Saravanan666/pypi-org huggingface dataset:
Package: db_backup
This holds the necessary code to use existing database dump tools with gpg to
create a full backup of a disk in an encrypted format that can sit on disk more
safely than just a text dump of that database.This library was originally created forRatticWebwhich made the decision
to not handle encryption within the application itself (encryption is difficult).UsageThere are two commands of importance in this library.db_backup.commands.backup(database_settings, recipients, backup_dir, gpg_home=None)This will dump the database as specified bydatabase_settingsand create a gpg encrypted file inside the specifiedbackup_dir(using thegpg_homeif specified, otherwise whatever the gpg binary
on your system wants to use) that can only be decrypted by
the specifiedrecipients.database_settingsis a dictionary of{name, engine, port, host, user, password}where all values exceptnameandengineare optional.engineis one ofsqlite3,psqlormysqlor the names of
the equivalent backends indjango.db.backends(i.e. django database
dictionary is fine)recipientsis a list of strings where each string is the uid for
a key in your gpg homedir.db_backup.commands.restore(database_settings, restore_from, gpg_home=None)This will take the gpg encrypted file atrestore_from, decrypt it
and feed the specified database with it.database_settingsandgpg_homebehave like they do for the
backup command.restore_fromis just the filepath to the encrypted backup file.InstallationUse pip!:pipinstalldb_backupOr if you’re developing it:pipinstall-e.pipinstall-e".[tests]"TestsRun the helpful script:./test.shOr if you’re outside a virtualenv and want to test with old pythons as well:tox
Package: dbbackup-tools
dbbackup-toolsTool to create a new dbbackup folderpip install dbbackupdbbackup-tools is instaled with dbbackup dependenciesRun it:pythonimport dbbackup_tools.utilEnter your folder name to hold dbbackup configurationcd to your new dbbackup folderConfiguration:ajust the file .env to match your local configrationTo logging on smtp, rename and adjust:loggin_config_example.yaml to loggin_config.yamlTo backup Mysql databases, rename and adjust:mysql-backup-script_example.config to mysql-backup-script.configWork with it:pythonimport dbbackupfrom dbbackup import check_dbbackup
Package: dbbs-models
dbbs-modelsCollection of neuron models for the NEURON simulator.CitationsIf you use our models for any scientific works you're required to cite the following papers:Granule cell modelMasoli, S., Tognolina, M., Laforenza, U., Moccia, F., and D’Angelo, E. (2020). Parameter tuning differentiates granule cell subtypes enriching transmission properties at the cerebellum input stage. Commun. Biol. 3, 222. doi:10.1038/s42003-020-0953-x.Golgi cell modelMasoli, S., Ottaviani, A., Casali, S., and D’Angelo, E. (2020). Cerebellar Golgi cell models predict dendritic processing and mechanisms of synaptic plasticity. PLoS Comput. Biol. 16, 1–27. doi:10.1371/journal.pcbi.1007937.Stellate cell modelRizza, M. F., Locatelli, F., Masoli, S., Sánchez-Ponce, D., Muñoz, A., Prestori, F., et al. (2021). Stellate cell computational modeling predicts signal filtering in the molecular layer circuit of cerebellum. Sci. Rep. 11, 3873. doi:10.1038/s41598-021-83209-w.Purkinje cell modelMasoli, S., Solinas, S., and D’Angelo, E. (2015). Action potential processing in a detailed Purkinje cell model reveals a critical role for axonal compartmentalization. Front. Cell. Neurosci. 9, 1–22. doi:10.3389/fncel.2015.00047.Masoli, S., and D’Angelo, E. (2017). Synaptic Activation of a Detailed Purkinje Cell Model Predicts Voltage-Dependent Control of Burst-Pause Responses in Active Dendrites. Front. Cell. Neurosci. 11, 1–18. doi:10.3389/fncel.2017.00278.
