Saravanan666/pypi-org huggingface dataset:
Package: queryfilter
FeatureAllow same query interface to be shared between Django ORM, SQLAlchemy, and GraphQL backend.Documenthttps://github.com/iCHEF/queryfilter/wikiInstallationpip install queryfilterDevelopmentgit clone https://github.com/iCHEF/queryfilter.git
cd queryfilter
pip install -e .[dev]TestsThis project usespytestto run tests.
Package: query-flow
QueryFlowQueryFlow, is a query visualization tool that provides insights into common problems in your SQL query.
QueryFlow visualizes the query execution using the Sankey diagram, a technique that allows one to illustrate complex processes, with a focus on a single aspect or resource that you want to highlight.
This allow to tackle the following problems:Identifying missing records.Identifying Ineffective operations.Identifying duplications in a query.Comparing optimizer planned metrics to actual metrics.Identifying performance bottlenecks in a single query.Identifying performance bottlenecks in multiple queries.Currently QueryFlow support the following databases/data-engines:AthenaPostgreSQLDocumentation:https://eyaltrabelsi.github.io/query-flowGitHub:https://github.com/eyaltrabelsi/query-flowPyPI:https://pypi.org/project/query-flow/Free software: MITInstallingThe best way to install query-flow is:$ pip install query-flowIn case you want to use another way go to theinstallation page.
Package: querykit
querykitA Wagtail app for handling queries. Please bear with us while we prepare more detailed documentation.Compatibilityquerykit' major.minor version number indicates the Wagtail release it is compatible with. Currently this is Wagtail 4.1.xInstallationInstall usingpip:pipinstallquerykitAddquerykitto yourINSTALLED_APPSsetting:INSTALLED_APPS=[# ...'querykit'# ...]
Package: query-log-tracer
query-log-tracerA Python tool/library that traces a value in MySQL general logs.UsageSet up$ pip install query-log-tracerExample usage./tests/files/general-query.logis a sample query log file of MySQL 5.7. Most of the queries are generated by EC-CUBE 4.$ query-log-tracer --log-file=./tests/files/general-query.log --target-table=dtb_customer --target-column=point --filter-column=id --filter-value=1
=== Searching in ./tests/files/general-query.log ===

2020-02-02T07:19:51.127168Z dtb_customer.point (id = 1) is set: '0'
2020-02-02T07:20:19.927027Z dtb_customer.point (id = 1) is set: '0'
2020-02-02T07:20:26.901577Z dtb_customer.point (id = 1) is set: '100'
2020-02-02T07:20:31.034901Z dtb_customer.point (id = 1) is set: '1000'
2020-02-02T07:20:39.396236Z dtb_customer.point (id = 1) is set: '2000'
2020-02-02T07:20:46.379143Z dtb_customer.point (id = 1) is set: '0'
2020-02-02T07:26:37.443522Z dtb_customer.point (id = 1) is set: '0'
2020-02-02T07:26:55.216881Z dtb_customer.point (id = 1) is set: '0'
2020-02-02T07:27:13.008757Z dtb_customer.point (id = 1) is set: '50'
2020-02-02T07:28:01.128957Z dtb_customer.point (id = 1) is set: '0'
2020-02-02T07:28:09.995354Z dtb_customer.point (id = 1) is set: '0'
2020-02-02T07:28:14.172518Z dtb_customer.point (id = 1) is set: '27'
2020-02-02T07:33:41.745400Z dtb_customer.point (id = 1) changes: +500For EC-CUBE 2, try the following command.$ query-log-tracer --log-dir=your-directory --target-table=dtb_customer --target-column=point --filter-column=customer_id --filter-value=1
Package: query-parser
qs-parserInstallFor use this lib with poetry :poetryaddquery-parserFor use this lib with pip :pipinstallquery-parserUsagefromquery_parser.parserimportparse_query_stringprint(parse_query_string("a=1&b=2&c=3&b[]=4&b[]=5&b[other]=6"))# {'a': '1', 'b': {'0': '2', '1': '4', '2': '5', 'other': '6'}, 'c': '3'}
Package: queryparser-python2
Tool for parsing and processing MySQL and ADQL SELECT queriesDesigned to be used in conjunction withdjango-daiqurias a query processing backend but it can be easily used as a stand-alone tool
or integrated into another project.InstallationThe easiest way to install the package is by using the pip tool:pipinstallqueryparser-python3or if you are using an older version (2.7) of pythonpipinstallqueryparser-python2Alternatively, you can clone the repository and install it from there.
