Seahub | The Web End Of Seafile Server Written in Python

Introduction

Seahub is the web frontend for Seafile.

Preparation

Build and deploy Seafile server from source. See http://manual.seafile.com/build_seafile/server.html

Getting it

You can grab souce code from GitHub.

$ git clone git://github.com/haiwen/seahub.git

Set up a virtualenv to install dependencies locally:

$ virtualenv .virtualenv
$ . .virtualenv/bin/activate

Install python libraries by pip:

$ pip install -r requirements.txt

Configuration

Modify CCNET_CONF_DIR, SEAFILE_CENTRAL_CONF_DIR, SEAFILE_CONF_DIR and PYTHONPATH in setenv.sh.template to fit your path.

CCNET_CONF_DIR is the directory, that contains the ccnet socket (and formerly ccnet.conf).

Since 5.0 SEAFILE_CENTRAL_CONF_DIR contains most config files.

SEAFILE_CONF_DIR is the seafile-data directory (and formerly contained seafile.conf).

Run and Verify

Run as:

$ . .virtualenv/bin/activate
$ ./run-seahub.sh.template

Then open your browser, and input http://localhost:8000/, there should be a Login page. You can create admin account using seahub-admin.py script under tools/ directory.

Internationalization (I18n)

Please refer to https://github.com/haiwen/seafile/wiki/Seahub-Translation

Download Details:
Author: haiwen
Source Code: https://github.com/haiwen/seahub
License: Unknown, Unknown licenses found

#python

A Simple Wrapper Around Amplify AppSync Simulator

This serverless plugin is a wrapper for amplify-appsync-simulator made for testing AppSync APIs built with serverless-appsync-plugin.

Install

npm install serverless-appsync-simulator
# or
yarn add serverless-appsync-simulator

Usage

This plugin relies on your serverless yml file and on the serverless-offline plugin.

plugins:
  - serverless-dynamodb-local # only if you need dynamodb resolvers and you don't have an external dynamodb
  - serverless-appsync-simulator
  - serverless-offline

Note: Order is important serverless-appsync-simulator must go before serverless-offline

To start the simulator, run the following command:

sls offline start

You should see in the logs something like:

...
Serverless: AppSync endpoint: http://localhost:20002/graphql
Serverless: GraphiQl: http://localhost:20002
...

Configuration

Put options under custom.appsync-simulator in your serverless.yml file

| option | default | description | | ------------------------ | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | apiKey | 0123456789 | When using API_KEY as authentication type, the key to authenticate to the endpoint. | | port | 20002 | AppSync operations port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20002, 20012, 20022, etc.) | | wsPort | 20003 | AppSync subscriptions port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20003, 20013, 20023, etc.) | | location | . (base directory) | Location of the lambda functions handlers. | | refMap | {} | A mapping of resource resolutions for the Ref function | | getAttMap | {} | A mapping of resource resolutions for the GetAtt function | | importValueMap | {} | A mapping of resource resolutions for the ImportValue function | | functions | {} | A mapping of external functions for providing invoke url for external fucntions | | dynamoDb.endpoint | http://localhost:8000 | Dynamodb endpoint. Specify it if you're not using serverless-dynamodb-local. Otherwise, port is taken from dynamodb-local conf | | dynamoDb.region | localhost | Dynamodb region. Specify it if you're connecting to a remote Dynamodb intance. | | dynamoDb.accessKeyId | DEFAULT_ACCESS_KEY | AWS Access Key ID to access DynamoDB | | dynamoDb.secretAccessKey | DEFAULT_SECRET | AWS Secret Key to access DynamoDB | | dynamoDb.sessionToken | DEFAULT_ACCESS_TOKEEN | AWS Session Token to access DynamoDB, only if you have temporary security credentials configured on AWS | | dynamoDb.* | | You can add every configuration accepted by DynamoDB SDK | | rds.dbName | | Name of the database | | rds.dbHost | | Database host | | rds.dbDialect | | Database dialect. Possible values (mysql | postgres) | | rds.dbUsername | | Database username | | rds.dbPassword | | Database password | | rds.dbPort | | Database port | | watch | - *.graphql
- *.vtl | Array of glob patterns to watch for hot-reloading. |

Example:

custom:
  appsync-simulator:
    location: '.webpack/service' # use webpack build directory
    dynamoDb:
      endpoint: 'http://my-custom-dynamo:8000'

Hot-reloading

By default, the simulator will hot-relad when changes to *.graphql or *.vtl files are detected. Changes to *.yml files are not supported (yet? - this is a Serverless Framework limitation). You will need to restart the simulator each time you change yml files.

Hot-reloading relies on watchman. Make sure it is installed on your system.