Package: dbbs-scaffold
Note:The scaffold framework is still under heavy development. Please check theKnown Issuessection at the bottom for important issues that fell victim to our
deadlines and will be solved at a later date.Scaffold: A scaffold model for the cerebellumThis package is intended to facilitate spatially, topologically and morphologically
detailed simulations of the cerebellum developed by the Department of Brain and Behavioral
Sciences at the University of Pavia.InstallationpipThis software can be installed as a Python package from PyPI through pip:sudo apt-get python3-rtree
 pip install dbbs-scaffoldNote:Windows users will have to install Rtree from this website:https://www.lfd.uci.edu/~gohlke/pythonlibs/#rtreeDevelopersDevelopers best use pip'seditableinstall. This creates a live link between the
installed package and the local git repository:sudo apt-get install python3-rtree
 git clone git@github.com:Helveg/cerebellum-scaffold.git
 cd cerebellum-scaffold
 pip install -e .[dev] --no-use-pep517
 pre-commit installUsageThe scaffold model can be used through the command line interface or as a python package.Command line interface (CLI)Run the scaffold in the command line with subcommandcompileto compile a network
architecture.scaffold --config=mouse_cerebellum.json compile -x=200 -y=200 -pTo run with different configurations, change the config argument to the relative path of a
.json config file. The-pflag indicates that the compiled network should be plotted
afterwards and can be omitted.Python packageThe central object is thescaffold.core.Scaffoldclass. This object requires ascaffold.config.ScaffoldConfiginstance for its construction. To emulate the CLI
functionality you can use theJSONConfigclass and provide the relative path to the
configuration file.fromscaffoldimportScaffoldfromscaffold.configimportJSONConfigconfig=newJSONConfig(file='mouse_cerebellum.json')scaffoldInstance=newScaffold(config)This scaffold instance can then be used to perform the subcommands available in the CLI by
calling their corresponding functions:scaffoldInstance.compile_network()Plotting network architectureAfter callingcompile_networkthe scaffold instance can be plotted:scaffoldInstance.plot_network_cache()Known issuesNo configuration serializationWhen modifying the config object through scripts and then saving it to file, you'll store
the original configuration file text, and you won't actually serialize the modified objectWe will fix this by version 3.2
Package: db-build
db-buildTools for building SQLite databases from files and directoriesInstallationInstall usingpiporpipx:pipinstalldb-buildIf you havesqlite-utilsinstalled as well, this will act as a plugin and add asqlite-utils buildcommand.Usagedb-buildcan build databases from a number of different flat file formats.It is always called with a SQLite database as the first argument, which can be a file that does not exist yet.Any subsequent arguments will be treated as files or directories that should be loaded into that database.A simple initial example, adding all CSV files in the current directory:db-builddata.db*.csvDevelopmentTo set up this plugin locally, first checkout the code. Then create a new virtual environment:cddb-build
python3-mvenvvenvsourcevenv/bin/activateNow install the dependencies and test dependencies:pipinstall-e'.[test]'To run the tests:pytest
Package: dbcache
DBCACHEThis small library provides small and simple stores based on
postgresql for the following purposes:a cache store for bytes with an expiration timestampa key-value store with json serializable valuesa versioned key-value store with values as bytesTo initialize the database schema, type:$dbcacheinit-dbpostgresql://foo:bar@postgresql/mydbExample usage (cache):fromtimeimportsleepfromdatetimeimporttimedeltafromdbcache.apiimportdbcachecache=dbcache('postgresql://foo:bar@postgresql/mydb')assertcache.get('a')isNonecache.set('a',b'aaa')assertcache.get('a')==b'aaa'cache.delete('a')assertcache.get('a')isNonecache.set('b',b'bbb',lifetime=timedelta(seconds=1))assertcache.get('b')==b'bbb'sleep(1)assertcache.get('b')isNoneExample usage (key/value