However, this step also requires generating the parser which is a slighly
more elaborate process (see below).Generating the parser from the git repositoryTo generate the parsers you needpython(either 2 or 3),javaabove version
7, andantlr4(antlr-4.*-complete.jarhas to be installed inside the/usr/local/lib/or/usr/local/bin/directories).After cloning the project runmakeand alibdirectory will be created with the complete source for python2
and python3. After that runpythonsetup.pyinstallto install the generated parser in your virtual environment.Parsing MySQLParsing and processing of MySQL queries can be done by creating an instance
of theMySQLQueryProcessorclassfromqueryparser.mysqlimportMySQLQueryProcessorqp=MySQLQueryProcessor()feeding it a MySQL querysql="SELECT a FROM db.tab;"qp.set_query(sql)and running it withqp.process_query()After the processing, the processor objectqpwill include tables, columns,
functions, and keywords used in the query or will raise aQuerySyntaxErrorif there are any syntax errors in the query.Alternatively, passing the query at initialization automatically processes it.Translating ADQLTranslation of ADQL queries is done similarly by first creating an instance of
theADQLQueryTranslatorclassfromqueryparser.adqlimportADQLQueryTranslatoradql="SELECT TOP 100 POINT('ICRS', ra, de) FROM db.tab;"adt=ADQLQueryTranslator(adql)and callingadt.to_mysql()which returns a translated string representing a valid MySQL query if
the ADQL query had no errors. The MySQL query can then be parsed with theMySQLQueryProcessorin the same way as shown above.TestingFirst, installpytestpipinstallpytestthen run the test suite for a version of python you would like to test withpytestlib/python2pytestlib/python3
Package: queryparser-python3
queryparserTool for parsing and processing of MySQL/PostgreSQL and translation of
ADQL SELECT-like queriesDesigned to be used in conjunction withdjango-daiqurias a query processing backend but it can be easily used as a stand-alone tool
or integrated into another project.InstallationThe easiest way to install the package is by using the pip tool:pipinstallqueryparser-python3Alternatively, you can clone the repository and install it from there.
However, this step also requires generating the parser which is a slightly
more elaborate process (see below).Generating the parser from the git repositoryTo generate the parsers you needpython3,javaabove version
7, andantlr4(antlr-4.*-complete.jarhas to be installed inside the/usr/local/lib/or/usr/local/bin/directories).After cloning the project runmakeand alibdirectory will be created. After that, runpythonsetup.pyinstallto install the generated parser in your virtual environment.Parsing MySQL and PostgreSQLParsing and processing of MySQL queries can be done by creating an instance
of theMySQLQueryProcessorclassfromqueryparser.mysqlimportMySQLQueryProcessorqp=MySQLQueryProcessor()feeding it a MySQL querysql="SELECT a FROM db.tab;"qp.set_query(sql)and running it withqp.process_query()After the processing is completed, the processor objectqpwill include
tables, columns, functions, and keywords used in the query or will raise aQuerySyntaxErrorif there are any syntax errors in the query.Alternatively, passing the query at initialization automatically processes it.PostgreSQL parsing is very similar to MySQL, except it requires importing
thePostgreSQLProcessorclass:fromqueryparser.postgresqlimportPostgreSQLQueryProcessorqp=PostgreSQLQueryProcessor()The rest of the functionality remains the same.Translating ADQLTranslation of ADQL queries is done similarly by first creating an instance of
theADQLQueryTranslatorclassfromqueryparser.adqlimportADQLQueryTranslatoradql="SELECT TOP 100 POINT('ICRS', ra, de) FROM db.tab;"adt=ADQLQueryTranslator(adql)and callingadt.to_mysql()which returns a translated string representing a valid MySQL query if
the ADQL query had no errors. The MySQL query can then be parsed with theMySQLQueryProcessorin the same way as shown above.TestingFirst, installpytestpipinstallpytestthen run the test suite for a version of python you would like to test withpytestlib/More elaborate testing procedures can be found in the development notes.