You can change the files being watched with the watch option, which is then passed to watchman as the match expression.

e.g.

custom:
  appsync-simulator:
    watch:
      - ["match", "handlers/**/*.vtl", "wholename"] # => array is interpreted as the literal match expression
      - "*.graphql"                                 # => string like this is equivalent to `["match", "*.graphql"]`

Or you can opt-out by leaving an empty array or set the option to false

Note: Functions should not require hot-reloading, unless you are using a transpiler or a bundler (such as webpack, babel or typescript), un which case you should delegate hot-reloading to that instead.

Resource CloudFormation functions resolution

This plugin supports some resources resolution from the Ref, Fn::GetAtt and Fn::ImportValue functions in your yaml file. It also supports some other Cfn functions such as Fn::Join, Fb::Sub, etc.

Note: Under the hood, this features relies on the cfn-resolver-lib package. For more info on supported cfn functions, refer to the documentation

Basic usage

You can reference resources in your functions' environment variables (that will be accessible from your lambda functions) or datasource definitions. The plugin will automatically resolve them for you.

provider:
  environment:
    BUCKET_NAME:
      Ref: MyBucket # resolves to `my-bucket-name`

resources:
  Resources:
    MyDbTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: myTable
      ...
    MyBucket:
      Type: AWS::S3::Bucket
      Properties:
        BucketName: my-bucket-name
    ...

# in your appsync config
dataSources:
  - type: AMAZON_DYNAMODB
    name: dynamosource
    config:
      tableName:
        Ref: MyDbTable # resolves to `myTable`

Override (or mock) values

Sometimes, some references cannot be resolved, as they come from an Output from Cloudformation; or you might want to use mocked values in your local environment.

In those cases, you can define (or override) those values using the refMap, getAttMap and importValueMap options.

refMap takes a mapping of resource name to value pairs
getAttMap takes a mapping of resource name to attribute/values pairs
importValueMap takes a mapping of import name to values pairs

Example:

custom:
  appsync-simulator:
    refMap:
      # Override `MyDbTable` resolution from the previous example.
      MyDbTable: 'mock-myTable'
    getAttMap:
      # define ElasticSearchInstance DomainName
      ElasticSearchInstance:
        DomainEndpoint: 'localhost:9200'
    importValueMap:
      other-service-api-url: 'https://other.api.url.com/graphql'

# in your appsync config
dataSources:
  - type: AMAZON_ELASTICSEARCH
    name: elasticsource
    config:
      # endpoint resolves as 'http://localhost:9200'
      endpoint:
        Fn::Join:
          - ''
          - - https://
            - Fn::GetAtt:
                - ElasticSearchInstance
                - DomainEndpoint

Key-value mock notation

In some special cases you will need to use key-value mock nottation. Good example can be case when you need to include serverless stage value (${self:provider.stage}) in the import name.

This notation can be used with all mocks - refMap, getAttMap and importValueMap

provider:
  environment:
    FINISH_ACTIVITY_FUNCTION_ARN:
      Fn::ImportValue: other-service-api-${self:provider.stage}-url

custom:
  serverless-appsync-simulator:
    importValueMap:
      - key: other-service-api-${self:provider.stage}-url
        value: 'https://other.api.url.com/graphql'

Limitations

This plugin only tries to resolve the following parts of the yml tree:

provider.environment
functions[*].environment
custom.appSync

If you have the need of resolving others, feel free to open an issue and explain your use case.

For now, the supported resources to be automatically resovled by Ref: are:

DynamoDb tables
S3 Buckets

Feel free to open a PR or an issue to extend them as well.

External functions

When a function is not defined withing the current serverless file you can still call it by providing an invoke url which should point to a REST method. Make sure you specify "get" or "post" for the method. Default is "get", but you probably want "post".

custom:
  appsync-simulator:
    functions:
      addUser:
        url: http://localhost:3016/2015-03-31/functions/addUser/invocations
        method: post
      addPost:
        url: https://jsonplaceholder.typicode.com/posts
        method: post

Supported Resolver types

This plugin supports resolvers implemented by amplify-appsync-simulator, as well as custom resolvers.