store):fromdbcache.apiimportkvstorestore=kvstore('postgresql://foo:bar@postgresql/mydb')assertstore.get('a')isNonestore.set('a','aaa')assertstore.get('a')=='aaa'store.set('a','newvalue')assertstore.get('a')=='newvalue'store.delete('a')assertstore.get('a')isNonestore.set('int',42)assertstore.get('int')==42store.set('float',42.0)store.set('dict',{'a':[1,2]})assertstore.all()=={'dict':{'a':[1,2]},'float':42.0,'int':42}assertstore.keys()==['dict','float','int']Example usage (versioned key/value store):fromdbcache.apiimportvkvstorevstore=vkvstore('postgresql://foo:bar@postgresql/mydb')assertvstore.get('html')isNonev1=datetime(2023,1,1,12,30,tzinfo=timezone.utc)vstore.set('html',b'<html></html>',insertion_date=v1)assertvstore.get('html')==b'<html></html>'v2=datetime(2023,1,2,12,30,tzinfo=timezone.utc)vstore.set('html',b'<html>Hello, World</html>',insertion_date=v2)assertvstore.get('html')==b'<html>Hello, World</html>'assertvstore.get('html',insertion_date=v1)==b'<html></html>'assertvstore.versions('html')==[v1,v2]assertvstore.versions('nope')==[]vstore.delete('html')assertvstore.keys()==[]assertvstore.get('html')isNone
Package: db_cache
DB Cachedatabase caching for dynamic programmingFree software: MIT licenseDocumentation:https://db-cache.readthedocs.io.IntroGuideTL;DRimportdb_cache# Instantiate cache object that connects to PostgreSQL with provided credentialcache=db_cache.Cache(database="db_name",user="admin",password="12345",host="localhost")# Create decorater that cache function result using provided table name@cache.use_table("some_table_name")defsome_expensive_function(large_int):prime1,prime2=factoring(large_int)return(prime1,prime2)# Return cached value if possible, otherwise compute and cache result.some_expensive_function(121103)FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2016-11-04)First release on PyPI.
Package: dbcalc
Conversion tool to do power <-> dB calculations. PARAMS is a list of space-separated values depending
on the mode (i,oord) selected.i— calculate input power from the PARAMS output power and dBo— calculate output power from the PARAMS input power and dBd— calculate dB from the PARAMS output power and input powerE.g.: to calculate the output power, given 1W of input power and 3dB loss$dbcalco1-30.5011872336272722Notice that the result has a newline character appended.
Package: dbcAnalyzer
dbcAnalyzerdbc解析工具
##Information/说明
Hey, this is a analyzer to get what you want in a dbc file:通过使用dbc解析工具，你可以在一个dbc文件中获取到：·a dbc file's versiondbc文件的版本·all nodes,messages or signals in a dbc file;dbc文件下的所有节点名称、报文名称、信号名称·a message's ID, Size, Transmitter or it's signals;获取某一帧报文的ID,Size,Transmitter·a signal's Value Table, Size, StartBit, Factor, OffSet, Min/Max value;获取某个信号的Value Table,Size,起始位，精度，偏移量，最小/最大值Installation / 安装Get dbcAnalyzer by pip(通过pip安装dbcAnalyzer)pip install dbcAnalyzerAPIs / 程序接口调用from dbcAnalyzer import dbc as db

dbc = db.DBC('your dbc file')  
version = dbc.getVersion()  # 获取dbc版本
message = dbc.getMessages()  # 获取报文
signal = dbc.getSignals()  # 获取信号
node = dbc.getNodes()  # 获取节点
messageID = dbc.getMsgID('message name')  # 获取报文ID  
messageSize = dbc.getMsgSize('message name')  # 获取报文Size
messageTransmitter = dbc.getMsgTransmitter('message name')  # 获取报文发送节点  
messageSignal = dbc.getMsgSignal('message name')  # 获取报文包含的信号
signalValue = dbc.getSigVal('signal name')  # 获取信号Value Table
signalSize = dbc.getSigSize('signal name')  # 获取信号Size
signalStartBit = dbc.getSigStrtBit('signal name')  # 获取信号起始位
signalFactor = dbc.getSigFac('signal name')  # 获取信号精度
signalOffSet = dbc.getSigOff('signal name')  # 获取信号偏移量
signalMin = dbc.getSigMin('signal name')  # 获取信号最小值
signalMax = dbc.getSigMax('signal name')  # 获取信号最大值

print(version,message,'...',signalMax)
Package: dbcat
Data Catalog for Databases and Data WarehousesOverviewdbcatscans and maintains metadata from all your databases and data warehouses.dbcatalso stores metadata generated by other data governance applications such asPIICatcherandLineage Engine.dbcatis typically used alongside other applications. It can also be used stand-alone to generate
a very simple data catalog using the CLI or API.dbcatstores the catalog in a Postgresql or SQLite database. By default, the catalog is stored in a SQLite
database in~/.config/tokern/catalog.dbThe catalog can be exported toDatahuborAmundsen. This is very
useful to export PII tags or column lineage generated by PIICatcher or Lineage Engine.
