="root",password="")datasets=Datasets(db)# List available datasetsdatasets.list_datasets()# List more information about a particular datasetdatasets.dataset_info("IMDB_X")# Import the datasetdatasets.load("IMDB_X")
Package: arangodb
There are a couple of Python implementations for ArangoDB’s rest API, but they
do not fit my mind:Have a declarative way of defining documents, Edges and Graphs.Have a clean separation of client API and ArangoDB API.Documents should be optionally de/serializable when loading or saving.The API client may differ for a special Document.Documents should behave like dicts.Have a nice query tool.Have ArangoDB errors thrown as exceptions.Use requests Session with keep-alive.
Package: arangodb-pythongraph
arangodb-pythongraphRun an AQL and get a Python network object in returnInstallationpip install arangodb-pythongraphDuh.Graph frameworksThis package is based onpyintergraphand thus supports extraction to NetworkX, python-IGraph and Graph-Tools graph objects.
However, these libraries are not defined as requirements for this package and if you want to extract to each of them you are required to install the necessary package accordingly.UsageAll queriesmustreturn path objects.Simple extractionfrom arangodb_pythongraph import execute_to_pygraph

db = ... # ArangoDB connection (use python-arango package)
example_query = '''
  FOR v0 in vertex_collection
    FOR e, v, p IN OUTBOUND v0 edge_collection
      RETURN p
'''
python_graph = execute_to_pygraph(db, query)
nx_graph = python_graph.to_networkx()
gt_graph = python_graph.to_graph_tool()
ig_graph = python_graph.to_igraph()Exporting the graphIf you want to export the graph (for example to use it withGephi),
you might run into trouble if you have nested or complex attributes in your graph.
To overcome this, use thecleanupargument:python_graph = execute_to_pygraph(db, query, cleanup=True)The functionality might be missing some use cases so if you encounter problems while exporting the graph to file,
please open an Issue describing the error you're getting together with a portion of the data you're trying to export.Attaching functionality to the AQL objectFor a neater use, runarangodb_pythongraph.register()Before:python_graph = execute_to_pythongraph(db, query)After:python_graph = db.aql.execute_to_pythongraph(query)DevelopmentContributions are more than welcome :)Note that the project is managed withpoetry,
so make sure you use poetry to update the pypoject file.Running testsTo run the tests you must have a running instance of ArangoDB.
If you don't have a connection to an existing DB you canuse dockerto run it easily.Once you have a running ArangoDB connection, create a DB named 'test' (or any other name you choose),
and run tests with pytestARANGODB_PASS=<pass_goes_here> ARANGODB_NAME=test poetry run pytest
Package: arangodol
arangodolArangoDB with a simple (dict-like or list-like) interfaceTo install:pip install arangodolA basic ArangoDB persister.>>>fromarangodolimportArangoDbPersister>>>s=ArangoDbPersister()>>>k={'key':'777'}# Each collection will happily accept user-defined _key values.>>>v={'val':'bar'}>>>for_keyins:...dels[_key]...>>>kinsFalse>>>len(s)0>>>s[k]=v>>>len(s)1>>>s[k]{'val':'bar'}>>>s.get(k){'val':'bar'}>>>s.get({'not':'a key'},{'default':'val'})# testing s.get with default{'default':'val'}>>>list(s.values())[{'val':'bar'}]>>>kins# testing __contains__ againTrue>>>dels[k]>>>len(s)0>>>s=ArangoDbPersister(db_name='py2store',key_fields=('name',))>>>for_keyins:...dels[_key]...>>>s[{'name':'guido'}]={'yob':1956,'proj':'python','bdfl':False}>>>s[{'name':'guido'}]{'yob':1956,'proj':'python','bdfl':False}>>>s[{'name':'vitalik'}]={'yob':1994,'proj':'ethereum','bdfl':True}>>>s[{'name':'vitalik'}]{'yob':1994,'proj':'ethereum','bdfl':True}>>>forkey,valins.items():...print(f"{key}:{val}"){'name':'guido'}:{'yob':1956,'proj':'python','bdfl':False}{'name':'vitalik'}:{'yob':1994,'proj':'ethereum','bdfl':True}ArangoDbStore using tuple keys.>>>fromarangodolimportArangoDbTupleKeyStore>>>s=ArangoDbTupleKeyStore(collection_name='test',key_fields=('key','user'))>>>k=(1234,'user')>>>v={'name':'bob','age':42}>>>ifkins:# deleting all docs in tmp...dels[k]>>>assert(kins)==False# see that key is not in store (and testing __contains__)>>>orig_length=len(s)>>>s[k]=v>>>assertlen(s)==orig_length+1>>>assertkinlist(s)>>>asserts[k]==v>>>asserts.get(k)==v>>>assertvinlist(s.values())>>>assert(kins)==True# testing __contains__ again>>>dels[k]>>>assertlen(s)==orig_length
