Saravanan666/pypi-org huggingface dataset:
Package: py-SPSPaRTAN
Cython package examplePurposeThe purpose of this package is to demonstrate how to organize a project developed using Cython.
It shows a suitable folder structure according to the best practices, how to create extension modules with Cython, how to implement functions in C and make them available to Cython, how to include package data, how to write asetup.pyscript that allows users without Cython to install the package nonetheless.InstallationFrom a repository checkoutmakeinstallorCYTHONIZE=1pipinstall--user.From PyPipipinstall--usercython-package-example
Package: pysptk
pysptkA python wrapper forSpeech Signal Processing Toolkit (SPTK).NOTE: pysptk is based on a modified version of SPTK (r9y9/SPTK).DocumentationSTABLE—most recently tagged version of the documentation.LATEST—in-development version of the documentation.Demonstration notebookIntroduction notebook: a brief introduction to pysptkSpeech analysis and re-synthesis: a demonstration notebook for speech analysis and re-synthesis. Synthesized audio examples (English) are available on the notebook.InstallationThe latest release is availabe on pypi and you can install it by:pipinstallpysptkIf yout want the latest master, runpipinstallgit+https://github.com/r9y9/pysptkor clone the repository and then build it yourself.
Package: pysptk-speechify
pysptkA python wrapper forSpeech Signal Processing Toolkit (SPTK).NOTE: pysptk is based on a modified version of SPTK (r9y9/SPTK).DocumentationSTABLE—most recently tagged version of the documentation.LATEST—in-development version of the documentation.Demonstration notebookIntroduction notebook: a brief introduction to pysptkSpeech analysis and re-synthesis: a demonstration notebook for speech analysis and re-synthesis. Synthesized audio examples (English) are available on the notebook.InstallationThe latest release is availabe on pypi and you can install it by:pipinstallpysptkIf yout want the latest master, runpipinstallgit+https://github.com/r9y9/pysptkor clone the repository and then build it yourself.
Package: pysptools
PySptools is a python module that implements spectral and hyperspectral algorithms. Specializations of the library are the endmembers extraction, unmixing process, supervised classification, target detection, noise reduction, convex hull removal, features extraction at spectrum level and a scikit-learn bridge. Version 0.15.0 introduce an experimental machine learning functionality based on XGBoost and LightGBM.The library is designed to be easy to use and almost all functionality has a plot function to save you time with the data analysis process. The actual sources of the algorithms are the Matlab Hyperspectral Toolbox of Isaac Gerg, the pwctools of M. A. Little, the Endmember Induction Algorithms toolbox (EIA), the HySime Matlab module by José Bioucas-Dias and José Nascimento and science papers.FunctionalitiesThe functions and classes are organized by topics:abundance maps: FCLS, NNLS, UCLSclassification: AbundanceClassification, NormXCorr, SAM, SIDdetection: ACE, CEM, GLRT, MatchedFilter, OSPdistance: chebychev, NormXCorr, SAM, SIDendmembers extraction: ATGP, FIPPI, NFINDR, PPImachine learning: XGBoost, LightGBMmaterial count: HfcVd, HySimenoise: Savitzky Golay, MNF, whitensigproc: bilateralscikit learn: HyperEstimatorCrossVal, HyperSVC, HyperGradientBoostingClassifier, HyperRandomForestClassifier, HyperKNeighborsClassifier, HyperLogisticRegression and othersspectro: convex hull quotient, features extraction (tetracorder style), USGS06 lib interfaceutil: load_ENVI_file, load_ENVI_spec_lib, corr, cov, plot_linear_stretch, display_linear_stretch, convert2D, convert3D, normalize, InputValidation, ROIs and othersThe library do an extensive use of the numpy numeric library and can achieve good speed for some functions. The library is mature enough and is very usable even if the development is at a beta stage (and some at alpha).InstallationFor installation, I refer you to the web sitehttps://pysptools.sourceforge.io/installation.htmlDependenciesPython 2.7 or 3.5, 3.6numpy, requiredscipy, requiredscikit-learn, required, version >= 0.18spectral, required, version >= 0.17matplotlib, required, [note: pytsptools >= 0.14.2 now execute on matplotlib 2.0.x and stay back compatible]CVXOPT, optional, version >= 1.1.7, [note: to run FCLS]jupyter, optional, version >= 1.0.0, [note: if you want to use the notebook display functionality]tabulate, optional, [note: use by ml module]pandas, optional, [note: use by ml module]plotnine, optional, [note: use by ml module, a ggplot2]lightgbm, optional, version 2.1.2 ONLY, [note: use by ml module]xgboost, optional, version 0.72.1 ONLY, [note: use by ml module]PySptools version 0.15.0 is developed on the linux platform with anaconda version 5.1.0 for both python 2.7 and 3.6.