Package: query-phenomizer
query_phenomizerA small module for querying thephenomizer toolwith HPO-terms.INFO!!!From 16/2-16 phenomizer demands a password and username when using the service in this way.
Request login credentials fromsebastian.koehler@charite.deInstallationpip install query_phenomizerorgit clone https://github.com/moonso/query_phenomizer.git
cd query_phenomizer
pip install --editable .##Usage##query_phenomizer HP:0001623 HP:0002465 --output phenitypes.txtUser can check if hpo terms exist by using the flag-c/--check_terms.query_phenomizer HP:0001623 HP:02345555 --check_terms -vPrints that HP:02345555 does not exist.For more info runquery_phenomizer --help
Package: querypool
querypoolExecution pool with caching and early return for python.Query pools let a query run in the background when it doesn't return
within a given timeout. In that case the result of the previous query
is returned or raised. If there is no result, the default value is returned.import requests
from querypool.pools import CooperativeQueryPool

pool = CooperativeQueryPool(timeout=0.001)
url = "https://jsonplaceholder.typicode.com/photos"

# Returns None because the query times out.
response = pool.execute(requests.get, args=(url,), default=None)
assert response is None

# Increase the timeout to let the query finish.
# The same function with the same arguments is still running so
# all this does is wait for the result of the previous call.
response = pool.execute(requests.get, args=(url,), default=None, timeout=3)
response.raise_for_status()

# Returns the previous result because the query times out.
response = pool.execute(requests.get, args=(url,), default=None)
response.raise_for_status()Documentationhttps://querypool.readthedocs.io/
Package: querypp
queryppDeprecation Noticequerypp has been deprecated in favor of vanilla jinja2. After porting it to jinja2, I realized that none of querypp
was actually necessary.Migrating docs here.v0.0.3is the last version that doesn't use jinja2, in case
you want a more lightweight version.querypp is a SQL query[1] templating system based onjinja2.[1]: Although it is trivially adapted to other languages, as the only SQL-specific assumption is the line comment
syntax.Take an example:-- :query users
SELECT *
FROM users
-- :qblock profiles
	LEFT JOIN profiles USING (user_id)
	-- :block login_history
		LEFT JOIN login_history USING (profile_id)
	-- :endqblock
-- :endqblock
-- :qblock user_id WHERE user_id = $1
-- :endqueryA Query template can be called:with no block names to return the query without any blockswith one or more block names to return the query with only those block names.In this case,q('profiles', 'user_id')would return the query with thelogin_historyJOIN removed.Additionally, anyjinja2 templating features,
such as variables and macro functions, can be used, using either the line syntax (e.g.-- :include 'foo.sql')
or the block syntax (e.g.{% if x == 1 %}).Usageenv = querypp.QueryEnvironment('sql/')
queries = env.get_template('queries.sql')  # opens sql/queries.sql
db.execute(queries.users('login_history', 'user_id'), user_id)MotivationAfter moving all my SQL queries to separate files,
I noticed that I was duplicating some of them except for one extra clause.