Package: arango-query-engine
python_arango_enginethis is a quering and creation engine for integration with arangodb databasesthis use pyArango backend
the target of writing this was using in django projectits syntax will be like the django quering API syntax like this :models.question.objects.get(name="hooman")installitionbecause of being small it is not installable but after a while i will add path to install itTODO[] complete the quering system for normal NoSQL[] complete the quering system for graph store DB[] add Inserting system for both normal and graph store systems[] add to django project
Package: aranha
Aranha (pronounced aranya) is a simple web spider written in python using
gevent for asynchronicity.  Aranha means “spider” in portuguese.Aranha’s goal is to be suitable for projects that need light url fetching
or a simple spidering of a few classes of webpages.  If spidering is a major
part of your project, you probably want to either write your own spider or
use scrapy as a base, as it’s much more sophisticated.
Package: aranizer
AraNizerDescriptionAraNizer contains custom tokenizers specifically designed for Arabic language processing. Built with SentencePiece and Byte Pair Encoding (BPE) methodologies, these tokenizers are engineered to be compatible with thetransformersandsentence_transformerslibraries. Each tokenizer in the AraNizer collection is optimized for different NLP tasks, accommodating a diverse range of vocabulary sizes to suit various linguistic scenarios.InstallationInstall AraNizer effortlessly with pip:pipinstallaranizer

UsageStartbyimportingthedesiredtokenizerfromAraNizer:# Other aranizers: aranizer_bpe50k, aranizer_bpe64k, aranizer_bpe86k, aranizer_sp32k, aranizer_sp50k, aranizer_sp64k, aranizer_sp86kfromaranizerimportaranizer_sp50k

Loadyourtokenizer:tokenizer=aranizer_sp50k.get_tokenizer()# Replace aranizer_bpe32k with your chosen tokenizerExampleoftokenizingatext:text="مثال على النص العربي"# Example Arabic texttokens=tokenizer.tokenize(text)print(tokens)Encoding Text:
To encode text, use the encode method. This converts a text string into a sequence of token ids:text="مثال على النص العربي"# Example Arabic textencoded_output=tokenizer.encode(text,add_special_tokens=True)print(encoded_output)Decoding Text:
To convert token ids back to text, use the decode method:decoded_text=tokenizer.decode(encoded_output)print(decoded_text)AraNizers-aranizer_bpe32k:BasedonBEPTokenizerwithVocabSizeof32k
-aranizer_bpe50k:BasedonBEPTokenizerwithVocabSizeof50k
-aranizer_bpe64k:BasedonBEPTokenizerwithVocabSizeof64k
-aranizer_bpe86k:BasedonBEPTokenizerwithVocabSizeof86k
-aranizer_sp32k:BasedonSentencePeiceTokenizerwithVocabSizeof32k
-aranizer_sp50k:BasedonSentencePeiceTokenizerwithVocabSizeof50k
-aranizer_sp64k:BasedonSentencePeiceTokenizerwithVocabSizeof64k
-aranizer_sp86k:BasedonSentencePeiceTokenizerwithVocabSizeof86kRequirements:transformersContact:For queries or assistance, please contactonajar@psu.edu.sa.Acknowledgments:Special thanks to Prince Sultan University and Riotu Lab, under the guidance of Dr. Lahouari Ghouti and Dr. Anis Koubaa, for their invaluable support.Version:0.1.8Citations:If AraNizer benefits your research, please cite us:@misc{AraNizer_2023,title={Aranizer:ACustomTokenizerforEnhancedArabicLanguageProcessing},author={Najar,OmarandSibaee,SerryandGhouti,LahouariandKoubaa,Anis},affiliation={PrinceSultanUniversity,Riyadh,SaudiArabia},year={2023},howpublished={\url{https://github.com/omarnj-lab/aranizer}}
Package: arasel_test
==================Arasel Python Test==================.. image:: https://img.shields.io/pypi/v/arasel_test.svg:target: https://pypi.python.org/pypi/arasel_testTest Solution to TransfCustomer Lifetime Value for each customer in input CSV.* Free software: MIT license* Documentation: https://arasel-test.readthedocs.io.Instalation--------```pip install arasel_test```Usage--------```arasel_test --orders=/path/to/orders.csv --model=/path/to/model.dill --output=/path/to/output.csv --port=8080```OR--------Clone this repository, install requirements.txt, add arasel_test directory to PYTHONPATH, and then:```python app.py```=======History=======0.1.0 (2018-02-24)------------------* First release on PyPI.