Checkdocumentation for detailed instructionsto set PII tags and
column-level lineage.Quick Startdbcatis distributed as a python application.python3 -m venv .env
source .env/bin/activate
pip install dbcat

dbcat catalog add-sqlite --name sample --path <path to sqlite db>
dbcat catalog scan --source-name sampleDocumentationFor advanced usage refer documentationCatalog Documentation.Supported TechnologiesThe following databases are supported:MySQL/MariadbPostgreSQLAWS RedshiftBigQuerySnowflakeAWS Athena
Package: dbca-utils
OverviewDBCA Django utility classes and functions.SSO Login MiddlewareThis will automatically login and create users using headers from an upstream proxy (REMOTE_USER and some others).
The logout view will redirect to a separate logout page which clears the SSO session.UsageAdddbca_utils.middleware.SSOLoginMiddlewaretosettings.MIDDLEWARE(after both ofdjango.contrib.sessions.middleware.SessionMiddlewareanddjango.contrib.auth.middleware.AuthenticationMiddleware.
Ensure thatAUTHENTICATION_BACKENDScontainsdjango.contrib.auth.backends.ModelBackend,
as this middleware depends on it for retrieving the logged in user for a session.
Note that the middleware will still work without it, but will reauthenticate the session
on every request, andrequest.user.is_authenticatedwon't work properly/will be false.Example:MIDDLEWARE = [
    ...,
    'django.contrib.sessions.middleware.SessionMiddleware',
    'django.contrib.auth.middleware.AuthenticationMiddleware',
    'dbca_utils.middleware.SSOLoginMiddleware'
    ...,
]Audit model mixinAuditMixinis an extension ofDjango.db.model.Modelthat adds a number of additional fields:creator - FK toAUTH_USER_MODEL, used to record the object creatormodifier - FK toAUTH_USER_MODEL, used to record who the object was last modified bycreated - a timestamp that is set on initial object savemodified - an auto-updating timestamp (on each object save)
Package: dbcc
Database connector for different DBs with same interface.Dbcc is SimplefromdbccimportMongoTableEnginedb=MongoTableEngine(URL,DB_NAME)collection=db["collection"]result=awaitcollection.create({"any":"entry"})print(result["id"])FeaturesIn processTo DoIn processLicensedbcc is aStepan Starovoitovopen source project,
distributed under the BSD license.
Package: dbc-editor
dbc-editorAn editor for CAN bus database files like dbc or sym,
based oncantoolsandurwid.UsagePass the file that you want to open as command line argument.
You can also pass the name of a not existing file in order to create a new file.When you open the program a list of all messages defined in the passed file is displayed.
If it is a new file this list is empty.How to navigate in the list view:'arrow up' / 'arrow down' to select a message'G'/'_' to jump to last/first line'arrow right' to display the signals of the currently selected message'arrow left' to return from the list of signals to the list of messages'i' to edit the selected message (if you are in the list of messages) / signal (if you are in the list of signals)'v' to get a visualization of the message layout'+' to create a new message/signal'-' to delete the selected message/signal'w' to write/save'q' to quit'1' if you are in the list of messages: sort by message id'2' if you are in the list of messages: sort by message name'0' if you are in the list of messages: sort by the order how they appear in the dbc fileHow to navigate in the edit view:'arrow up' / 'arrow down' to select the entry field'arrow left' / 'arrow right' to select a radio button.
