Saravanan666/pypi-org huggingface dataset:
Package: db-env
**Version 0.4**--- What can db_env do? ---db_env aims to make it easier and more straight forward to create relational database environments within Python. db_env uses SQLite and Pandas as dependencies. Currently db_env holds the following functions:- create_connect_db --> connecting to newly created database- create_table_sql --> connecting to database and creating tables within- insert_data_sql --> connecting to database and inserting data- select_data_sql --> connecting and fetching data from chosen tables. It automatically creates a new Pandas dataframe for further analysis.--- important Info: ---- this library needs SQLite3 and Pandas in addition. As dependencies all packages will be installed automatically.- SQL-Usage: db_env uses SQLite and therefore SQL-statements for creating, calling and manipulating data.- it is encouraged to import your writen SQL-strings from another py-file as a variable (e.g. ENUM). However, you can directly insert your SQL-statement as a string into the function.--- Example SQL-statements for existing functions: -----> create_table_sql ="DROP TABLE IF EXISTS ORDERS; CREATE TABLE ORDERS(ID INTEGER, NAME VARCHAR(30));"--> insert_data_sql ="INSERT INTO ORDERS (ID, NAME) VALUES (1, 'Frank');"or(f'''INSERT INTO ORDERS (ID, NAME) VALUES(5, 'John'),(6, 'Tobias'),(7, 'Lisa');''', "orders.db")--> select_data_sql ="SELECT * FROM ORDERS;"--- Goal for upcoming versions: ---- Functions which give user the option to write his own SQL-statements into an extra Python file and call writen SQL-strings as variables into your working environment.- Functions to collect and insert data from called API.-------------- CHANGES in VERSION 0.4 --------------2024-02-25- installed dependencies (Pandas)- created function to select data from db and create dataframe- created function to insert data into database manually----------------------------------------------------
Package: dber
使用教程快速开始importdberdb=dber.SQLite("test.db")create_table_sql="""CREATE TABLE IF NOT EXISTS t_test (data_key varchar(255) PRIMARY KEY,data_value text,data_int integer);"""# 创建数据表db.execute(create_table_sql)# 插入数据db.replace("replace into t_test values (?,?,?)","test_key","test_data",1)# 查询数据print(db.select("select * from t_test where data_key = ?","test_key"))print(db.selectOne("select * from t_test where data_key = ?","test_key"))print(db.selectTable("t_test",data_key="test_key"))# 查询字段print(db.getColumnIntValue("select data_int from t_test where data_key = ?","test_key"))print(db.getColumnFloatValue("select data_int from t_test where data_key = ?","test_key"))print(db.getColumnBoolValue("select data_value,data_int from t_test where data_key = ?","test_key",column="data_int"))# 批量插入数据rows=[]foriinrange(0,100):row=(f"k{i}",f"v{i}",i)rows.append(row)db.replaceBatch("replace into t_test values (?,?,?)",rows)print(db.count("t_test"))print(db.count("t_test",where="data_int > 90"))# 更新数据db.update("update t_test set data_int=? where data_key = ?",100,'test_key')# 删除数据db.delete("delete from t_test")# 清空表db.clear("t_test")# 删除表db.drop("t_test")# 关闭db.close()
Package: dbest
All rights reserved.Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.Description: DBEst Repository========================This project implements the Approximate Query Processing engine (AQP) of DBEst.DBEst is a model-based AQP engine using regression models and density estimator.Currently DBEst supports various aggregate funcitons, including COUNT, SUM, AVG, PERCENTILE, VARIANCE, STDDEV, MIN, MAX, etc.Group By is also supported.The main function is located in creg/DBEst.pyv2.0 RoadMap---------------1. Enable multi-thread training\\2. Enable multi-thread prediction, especially group by\\3. Transfer to Java4. DBEst over sparkKeywords: Approximate Query Processing AQPPlatform: UNKNOWNClassifier: Development Status :: 2.0Classifier: License :: OSI Approved :: MIT LicenseClassifier: Programming Language :: Python :: 3.6Classifier: Topic :: Approximate Query Processing :: AQP :: Data Warehouse
Package: dbest-sdk
dbest_sdkA Python package for remote control of DBEST (drone battery exchanger system for DJI Mavic 2 products)Free software: MIT licenseDocumentation:https://dbest-sdk.readthedocs.io.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2020-07-27)First release on PyPI.