Package: py-spy-for-datakit
py-spy-for-datakit: Send profiling data to datakit instead of writing to a fileInstallationPrebuilt binary wheels can be installed from PyPI with:pip install py-spy-for-datakitIf you have rust and cargo installed, py-spy-for-datakit can also be installed with:cargo install py-spy-for-datakit.In addition to above, you can also download prebuilt binaries for most platforms from theGitHub Releases
Pagedirectly.Usagepy-spy-for-datakit works from the command line and takes either the PID of the program you want to sample from
or the command line of the python program you want to run.# Use process PIDsudopy-spy-for-datakitdatakit--host127.0.0.1--port9295--servicepy-spy-demo--envdev--versionv0.1--pid12345# OR use your app starting command linesudopy-spy-for-datakitdatakit--host127.0.0.1--port9295--servicepy-spy-demo--envdev--versionv0.1--pythonmyapp.pyFor more usage help, usepy-spy-for-datakit help datakitcommand or refer topy-spymanual
Package: py-spy-kw
py-spy-kw is a project forked from benfred/py-spy
(https://github.com/Rosyuku/py-spy/releases/tag/v0.3.3).InstallationPrebuilt binary wheels can be installed from PyPI with:pip install py-spy-kwUsagepy-spy-kw supports additional one subcommandlogwhich can output
stack trace jsonfiles of python process automatically every sampling.
Following code is a sample command that launches myprogram.py and
outputs stack trace jsonfiles to ./log 10 times per second until the
process ends.py-spy-kwlog-o./log-r10--pythonmyprogram.pylog output
Package: pyspyne
Spyne v1.0.0The all-in-one Python package.SetupIn your terminal:$pipinstallpyspyneIn the python file:importpyspyneModules####MathYou can use all the methods in the regular Python Math module in Spyne Mathmath=spyne.mathmy_equation=math.Equation("2 * x")Creates a new Equation object for the Graphr Module####Graphrgraphr=spyne.graphrgraphr.draw(my_equation,units=1)Draws a turtle graph based on the equationParameters:my_equation (Required): Equation object from Spyne Mathunits (Default=1): Graph units###Extended documentation coming soon!