I created this to allow me to deduplicate such queries.LicensePublic domain, seeCOPYING
Package: query-prom
QueryPrometheusThis is a simple library to ease querying prometheus in python.Getting StartedTo get up and running, you can either clone the repo and go from there. Or it should be pip installable.git clone git@github.com:jpavlav/QueryPrometheus.git
cd QueryPrometheus
pip install -r requirements.txtThe advantage to a pip install is the required packages are included.pip install git+https://github.com/jpavlav/QueryPrometheus.gitPrerequisitesPython3Built WithPython3- Beautiful language.AuthorsJustin Palmer-Urrverything-MeAcknowledgmentsKenneth Reitz ->setup- Thanks!Kamori ->Cool Guy- Thanks to you as well!
Package: query-pts
Query_ptsA package for calculate barycentric coordinates in the tetrahedras.DependencyThis package relies oncuda 10, which has been tested onpytorch 1.7.1andcuda 10.2.Usageimport torch
import query_pts
tet_idx, barycentric = query_pts.cal_barycentric(q_pts, verts, tets, indexes, 4)
Args:
    q_pts (torch.tensor): the query points, [Nq,3]
    verts (torch.tensor): the vertices tethedra, [NV,3]
    tets (torch.tensor): the vertex index of each tet, [NT,4]
    K (int): the nearest neighbors for searching to accelerate query
    use_cuda (bool, optional): _description_. Defaults to True.
Return:
    tet_idx (torch.tensor): the tet which containing the query point, [Nq,]
    barycentric (torch.tensor): corresponding barycentric coordinates, [Nq,4]If a point is not in any tetrahedras, the tet idx is set to-1and barycentric coordinates are set to[0,0,0,0].
Package: query_quiver
QueryQuiverQueryQuiver estimates your interests based on your past Google Chrome search history and suggests technical article ideas that you might be comfortable writing about.Installpipinstallgit+https://github.com/marutaku/QueryQuiverUsagePlease close Google Chrome before using this tool.The tool references the SQLite database used internally by Google Chrome.While using GoogleChrome, this SQLite database will be locked and an error will occur.queryquivergenerateOptionsqueryquivergenerate--help

NAMEqueryquivergenerate-GenerateideaoftecharticlesfromGoogleChromehistorySYNOPSISqueryquivergenerate<flags>

DESCRIPTIONGenerateideaoftecharticlesfromGoogleChromehistoryFLAGS-q,--query_history_limit=QUERY_HISTORY_LIMITType:intDefault:20-n,--number_of_ideas=NUMBER_OF_IDEASType:intDefault:5-c,--chrome_history_path=CHROME_HISTORY_PATHType:Optional[str|None]Default:None-o,--openai_api_key=OPENAI_API_KEYType:Optional[str|None]Default:None-d,--debug=DEBUGType:boolDefault:False-l,--language=LANGUAGEType:strDefault:'en'-u,--use_gpt4=USE_GPT4Type:boolDefault:FalseDeveloper informationsetupmakesetuptestmaketestlintmakelintformatmakeformat
Package: query_reports
Query Reports creates reports based on the django queryset object.## Using the pretty bootstrap templateIf you want to use a pretty bootstrap template instead of the normal sitebase.htmlyou can overridequery_reports/base.htmland just put this in the file{% extends “query_reports/bootstrap_base.html” %}## Running the TestsYou can run the tests with viapython setup.py testorpython run_tests.py
Package: queryrunner
Query-RunnerCLI tool to help with running queries.QuickstartPass through asqlalchemy DB URLand a query to run a query and export to file.