Package: dbf
Currently supports dBase III, Clipper, FoxPro, and Visual FoxPro tables. Text is returned as unicode, and codepage settings in tables are honored. Memos and Null fields are supported.  Documentation needs work, but author is very responsive to e-mails.Not supported: index files (but can create tempory non-file indexes), auto-incrementing fields, and Varchar fields.Installation:pip install dbf
Package: dbf2csv-dbase7
Conversión de formato DBF a CSVScript simple para convertir ficheros de formato DBF a CSV. De momento sólo funciona para ficheros DBF "dBASE level 7".Uso:$ ./dbfconv.py <fichero.dbf>También se puede instalar desdehttps://pypi.orgcomo:$ pip install dbf2csv-dbase7Una vez descargado se puede ejecutar del siguiente modo:$ python -m dbf2csv <fichero.dbf>O también se puede instalar como pipx:$ pipx install dbf2csv-dbase7Lo que añade la utilidaddbf2csv:$ dbf2csv <fichero.dbf>
Package: db-facts
db-factsdb-facts translates from user-familiar database coordinates (e.g.,
"redshift", "corppostgres dbadmin", "productoracle impl juser") into
detailed instructions on how to access the database in question,
providing configuration and templating mechnisms to wrap any
credential management tools involved in providing those details and
credentials.Example:$db-factsshredshiftexportCONNECTION_TYPECONNECTION_TYPE=directexportLASTPASS_SHARE_NAME_SUFFIXLASTPASS_SHARE_NAME_SUFFIX='blue labs redshift'exportDB_PASSWORDDB_PASSWORD='hunter2'DB_HOST=whatevs.whatevs.us-east-1.redshift.amazonaws.comexportDB_HOSTexportDB_DATABASEDB_DATABASE=analyticsexportDB_USERNAMEDB_USERNAME=vbrozexportDB_PORTDB_PORT=5439exportDB_TYPEDB_TYPE=redshiftexportDB_PROTOCOLDB_PROTOCOL=postgresFor details on the potential facts returned, see theAPI reference.db-factsrelies on a config file ("dbcli.yml") which teaches it
how to parse the user-friendly coordinates.  Much of the heavy lifting
in the parsing part is done
byjinja_context.py,
which sets some variables and functions that can be used in jinja
templates within the config file.If you need to set the instructions immediately to your environment
variables, you can do this with the command:eval$(db-factsshredshift)For AWS IAM credentials in Lastpass, ensure that this block exists underexports_from:in your db-facts config:lpass_aws_iam:
    pull_lastpass_aws_iam: "{{ lastpass_entry }}"and set up a db credential with export_typelpass_aws_iam, for example:aws_user_example:
    exports_from: lpass_aws_iam
    lastpass_entry: 'AWS IAM: example_user'You can then credential your shell with this one-liner:eval $(db-facts sh aws_user_example)You can also accessdb-factsvia a Python API; for details, see theAPI reference.ConfigurationYou can configuredb-factsto connect to your databases.  SeeCONFIGURATION.mdfor details.ExtensionsYou can extenddb-factsto pull configuration from other systems.
SeeEXTENSIONS.mdfor details.LibraryTo use as a library:$python
Python3.5.2(default,Sep122016,09:31:17)[GCC4.2.1CompatibleAppleLLVM7.3.0(clang-703.0.31)]ondarwin
Type"help","copyright","credits"or"license"formoreinformation.
>>>importbluelabs_db_facts
>>>db_facts.db(['redshift']){'protocol':'postgres','lastpass_share_name_suffix':'blue labs redshift','host':'bl-int-analytics1.cxtyzogmmhiv.us-east-1.redshift.amazonaws.com','connection_type':'direct','user':'vbroz','database':'analytics','password':'hunter1','port':5439,'type':'redshift'}>>>DevelopmentSeeDEVELOPMENT.md
Package: db-faker
Database fakerCLI application that handles the creation of fake data for test databases.Free software: MIT licenseDocumentation:https://db-faker.readthedocs.io.FeaturesCreation of fake data from a JSON schema defining the database structure.Extensible outputs. Console and File outputs available from the box.CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.1 (2020-09-14)First release on PyPI.