Package: pysqes
pysqes======*Simple queue service for python using SQS and boto.*.. image:: https://travis-ci.org/sauramirez/pysqes.png:alt: Build Status:target: https://travis-ci.org/sauramirez/pysqesUsage======In order to create a task you can use the SQSTask class to createan instance that include a function decorator which can be sentto the queue when you run the delay method that will be addedto the function. The delay function takes the parameters that willbe used by the worker when it actually executes the task... code-block:: pythonfrom boto.sqs.connection import SQSConnectionfrom pysqes.task import Taskconn = SQSConnection('ACCESS_KEY', 'SECRET_KEY')queue = Queue(conn, 'pysqes_test', backend=backend)def add(a, b):return a + b# this will submit a job to the queuequeue.enqueue(add, 1, 2)You can run the task by using the work method included in theSQSWorker class, all you need to do is create a worker instance... code-block:: pythonfrom boto.sqs.connection import SQSConnectionfrom pysqes.runners.gevent_runner import GeventRunnerfrom pysqes.worker import Workerconn = SQSConnection('ACCESS_KEY', 'SECRETE_KEY')runner = GeventRunner()queue = Queue(conn, 'pysqes_test', backend=backend)worker = Worker(queue, runner=runner)worker.work()New in 0.2======Worker Runners=====Pysqes now supports having different runners, the default one is theprocess runner, which will spawn a new a process and run the task in it.We also have a gevent runner, which you can use by using the gevent flagin the command line and set the number of threads you would like to haverunning.Note: It has only been tested with gevent 1.0Command line scripts=====Pysqes now comes with command line scripts. The worker command will be the onlyone available for this version, but task and peek commands may be coming to 0.3... code-block:: bashpysqes worker --gevent --workerpath=/home/user/pysqesproj/ --config=pysqesconfig --configpath=/home/user/pysqesproj/settings/Running the tests======If you are using python 2.7 you can run the unit tests byusing the new discover runner included in the unittest module:.. code-block:: bashpython -m unittest discover -s testsor you can just run each unit test individually.Coming in 0.3======* New command line scripts.* Tests for command line scripts.* Better logging.
Package: pysql
PySQL=====PySQL aims to be a full replacement for sqlplus (and much more).It has features such as history, completion, explain plan, session list,background queries, datamodel graphical output, object dependencies,PL/SQL package function call tree...Installation from source========================As a simple user : just untar pysql tarball where you want and just run pysql...As root : untar pysql tarball where you want and run the setup script...Installation from package========================Redhat, Debian, Slackware, Windows....Documentation generation========================Use the doc.sh script in script/ dir. You will need Epydoc (http://epydoc.sf.net).You can also browse documentation online at : http://pysql.sf.net/doc/
Package: pysql-beam
pysql-beamThis package is still under development but has been used in few projects in production. This has been tested with dataflow Runner and Direct runnerThis package aim to provide Apache_beam io connector for MySQL and Postgres database.This package provides apache beam io connector for postgres db and mysql db.
This package wil aim to be pure python implementation for both io connectorFYI: This does not uses any jdbc or odbc connectorRequirements:1. Python>=2.7 or python>= 3.5
2. Apache beam >= 2.10
3. pymysql[rsa]
4. psycopg2-binaryInstallation:1. pip install git+git@github.com:MediaAgility/pysql-beam.gitCurrent functionality:1. Read from MySQL database by passing either table name or sql query
2. Read from Postgres database by passing either table name or sql queryReference Guide:Java IO connector for the same:https://github.com/spotify/dbeamHow to write io connector for Apache Beam:https://beam.apache.org/documentation/io/developing-io-overview/https://beam.apache.org/documentation/io/developing-io-python/Usage Guide:from pysql_beam.sql_io.sql import ReadFromSQL

....
ReadFromSQL(host=self.options.host, port=self.options.port,
        username=self.options.username, password=self.options.password,
        databse=self.options.database,
        query=self.options.source_query,
        wrapper=PostgresWrapper,
        batch=100000)Examples:For mysql:
`python cloud_sql_to_file.py --host localhost --port 3306 --database SECRET_DATABASE --username SECRET_USER --password SECRET_PASSWORD --table YOUR_TABLE --output YOUR_OUTPUT_FLLE`

For postgres:
`python cloud_sql_to_file.py --host localhost --port 5432 --database SECRET_DATABASE --username SECRET_USER --password SECRET_PASSWORD --table YOUR_TABLE --output YOUR_OUTPUT_FLLE`contribution:
You can contribute to this package by raising bugs or sending pull requests
Package: pysqlcipher3
Python interface to SQLCipherpysqlcipher3 is an interface to the SQLite 3.x embedded relational
database engine. It is almost fully compliant with the Python database API
version 2.0. At the same time, it also exposes the unique features of
SQLCipher. Prior to installation, libsqlcipher must already be installed
on your system, with the process dependent on your operating system.