(You may need the relevant DB drivers installed also.)python-mqueryrunnershow"sqlite:///""SELECT 'Val' as col1"python-mqueryrunnerto-csv"sqlite:///""SELECT 'Val' as col1""output.csv"You can also use an environment variable to contain your connection string, and a file to contain your SQL query.DB_URI="sqlite:///"#example-query.sqlSELECT'Val'ascol1python-mqueryrunnerto-csv"DB_URI""example-query.sql""output.csv"Query ParametersYou can pass query parameters as extra CLI options, but this only works for strings.So this will work:python-mqueryrunnershow"sqlite:///""SELECT '5' as col1 WHERE col1=:val"--val5python-mqueryrunnershow"sqlite:///""SELECT 5 as col1 WHERE CAST(col1 as text)=:val"--val5But this will not:python-mqueryrunnershow"sqlite:///""SELECT 5 as col1 WHERE col1=:val"--val5
Package: queryS3
queryS3 APIIntroductionThis API enable users to query images from AI Testing database, currently implementing on AWS S3, with natural English description. A string of keywords also works if users want to put more restrictions onto the picture. The main functionality of this API can be treated in a blackbox manner. That it takes is a string of description and returns a list of S3 object URL of the images.Dependencies- nltk: Natural Language Toolkitgithub link- pandas: powerful Python data analysis toolkitgithub linkInstallationpipinstallqueryS3Example usagefromqueryS3importQS3qs=QS3.QS3()# this line will retrieve all images that have single husky# the return type will be a python listqs.query('single husky')API detailsQS.query(in_q: str): -> List[str]: "query" is a function in the class QS. It takes a english description(or a string of keywords needed) as input and returns a list of S3 object URL stringsQS.set_label_list(self, label_list: List[str]): This function will replace the original label list in the database with a new list of labels only for this object instance of QS. By doing so, the whole "extract label from description" and "label matching search" process will then based on the new set of labels. Duplicated labels will be removed.QS.add_label_list(self, label_list: List[str]): This function will append the label list with the newly added list. Duplicated labels will be removed.AuthorQiao Liu,Everette LiCopyrightCopyright © 2020, The AITestResourceLibrary Authority. Released under the MIT License.
Package: querySDSS
QuerySDSS is a Python script that utilizes the Astropy and Astroquery
libraries to retrieve data from the Sloan Digital Sky Survey (SDSS) Data
Release 18 (DR18). This script fetches information about celestial
objects including their nature (galaxy, star, quasar), redshift,
coordinates, positions, and flux values.RequirementsPython 3.xAstroqueryAstropyYou can install the required packages using the following command:pipinstallastroqueryastropyHow to InstallClone this repository to your local machine using the following command:gitclonehttps://github.com/aCosmicDebbuger/querySDSS.gitcdquerySDSSor you can use pippipinstallquerySDSSUsage:Just opena a terminal where the file is located and runpython3querySDSS.pyor if you need to import it:fromquerySDSS.querySDSS.querySDSSimportquery_sdss_dataa=query_sdss_data(num_observations=3000)print(a)You’ll get a table of SDSS data.
Package: query-selector
Query selector allows one treat a file full of SQL queries as a record, with
one attribute for each annotated query. This makes working with long, ad-hoc
SQL queries more hygienic, and has the benefit of making it easy to find the
queries.TheQuerySelectorconstructor accepts a string, file handle or(<package>, <resource)pair and parses the SQL into groups annotated with--@<name> <mode>. The<name>is any Python compatible name; it will
become an attribute of the object. The<mode>is merely metadata, and can
be omitted; it describes whether a query should have one, none or many
results.For example, a file like this:--@ t oneSELECTnow();becomes an object with a single attributet:>>>q.tQuery(args=[], mode=u'one', readonly=False, text=u'SELECT * FROM now();')AQuerySelectorobject is iterable, providing pairs of name and query in
the order that the queries originally appeared in the file.>>>forname,qinqs:...print'%s:%s'%(name,q)t: Query(args=[], mode=u'one', readonly=True, text='SELECT now();')The Query ConventionIf you have a scripttask.pyand a SQL filetask.sql, or a module in a