Package: dbfe
DBFE: Distribution-Based Feature ExtractorDBFE is a Python library with feature extraction methods that facilitate classifier learning from distributions of genomic variants.Installing dbfeTo install dbfe, just execute:pipinstalldbfeQuickstartimportpandasaspdfromsklearn.metricsimportroc_auc_scorefromsklearn.model_selectionimporttrain_test_splitfromsklearn.pipelineimportmake_pipelinefromsklearn.preprocessingimportStandardScalerfromsklearn.linear_modelimportLogisticRegressionimportdbfe# sample datastat_vals=pd.read_csv(f"../experiments/data/ovarian/ovarian_cnv.csv.gz",index_col='SAMPLEID')stat_vals=stat_vals.loc[stat_vals.SVCLASS=="DEL",:]stat_vals=stat_vals.groupby(stat_vals.index)['LEN'].apply(list).to_frame()labels=pd.read_csv(f"../experiments/data/ovarian/labels.tsv",sep='\t',index_col=0)labels=(labels=="RES")*1stat_df=stat_vals.join(labels.CLASS_LABEL,how='inner')# splitting into training and testing dataX=stat_df.loc[:,"LEN"]y=stat_df.loc[:,"CLASS_LABEL"]X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.25,random_state=23,stratify=y)# DBFE in a classification pipelineextractor=dbfe.DistributionBasedFeatureExtractor(breakpoint_type='supervised',n_bins='auto',cv=10)pipe=make_pipeline(extractor,StandardScaler(),LogisticRegression())pipe.fit(X_train,y_train)extractor.plot_data_with_breaks(X_train,y_train,plot_type='kde')y_prob=pipe.predict_proba(X_test)print("AUC on test data:{:.3}".format(roc_auc_score(y_test,y_prob[:,1])))LicenseThis project is released under a permissive new BSD open source license (LICENSE-BSD3.txt) and commercially usable. There is no warranty; not even for merchantability or fitness for a particular purpose.In addition, you may use, copy, modify and redistribute all artistic creative works (figures and images) included in this distribution under the directory
according to the terms and conditions of the Creative Commons Attribution 4.0 International License.  See the fileLICENSE-CC-BY.txtfor details. (Computer-generated graphics such as the plots produced by seaborn/matplotlib fall under the BSD license mentioned above).CitingIf you use dbfe as part of your workflow in a scientific publication, please consider citing the associated paper:Piernik, M.et al.(2022) DBFE: Distribution-based feature extraction from copy number and structural variants in whole-genome data.
Package: dbf_light
https://github.com/idlesign/dbf_lightDescriptionLight and easy DBF readerNo fancy stuff, just DBF reading for most common format versions.Python 2.7, 3.5+;Usesnamedtuplefor row representation and iterative row reading to minimize memory usage;Works fine with cyrillic (supports KLADR and CBRF databases);Reads .dbf from zip files.APIfromdbf_lightimportDbfwithDbf.open('some.dbf')asdbf:forfieldindbf.fields:print('Field:%s'%field)print('Rows (%s):'%dbf.prolog.records_count)forrowindbf:print(row)# Read `some.dbf` from zip (ignoring filename case):withDbf.open_zip('some.dbf','here/myarch.zip',case_sensitive=False)asdbf:...CLIRequiresclickpackage (can be installed with:pip install dbf_light[cli]).$dbf_lightdescribemyfile.dbf$dbf_lightshowmyfile.dbf
Package: dbfn
The Discord Bot Functions Module contains functions to enhance and simplify your python Discord Bot.Instalationpip install dbfnUsage and examplesAt the moment it only contains one function: Reaction Books, which allows the user to create interactable embedsAn example of a basic bookfromdbfnimportreactionbook# (inside a cog)asyncdeffunction(self,ctx):book=reactionbook(self.bot,ctx)book.createpages("This page only has one line")book.createpages(["This page only has...","...two"])awaitbook.createbook(TITLE="Example book",MODE="numbers")
Package: dbfpy
dbfpy is a python-only module for reading and writing DBF-files.
It was created by Jeff Kunce and then modified by Hans Fiby
and Yaroslav Samchuk.dbfpy can read and write simple DBF-files.  TheDBF-formatwas developed about 30 years ago and was used by a number
of simple database applications (dBase, Foxpro, Clipper, …).
The basic datatypes numbers, short text, and dates are available.
Many different extensions have been used; dbfpy can read and write
only simple DBF-files.