Package: arasents
Arasents : طھط­ظ„ظٹظ„ ط§ظ„ظ…ط´ط§ط¹ط± ظپظٹ ط§ظ„ظ†طµظˆطµ ط§ظ„ط¹ط±ط¨ظٹط©Arasents ظ…ظƒطھط¨ط© ط¨ط³ظٹط·ط© ظ„ط§ط³طھظ†طھط§ط¬ ط§ظ„ظ…ط´ط§ط¹ط± ظ…ظ† ط§ظ„ظ†طµ ط§ظ„ط¹ط±ط¨ظٹ طŒ ظ„ط§ طھط³طھط®ط¯ظ… nltk ظˆظ„ط§ ط£ظٹط© ط®ظˆط§ط±ط²ظ…ظٹط© ظ„طھط­ظ„ظٹظ„ ط§ظ„ظ†طµظˆطµ .ط£ظ†ظ…ط§ط· ط§ظ„ظ…ط´ط§ط¹ط± ط§ظ„طھظٹ ظٹطھظ… ط§ط³طھط®ط±ط§ط¬ظ‡ط§ :Negative : ظ…ط´ط§ط¹ط± ط³ظ„ط¨ظٹط© .positive : ظ…ط´ط§ط¹ط± ط§ظٹط¬ط§ط¨ظٹط©.neutral : ظ…ط´ط§ط¹ط± ظ…ط­ط§ظٹط¯ط© .ط·ط±ظٹظ‚ط© ط§ظ„ط§ط³طھط®ط¯ط§ظ… :importarasentsmy_text=arasents.text("ط£ظ†طھ ظ‚ط§ط±ط¦ ط¬ظٹط¯")print(my_text.sentiments()){ 'positive': 100.0 , 'text': 'ط£ظ†طھ ظ‚ط§ط±ط¦ ط¬ظٹط¯' }importarasentsmy_text=arasents.text('ظ‡ظˆ ظƒط³ظˆظ„ ط¬ط¯ط§')print(my_text.sentiments()){ 'negative': 100.0, 'text': 'ظ‡ظˆ ظƒط³ظˆظ„ ط¬ط¯ط§' }importarasentsmy_text=arasents.text('ط°ظƒط±ظٹط§طھ ..')print(my_text.sentiments()){'neutral': 100.0, 'text': 'ط°ظƒط±ظٹط§طھ ..'}importarasentsmy_text=arasents.text('ظ‡ظٹ ط¬ظ…ظٹظ„ط© ظˆظ„ظƒظ†ظ‡ط§ ط³ظٹط¦ط©')print(my_text.sentiments()){'positive': 50.0, 'negative': 50.0, 'text': 'ظ‡ظٹ ط¬ظ…ظٹظ„ط© ظˆظ„ظƒظ†ظ‡ط§ ط³ظٹط¦ط©'}ظ…ظ„ط§ط­ط¸ط§طھ ظ…ظ‡ظ…ط© :ط§ظ„ظ…ظƒطھط¨ط© طھط¬ط±ظٹط¨ظٹط© ظˆطھظ… ط§ظ†ط´ط§ط¦ظ‡ط§ ظپظٹ ظ…ط±ط­ظ„ط© ط§ظ„طھط¹ظ„ظ… طŒ ظپظٹ ط§ظ†طھط¸ط§ط± ط§ظ„طھط·ظˆظٹط±  .