Package: pysqlcipher3-binary
Python interface to SQLCipherpysqlcipher3 is an interface to the SQLite 3.x embedded relational
database engine. It is almost fully compliant with the Python database API
version 2.0. At the same time, it also exposes the unique features of
SQLCipher. Prior to installation, libsqlcipher must already be installed
on your system, with the process dependent on your operating system.
Package: pysql-cli
PySQLPython wrapper for making MySQL queries easier to executeInstallationClone the repository to your local machinegit clone https://github.com/Devansh3712/PySQL.gitInstallation pre-requisitesMySQL local serverPyPi packageWindowspip install pysql-cliLinux / MacOSpip3 install pysql-cliAutomatic InstallationOpen thePySQLdirectory and run the install fileWindowsinstall.batLinux / MacOSchmod +x ./install.sh./install.shManual SetupOpen thePySQLdirectoryusing requirements.txtpip install -r requirements.txtusing poetrypoetry installUsageUsing the pip packagepysql: Basic PySQL CLIcpysql: Colored PySQL CLIpysqlcpysqlUsing the Python command-line wrapper.py filemain.py: Basic PySQL CLImain_c.py: Colored PySQL CLIWindowspython pysql/main.pypython pysql/main_c.pyLinuxpython3 pysql/main.pypython3 pysql/main_c.pyCommandsList of available commandsALL COMMANDS

    select              TB_NAME, COLUMNS, ARGS      Displays selected columns of a table
    insert      -s      TB_NAME, ARGS               Insert a single row in a table
                -m      TB_NAME, NUM, ARGS          Insert `NUM` rows in a table
                -f      TB_NAME, FILE_NAME          Insert values in a table from CSV file
    update              TB_NAME, COLUMNS, ARGS      Updates values of columns in a table
    delete              TB_NAME, COLUMN             Deletes values of row in a table
    showdb                                          Display all databases in MySQL server
    usedb                                           Use a database
    createdb            DB_NAME                     Create a new database
    dropdb              DB_NAME                     Delete a database
    showtb                                          Display all tables in current db
    createtb            TB_NAME, ARGS               Create a new table in current db
    droptb              TB_NAME                     Delete a table in current db
    trunctb             TB_NAME                     Truncate a table in current db
    desctb              TB_NAME                     Display structure of a table in current db
    altertb             TB_NAME, ARGS               Alter contents of table in current db
    exportdb            DB_NAME, PATH               Export db as `.sql` file to path
    exporttb    -json   TB_NAME, PATH               Export table as `.txt` file to path
                -csv    TB_NAME, PATH               Export table as `.csv` file to path
                -sql    TB_NAME, PATH               Export table schema as `.sql` file to path
    exportall   -json   PATH                        Export all tables in db as `.txt` file to path
                -csv    PATH                        Export all tables in db as `.csv` file to path
                -sql    PATH                        Export all tables schema in db as `.sql` file to path
    importdb            DB_NAME, PATH               Import `.sql` file into input database
    importtb            DB_NAME, PATH               Import `.sql` table schema into input table
Package: pysqldbm
pysqldbmA python API to wraphttps://developers.sqldbm.com/.sqldbmCLI toolInstallationpipinstallpysqldbm[cli]Usagesqldbm--helpexportSQLDB_API_KEY="your_api_key"sqldbmlist-projects# or `sqldbm --api-key="your_api_key" list-projects`pysqldbmlibraryInstallationpipinstallpysqldbmIf you would like to use the latest overnight builds, you can install from test pypipipinstall-ihttps://test.pypi.org/simple/pysqldbmSample Usage with Clientimportpysqldbm# Create a clientAPI_KEY="your_api_key"sqldbm=pysqldbm.client(API_KEY)forprojectinsqldbm.list_projects():print(f"Show revisions for project '{project['name']}'...")forrevisioninsqldbm.list_revisions(project['id']):print(revision)ArchitectureSeeARCHITECTURE.md.
Package: pysqldict
A library that allows python dictionaries to be stored in SQLite and provides a simple interface for read and write.Free software: MIT licenseInstallationpip install pysqldictDocumentationhttps://pysqldict.readthedocs.io/DevelopmentTo run the all tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.1.1 (2019-02-20)Added support for updating and deleteing data.0.1.0 (2019-02-05)First release on PyPI.