Package: dbfpy3
Python 3 modules for accessing .dbf filesPort to Python 3 and released at PyPi by Frank Xu.### FeaturesSupport FoxProSupport memoCode page### TODOWrite testdBase compatible### InstallRunpip install dbfpy3—### NOT FULLY TEST YET### USE AT YOUR OWN RISK### NO WARRANTIES WHATSOEVER—steelywing <https://github.com/steelywing/dbfpy>Jeff Kunce <kuncej@mail.conservation.state.mo.us>Hans Fiby <hans@fiby.at>Frank Xu <https://github.com/frankyxhl/dbfpy3>Zdeněk Böhm <https://github.com/zbohm>History0.1.0 (2020-12-26)First release on PyPI.
Package: dbfread
DBF is a file format used by databases such dBase, Visual FoxPro, and
FoxBase+. This library reads DBF files and returns the data as native
Python data types for further processing. It is primarily intended for
batch jobs and one-off scripts.>>> from dbfread import DBF
>>> for record in DBF('people.dbf'):
...     print(record)
OrderedDict([('NAME', 'Alice'), ('BIRTHDATE', datetime.date(1987, 3, 1))])
OrderedDict([('NAME', 'Bob'), ('BIRTHDATE', datetime.date(1980, 11, 12))])By default records are streamed directly from the file.  If you have
enough memory you can instead load them into a list. This allows for
random access:>>> table = DBF('people.dbf', load=True)
>>> print(table.records[1]['NAME'])
Bob
>>> print(table.records[0]['NAME'])
AliceFull documentation athttps://dbfread.readthedocs.io/See docs/changes.rst for a full list of changes in each version.Main Featureswritten for Python 3, but also works in 2.7simple but flexible APIdata is returned as native Python data typesrecords are ordered dictionaries, but can be reconfigured to be of
any typeaims to handle all variants of DBF files. (Currently only widely
tested with Visual FoxPro, but should work well with other
variants.)support for 18 field types. Custom types can be added by subclassingFieldParserreadsFPTandDBTmemo files, both text and binary datahandles mixed case file names gracefully on case sensitive file systemscan retrieve deleted recordsInstallingRequires Python 3.2 or 2.7.pip install dbfreaddbfreadis a pure Python module and doesn’t depend on any packages
outside the standard library.To build documentation locally:python setup.py docsThis requires Sphinx. The resulting files can be found indocs/_build/.Source codeLatest stable release:http://github.com/olemb/dbfread/Development version:http://github.com/olemb/dbfread/tree/develop/API Changesdbfread.open()anddbfread.read()are deprecated as of version2.0, and will be removed in2.2.TheDBFclass is no longer a subclass oflist. This makes the
API a lot cleaner and easier to understand, but old code that relied
on this behaviour will be broken. Iteration and record counting works
the same as before. Other list operations can be rewritten using therecordattribute. For example:table = dbfread.read('people.dbf')
print(table[1])can be rewritten as:table = DBF('people.dbf', load=True)
print(table.records[1])open()andread()both returnDeprecatedDBF, which is a
subclass ofDBFandlistand thus backward compatible.Licensedbfread is released under the terms of theMIT license.ContactOle Martin Bjorndalen -ombdalen@gmail.com
Package: dbf_read_iffy
Make possible to read from dbf’s with codepage unsupported by modules
dbf and codecs (895 cz Kamenicky, ..)import dbf
from dbf_read_iffy import fix_init, fix_895

fix_init(dbf)
t = dbf.Table('autori.dbf')
t.open('read-only')
for record in t:
    print fix_895(record.autor)
t.close()You can ignore Python 2.7 installation error in test_v3.py (from aenum
which is requirement of dbf).For 620 pl Mazovia: You can define conversion map in fix_620(). If
possible please: Fork me, clone your fork, commit/push, generate Pull
request from your fork. Thx.