Be careful to not press these buttons too often:If you are on the left most position, pressing 'arrow left' returns to the list view. If you have made changes it will ask you whether you want to save the changes. You can press 'escape' in this dialog to return to the edit view.If you are on the right most position, pressing 'arrow right' saves the changes and returns to the list view. (Same like 'enter')Maybe I will change this in the future but this does not have a priority.'enter' to save changes and return to the list of messages/signals'escape' to discard changes and return to the list of messages/signalsInstallation$ pipx install dbc-editorTODOMissing message attributes:senderssend_typecycle_timeMissing signal attributes:initialminimummaximum
Package: dbcfg
dbconn项目目的把数据库连接信息独立出来，放在一个专用的配置目录下。可以提供以下好处：代码中不再包含连接信息，方便做到开发和运维分离。代码中没有连接信息，也提高了安全性，避免不小心分发出去的代码泄露了秘密。后续数据库变换地址、连接方式、修改密码不再需要调整源代码，直接修改配置即可。同一份源代码，无须变动，即可适应生产、测试环境。数据库定期修改密码时，仅需要改动少量配置文件。一些特性支持不同的语言，初期支持python、c快速入门安装使用pip install dbconn即可下载安装
Package: dbcl
dbcl - Database Command LineAn engine-agnostic database command line interface.InstallationUsepipto install the dbcl tool:pip install dbclAlso install the necessary packages for your database, for example:cx_Oracle,pg8000orPyMySQL.Database connectionDatabase connections are specified usingSQLAlchemy database URLs. The database URL can be given as an argument to thedbclcommand:dbcl sqlite:///database.dbIf the URL isn't given as an argument, a prompt will ask for the URL to use for the connection:$ dbcl
Connect to [sqlite:///database.db]:If the DATABASE_URL environmental variable is set, that value will be the default for the database prompt:$ export DATABASE_URL=sqlite:///database.db
$ dbcl
Connect to [sqlite:///database.db]:Example of a connection to a PostgreSQL database using whtpg8000package:dbcl postgresql+pg8000://username:password@127.0.0.1:5432/dbname
Package: dbclientpy
DBClientAn easy-to-use, flexible, and fast client for reading, writing, and manging your local database.UsagefromdbclientimportCollection,Documentdb=Collection('/path/to/db')users=db['users']# Creates a ghost collection; Will be created when sub-document is writtenusers['johndoe']={'name':'Jhon Doe','age':26,'email':johndoe@example.com'} # Creates a document with contents
Package: dbcli-mongo-redis
dbclidbcli provides lightweight utilities set for basic CRUD operations for MongoDB and Redis.With mcli You can access mongo documents for create and edit operations using your favourite text editor. It validates document and performs add and update operations.rcli provides similar interface for Redis DB. You are able to edit strings(bytes), lists and hashs with json-like syntax in your text editor.$EDITOR is used for bash. For Windows OS notepad or other windows editor.DataBase cli utilitiesmcli - Mongo client based on pymongorcli - Redis client based on pyredisInstallationpipinstalldbcli-mongo-redismcli usage examplesmclilist-dbs
mclilist-cols-dbooks
mcli-dbooks-cauthorslist-docs
mcli-dbooks-cauthorslist-docs-f'{"Language":"Chinese"}'mcli-daws-cimagesshow-doc-iami-eede2314
mcli--databaseaws--collectionimagesshow-doc-iami-eede2314
mcli--databaseaws--collectionimagesshow-doc--document-idami-eede2314
mcli-dgcloud-celementsshow-doc-o5ef869cf316dd267c64be59c
mcli-dgcloud-celementsshow-doc--document-object-id5ef869cf316dd267c64be59c
mcli-ddevops-cnewcoledit-doc-o5ef865fceb8e7562e8eaf9f6
mcli-ddevops-cnewcoledit-doc-iobject-234
mcli-ddevops-cnewcoldel-doc-iobject-234
mcli-ddevops-cnewcoldel-doc-o5ef865fceb8e7562e8eaf9f6rcli usage examplesrclidb-count
rclilist-keys
rclilist-keys-pimage
rclishow-db
rclishow-db-kimage_325
rclishow-db-pimage_
rcliadd-data
rcliadd-key
rcliadd-key-thashrcliedit-doc-kimage_325
rclidel-doc-kimage_214
rclito-set-ksome_list