packagepackage/module.pyand a SQL filepackage/module.sql, QuerySelector
has a shortcut for you:fromquery_selector.magicimportqueriesforqinqueries:printqThemagicmodule overrides the normal module loading machinery to
determine which script or module is importing it and locate an adjacent SQL
file. This magic is in a separate module to make it stricly opt-in!ModesModes can be one ofnone,one,one?andmany. When not
specified, default ismany. A mode string can also be followed with the
single wordroas a clue that the query is read-only.Realistically,SELECT now()is a read-only query. We can annotate it as
such, the resulting query datastructure records this:>>>QuerySelector("""...--@ t one ro...SELECT now();...""").tQuery(args=[], mode=u'one', readonly=True, text=u'SELECT * FROM now();')Parametersquery-selectorrecognizes the%(...)sstyle parameter references
defined in Python DBI 2.0. Say that we’d like to pass a timezone
when selecting the server time. We can do so by addingAT TIME ZONE %(tz)sto our query. The presence of this parameter is stored in theargsfield
of the parsed result. (The parameters in.argsare listed in the order of
their first appearance in the query.)>>>QuerySelector("""...--@ t one ro...SELECT now() AT TIME ZONE%(tz)sAS t;...""").tQuery(args=[u'tz'], mode=u'one', readonly=True,
      text=u'SELECT now() AT TIME ZONE %(tz)s AS t;')
Package: queryset-reporter
Django Queryset ReporterDescriptionA django pluggable admin-site app for create persisted queryset's and make reports based on them, in various forms of data like cvs's, xlsx's.Project URL:https://github.com/ricardodani/django-queryset-reporter/InstallType:pipinstallqueryset_reporterIn yoursettingsadd:INSTALLED_APPS=[# ...'queryset_reporter',]Migrate `queryset_reporter`` models:./manage.pymigrateAdd url's definitions to yourproject.urlsmodule:path('path-of-choice/',include('queryset_reporter.urls')),PermissionsYou should addqueryset_reporter.can_use_reportsto regular users that you want to access the report view/creation page.Example project credentialsIn order to test the project, there's a Example project with a pre defined database that you can use right away.
Here's the credentials:Admin user:User: admin - Pass: 123Common user:User: tester - Pass: asdfghjklçTested ondjango == 2.2.xpython == 3.7.xAboutAuthor: Ricardo DaniE-mail:ricardodani@gmail.comGithub: github.com/ricardodaniLicenseMIT
Package: queryset-serializer
QuerysetSerializerThis package adds a serializer to ensure all models in the serializers get properly prefetched or selectedinstallationpip install queryset-serializerUsageSimply install the package into your project and import the serializerfromqueryset_serializerimportQuerySetSerializerclassMyModelSerializer(QuerySetSerializer):...classMeta:...In order to prefetch/select everything make sure all serializers used are of QuerySetSerializerNote : You cannot mixrestframework.serializer.ModelSerializerwith this class
(However all instance of ModelSerializer should be replaceable)Configconfigurations can be changed as following:fromqueryset_serializer.serializersimportConfigConfig.meta_class.{setting}={new_value}these are the relevant settings :prefetch_to_attr_prefix , What string will be used as prefix.prefetch_listing , How the prefetch is done (Options: PrefetchToAttrSerializerList, PrefetchSerializerList)prefetch_listingthere are 2 options for the prefetch_listing. (Located inqueryset_serializer.serializers.model)PrefetchToAttrSerializerListwill prefetch/select relations and use theto_attrattribute of thePrefetchclassPrefetchSerializerListwill only prefetch/select relationsThis package by default makes use PrefetchToAttrSerializerList,
The benefit of this is that the.all()calls on the relations are nog longer lazy.This can significantly speed up performance especially on a queryset with a large amount of results or
if there are a lot of child (queryset)serializerThis can also be turned off, and instead do a regular prefetch:fromqueryset_serializer.serializersimportConfigfromqueryset_serializer.serializers.modelimportPrefetchSerializerListConfig.meta_class.prefetch_listing=PrefetchSerializerList