Package: pysqleet
Pysqleet is a Python wrapper aroundsqleet. It is a drop in replacement
for the standard libraries sqlite3.Installationpip install pysqleetUsageThe usage is the same as sqlite3 with a few differences.You can pass the kwargkey=[bytes, str, None]tosqleet.connect()andsqleet.Connection.You can callconnection.change_key(key: [bytes, str, None])to change the key on an already
open database. Setting the key to None will decrypt the database, making it compatible with the traditional
sqlite3 lib.A new exception typesqleet.AuthenticationError(sqleet.DatabaseError)is exposed,
which is raised on authentication based errors.Example:importsqleetkey=b"Key"db_name="test.sqlite3"# Create a new encrypted dbcon=sqleet.connect(db_name,key=key)con.execute("create table test(col char);")con.commit()con.close()# Try to open db with the wrong key, this failstry:con=sqleet.connect(db_name,key="The wrong key")exceptsqleet.AuthenticationError:print("Failed to open database")# Remove the encryption on the created databasecon=sqleet.connect(db_name,key=key)con.change_key(None)con.close()VersioningThe versions (sqleet.__version__) first 2 places (major, minor) match the sqleet version used in the sources.
For example an sqleet version of 1.2.3 would have pysqleet version of 12.3. The last place (patch) is used
internally for pysqleet patches.SourcesPysqleet mixes source code from the below sources, with any modifications being noted in the copyright header
at the beginning of the file.CPython v3.6.14sqlite3 module. (C Sources(used for ext _sqleet),Python sources(used for sqleet py module) )Sqleet v0.31.1amalgamation
Package: pysqlflow
#### 项目git：https://github.com/lqkweb/sqlflow#### Blog：http://www.leiqiankun.com#### 简书博客: https://www.jianshu.com/u/3fe4aab60ac4开发交流QQ群: 941879291# SQLflow (python3.6)SQLflow based on python development, support to Spark, as the underlying distributed computing engine, through a set of unified configuration file to complete the batch, flow calculation, the Rest service development.##### 2019-03-26 更新后台路由,前端抽取base模板并更新使用ajax方式执行sql语句主页：<div align="center"><a href="https://buglib.tech/" target="_blank"><img src="https://upload-images.jianshu.io/upload_images/11023671-f9f8887c69961f55.png" alt="SQLflow Logo" width="500px"></img></a></div>结果页：<div align="center"><a href="https://buglib.tech/" target="_blank"><img src="https://upload-images.jianshu.io/upload_images/11023671-b4d8905fda2ebe67.png" alt="SQLflow Logo" width="500px"></img></a></div># 目标SQLflow 基于python开发, 支持通过写sql的方式操作分布式集群, 运行spark, 机器学习, 深度学习, 分布式爬虫, 数据可视化。# Buildpython3.6git clone https://github.com/lqkweb/sqlflow.gitpip install -r requirements.txtpython manage.py主页：http://127.0.0.1:5000脚本页面：http://127.0.0.1:5000/script单sql页面：http://127.0.0.1:5000/sql【注意：1、下载apache spark文件配置manage.py中的SPARK_HOME路径。2、data.csv是放到sqlflow/data目录中】# Usage [sparksql doc:https://spark.apache.org/docs/latest/api/sql/index.html]在脚本执行页面：http://127.0.0.1:5000/script  输入 select * from A limit 3; 或者 select * from A limit 3 as B; 生成临时表A或者B生成临时表A数据:select * from A limit 3;生成临时表B数据:select * from A limit 3 as B;打开单sql执行页面：http://127.0.0.1:5000/sql, 直接就可以用spark sql语法操作数据表A和数据表B了:desc Aselect * from A limit 2select * from B limit 2as B 相当于创建了一个 B 临时表。一个简单的sql操作spark集群的demo,是不是很简单。### [还有更多sql版黑科技，sql版scikitlearn, sqlspider, sqlcharts, sqlkeras深度学习平台正在内测中！]### * 正在新增sql版机器学习算法功能, 谢谢支持。 *### * 正在新增sql版爬虫功能, 谢谢支持。 *### * 正在新增sql版数据可视化功能, 谢谢支持。 *### * 正在新增sql版keras深度学习功能, 谢谢支持。 *# 记得给个star鼓励一下！Thanks♪(･ω･)ﾉ----------[![HitCount](http://hits.dwyl.io/lqkweb/sqlflow.svg)](http://hits.dwyl.io/lqkweb/sqlflow)
Package: pysqlformatter