rclito-zset-ksome_hashInspired bydbcli.LimitationsShould avoid using in production and for huge amount of data. Since it's interactive tool it shouldn't be used for automatic updates of multiple docs.License & AuthorsAuthors: Rasul Osmanov, Artur KrasnykhCopyright (c) 2020, Rasul Osmanov

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.TODO- AWS DynamoDB client
- Google Cloud DataStore client
Package: dbcls
DbClsDbCls is a versatile client for multiple databases, enabling the editing and preservation of SQL queries in a file, and executing queries directly from the editor, thereby providing a convenient interface for data representation.Briefly, this application combines the kaa editor and the visidata data visualization tool.InstallationpipinstalldbclsRundbcls-H127.0.0.1-uuser-pmypasswd-Emysql-dmydbmydb.sqlHotkeysAlt + r - Execute query under cursor or selected textAlt + e - Show databases listAlt + t - Show tables listCtrl + q - QuitCtrl + s - Save fileOptions-H --hostHost to connect to-u --userUsername to connect as-p --passwordPassword to use when connecting to server-E --engineDatabase engine, options are: mysql, postgresql, clickhouse-d --databaseDatabase to use-P --portPort number to use for connection (optional)-e --encpassEncrypted with ssh-crypt passwordBugsSee github issues:https://github.com/Sets88/dbcls/issues
Package: dbcluster
dbcluster: Database Cluster Session ManagerKris Hardykris@abqsoft.comNOTE: This code is in early beta and is under active development.  Please use carefully until the code stabalizes into version 1.0 (target: May 2019)This database engine manager manages master/slave database connections and
session management.  This is useful for applications which need to manage sqlalchemy database engines and sessionmakers for master/slave database clusters.Example usage:importsqlalchemyfromdbclusterimportMasterSlaveManagermanager=MasterSlaveManager()# Set up the master(s)manager.append_master(sqlalchemy.create_engine('postgresql://127.0.0.1:5432'),orm=MasterSlaveManager.ORM_SQLALCHEMY)# Set up slavesmanager.append_slave(sqlalchemy.create_engine('postgresql://127.0.0.1:5433'),orm=MasterSlaveManager.ORM_SQLALCHEMY)manager.append_slave(sqlalchemy.create_engine('postgresql://127.0.0.1:5435'),orm=MasterSlaveManager.ORM_SQLALCHEMY)# Use the database sessionswithmanager.master_session_ctx()asdb_session:# Do something with the session ...db_session.commit()withmanager.slave_session_ctx()asdb_session:# Returns a random slave session# Do something with the session ...db_session.commit()withmanager.slave_session_ctx(0)asdb_session:# Returns a session to the first slave# Do something with the session ...db_session.commit()
Package: dbComm
dbCommAuthor:Alex Caviness (caviness2@llnl.gov)AboutdbComm is a module for integrating a Python codebase with MongoDB using the PyMongo library.
The methods contained are used to connect to a Mongo database and push/pull data.InstallingThe easiest method of installation is through using Pip.pip install -U git+https://github.com/LLNL/dbComm.gitIf you prefer, you can clone the repo using:git clone https://github.com/LLNL/dbComm.gitUsageTo use dbComm, create an instance of the class. This will attempt to connect to the database.
Upon successful connection, any of the methods can be used in the class to interact with the database.import dbComm
db = dbComm.Mongo('myServer')
print(myServer.getDBs())TroubleshootingIf when running the pip install, you get an error likeAttributeError: module 'enum' has no attribute 'IntFlag'(32-bit Python),run:pip uninstall enum34ContributingdbComm is an open source project and constantly evolving!
We welcome contributions via pull requests as well as questions, feature requests, or bug reports via issues.
Contact our team atcaviness2@llnl.govwith any questions.If you are not a developer at LLNL, you won't have permission to push new branches to the repository.
First, you should create a fork.
This will create your copy of the ATS repository and ensure you can push your changes up to GitHub and create PRs.LicenseLLNL-CODE-845190