Package: db-frostyfeet909
db_frostyfeet909Provides methods to work with a queue pool from SQL alchemy.Exampleimportdb_frostyfeet909asdbconnection=db.Connection('postgresql+psycopg2://{USERNAME}:{PASSWORD}@{IP}/{DATABASE}')connection.create_database()connection.execute_query("CREATE TABLE test (key INT PRIMARY KEY, value TEXT);")connection.execute_query("INSERT INTO test (key, value) VALUES (1, 'first');")connection.execute_query("INSERT INTO test (key, value) VALUES (2, 'second');")first_key={"key":1}first_value=connection.execute_query_result_single("SELECT value FROM test WHERE key = :key LIMIT 1;",first_key)["value"]print("The first value is:{0}".format(first_value))
Package: dbf-to-sqlite
dbf-to-sqliteCLI tool for converting DBF files (dBase, FoxPro etc) to SQLite.$ dbf-to-sqlite --help
Usage: dbf-to-sqlite [OPTIONS] DBF_PATHS... SQLITE_DB

  Convert DBF files (dBase, FoxPro etc) to SQLite

  https://github.com/simonw/dbf-to-sqlite

Options:
  --version      Show the version and exit.
  --table TEXT   Table name to use (only valid for single files)
  -v, --verbose  Show what's going on
  --help         Show this message and exit.Example usage:$ dbf-to-sqlite *.DBF database.dbThis will create a new SQLite database calleddatabase.dbcontaining one table for each of theDBFfiles in the current directory.Looking for DBF files to try this out on? Try downloading theHimalayan Databaseof all expeditions that have climbed in the Nepal Himalaya.
Package: dbfwrite
Package name: dbfwriteAuthor: Wenyu LiEmail:vanelwy@gmail.comUrl:https://github.com/vanelwyVersion: 0.1Reference code source:http://code.activestate.com/recipes/362715-dbf-reader-and-writer/Function: convert dataframe into dbf fileimport package: from dbfwrite import dftodbfFunction: dftodbf.dbfwrite(df,dbffilepath)df:dataframe
dbffilepath: the filename and path you want to save dataframe as dbf file
Package: dbgclient
dbgclientdbgclientis a simple module that can help you to make bot HTTP API requests.
Currently supportGET and POSTmethod only, please pay attention currently this module ispre-releaseso is under development.GET and POSTI think enought to your build API bot.
In the future this module may can added some HTTP requests method likePUT, PATCH, DELETE or CUSTOMdefined by your choice :) .
So you guys I hope you can enjoy by this first time release, some feature are described belowFeatureIndonesian Fake DataGET or POST support HTML Inspector by CSS SelectorStorage Utils (append, write)Class MethodDbgHttp and BaseClientThis method to make new client of http client request.UsagefromdbgidimportDbgHttp,BaseClient#ClientBase Exampleclient=BaseClient('url here',verbose=False)print(client._get({}))"""Note BaseClient are same attribute with DbgHttp.To call DbgHttp must use with, For BaseClient is not require with"""withDbgHttp('url here',verbose=False)asclient:#get methodclient._get(headers={'accept':'*/*})#post method support output json/htmlclient._post({'accept':'*/*','content-type':'application/x-www-form-urlencoded'},{'body':'this is body string'},json=False)#get text element by css class, support span,p,divclient._get_text_element_by_class('html content','span','class-text')#get input value by nameclient._get_input_value_by_name('html content','email')#get input value by idclient._get_input_value_by_id('html content','email')#json post dataclient.__post_json({'accept':'application/json'},{'key':'value'})dbgStorageThis method for save data to local storageUsagefromdbgidimportdbgStorage#save append filedbgStorage.save('filename.txt','a','string to save')#read filedbgStorage.read('filename.txt')#read as binarydbgStorage.readBinary('filename.txt')#read file each linedbgStorage.readLine('filename.txt')#read json filedbgStorage.readJson('filename.json')dbgFakerThis method can generate indonesian data fakeUsagefromdbgidimportdbgFakerfake=dbgFaker()print(fake.getData())#return dict dataInsyallah in next update will rich feature added soon.
If you have bug issues don't hestitate to tell me guys
Package: dbgcode
dbgcode: Write debug code with confidencedbgcode is a python package that make it easyto remove debug code after you finish debuggingInstallation------------.. code-block:: bash$ pip install dbgcodeQuick Start-----------example usage:file: f.py.. code-block:: pythonx = []for i in range(1, 100):for j in range(1, 100):# dbgprint("i", i)print("j", j)# /dbgif i % 3 == 0 and j % 3 == 0:print("(i, j) ", (i, j))  # _dbgx.append((i, j))save this file and then in the command line.. code-block:: bash$ dbgcode clean f.pythe result is:.. code-block:: pythonx = []for i in range(1, 100):for j in range(1, 100):if i % 3 == 0 and j % 3 == 0:x.append((i, j))LICENSE-------**MIT**