pyspark-sql-formatterA formatter for Pyspark code with SQL queries. It relies on Python formatteryapfand SparkSQL formattersparksqlformatter, both working indepdendently. User can specify configurations for either formatter separately.The queries should be in the formspark.sql(query)orspark.sql('xxx'). Cases likespark.sql('xxx'.format()),spark.sql('xxx'.replace())may raise Exceptions.pyspark-sql-formatterInstallationInstall using pipInstall from sourceCompatibilityUsageUse as command-line toolUse as Python libraryInstallationInstall using pippip install pysqlformatterInstall from sourceDownload source code.Navigate to the source code directory.Dopython setup.py installorpip install ..CompatibilitySupports Python 2.7 and 3.6+.Usagepysqlformattercan be used as either a command-line tool or a Python library.Use as command-line toolusage: pysqlformatter [-h] [-f FILES [FILES ...]] [-i] [--query-names QUERY_NAMES [QUERY_NAMES ...]] [--python-style PYTHON_STYLE] [--sparksql-style SPARKSQL_CONFIG]

Formatter for Pyspark code and SparkSQL queries.

optional arguments:
  -h, --help            show this help message and exit
  -f FILES [FILES ...], --files FILES [FILES ...]
                        Paths to files to format.
  -i, --in-place        Format the files in place.
  --python-style PYTHON_STYLE
                        Style for Python formatting, interface to https://github.com/google/yapf.
  --sparksql-style SPARKSQL_CONFIG
                        Style for SparkSQL formatting, interface to https://github.com/largecats/sparksql-formatter.
  --query-names QUERY_NAMES [QUERY_NAMES ...]
                        String variables with names containing these strings will be formatted as SQL queries. Default to 'query'.E.g.,$ pysqlformatter -f <path_to_file> --python-style='pep8' --sparksql-style="{'reservedKeywordUppercase': False}" --query-names queryOr using config files:$ pysqlformatter -f <path_to_file> --python-style="<path_to_python_style_config_file>" --sparksql-style="<path_to_sparksql_config_file>" --query-names queryUse as Python libraryCallpysqlformatter.api.format_script()to format script passed as string:>>> from pysqlformatter import api
>>> script = '''query = 'select * from t0'\nspark.sql(query)'''
>>> api.format_script(script=script, pythonStyle='pep8', sparksqlConfig=sparksqlConfig(), queryNames=['query'])
"query = '''\nSELECT\n    *\nFROM\n    t0\n'''\nspark.sql(query)\n"Callpysqlformatter.api.format_file()to format script in file:>>> from pysqlformatter import api
>>> api.format_file(filePath=<path_to_file>, pythonStyle='pep8', sparksqlConfig=sparksqlConfig(), queryNames=['query'], inPlace=False)
...
Package: pysqlite3tool
SQLiteToolThe cross-platform sqlite3 based tool to work with SQLite database.SQLiteTool can:Execute custom SQL querySelect (returns list)DeleteInsertInsert manyCreate database (not implemented)Update database (not implemented)Get cursor to access to low-level original sqlite3 methods.InstallationFor most users, the recommended method to install is via pip:pip install psqliteImportfrompysqlite3toolimportSQLiteToolHelpful predefined methodsinsertselectdelete...CHANGELOG0.0.1a (8.01.2020) Initial commit. The first alpha