From Aws Amplify:

NONE
AWS_LAMBDA
AMAZON_DYNAMODB
PIPELINE

Implemented by this plugin

AMAZON_ELASTIC_SEARCH
HTTP
RELATIONAL_DATABASE

Relational Database

Sample VTL for a create mutation

#set( $cols = [] )
#set( $vals = [] )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #set( $discard = $cols.add("$toSnake") )
  #if( $util.isBoolean($ctx.args.input[$entry]) )
      #if( $ctx.args.input[$entry] )
        #set( $discard = $vals.add("1") )
      #else
        #set( $discard = $vals.add("0") )
      #end
  #else
      #set( $discard = $vals.add("'$ctx.args.input[$entry]'") )
  #end
#end
#set( $valStr = $vals.toString().replace("[","(").replace("]",")") )
#set( $colStr = $cols.toString().replace("[","(").replace("]",")") )
#if ( $valStr.substring(0, 1) != '(' )
  #set( $valStr = "($valStr)" )
#end
#if ( $colStr.substring(0, 1) != '(' )
  #set( $colStr = "($colStr)" )
#end
{
  "version": "2018-05-29",
  "statements":   ["INSERT INTO <name-of-table> $colStr VALUES $valStr", "SELECT * FROM    <name-of-table> ORDER BY id DESC LIMIT 1"]
}

Sample VTL for an update mutation

#set( $update = "" )
#set( $equals = "=" )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $cur = $ctx.args.input[$entry] )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #if( $util.isBoolean($cur) )
      #if( $cur )
        #set ( $cur = "1" )
      #else
        #set ( $cur = "0" )
      #end
  #end
  #if ( $util.isNullOrEmpty($update) )
      #set($update = "$toSnake$equals'$cur'" )
  #else
      #set($update = "$update,$toSnake$equals'$cur'" )
  #end
#end
{
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> SET $update WHERE id=$ctx.args.input.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.input.id"]
}

Sample resolver for delete mutation

{
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> set deleted_at=NOW() WHERE id=$ctx.args.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.id"]
}

Sample mutation response VTL with support for handling AWSDateTime

#set ( $index = -1)
#set ( $result = $util.parseJson($ctx.result) )
#set ( $meta = $result.sqlStatementResults[1].columnMetadata)
#foreach ($column in $meta)
    #set ($index = $index + 1)
    #if ( $column["typeName"] == "timestamptz" )
        #set ($time = $result["sqlStatementResults"][1]["records"][0][$index]["stringValue"] )
        #set ( $nowEpochMillis = $util.time.parseFormattedToEpochMilliSeconds("$time.substring(0,19)+0000", "yyyy-MM-dd HH:mm:ssZ") )
        #set ( $isoDateTime = $util.time.epochMilliSecondsToISO8601($nowEpochMillis) )
        $util.qr( $result["sqlStatementResults"][1]["records"][0][$index].put("stringValue", "$isoDateTime") )
    #end
#end
#set ( $res = $util.parseJson($util.rds.toJsonString($util.toJson($result)))[1][0] )
#set ( $response = {} )
#foreach($mapKey in $res.keySet())
    #set ( $s = $mapKey.split("_") )
    #set ( $camelCase="" )
    #set ( $isFirst=true )
    #foreach($entry in $s)
        #if ( $isFirst )
          #set ( $first = $entry.substring(0,1) )
        #else
          #set ( $first = $entry.substring(0,1).toUpperCase() )
        #end
        #set ( $isFirst=false )
        #set ( $stringLength = $entry.length() )
        #set ( $remaining = $entry.substring(1, $stringLength) )
        #set ( $camelCase = "$camelCase$first$remaining" )
    #end
    $util.qr( $response.put("$camelCase", $res[$mapKey]) )
#end
$utils.toJson($response)

Using Variable Map

Variable map support is limited and does not differentiate numbers and strings data types, please inject them directly if needed.

Will be escaped properly: null, true, and false values.

{
  "version": "2018-05-29",
  "statements":   [
    "UPDATE <name-of-table> set deleted_at=NOW() WHERE id=:ID",
    "SELECT * FROM <name-of-table> WHERE id=:ID and unix_timestamp > $ctx.args.newerThan"
  ],
  variableMap: {
    ":ID": $ctx.args.id,
##    ":TIMESTAMP": $ctx.args.newerThan -- This will be handled as a string!!!
  }
}

Requires

serverless framework
serverless-appsync-plugin
serverless-offline
serverless-dynamodb-local (when using dynamodb resolvers only)
watchman (if Hot-reloading is desactivated it is not required)

Author: Serverless-appsync
Source Code: https://github.com/serverless-appsync/serverless-appsync-simulator
License: MIT License

#serverless #sync #graphql

Chesley Labadie

1648972740

Generis: Versatile Go Code Generator

Generis

Versatile Go code generator.

Description

Generis is a lightweight code preprocessor adding the following features to the Go language :

Generics.
Free-form macros.
Conditional compilation.
HTML templating.
Allman style conversion.

Sample

package main;

// -- IMPORTS

import (
    "html"
    "io"
    "log"
    "net/http"
    "net/url"
    "strconv"
    );

// -- DEFINITIONS

#define DebugMode
#as true

// ~~

#define HttpPort
#as 8080

// ~~

#define WriteLine( {{text}} )
#as log.Println( {{text}} )

// ~~

#define local {{variable}} : {{type}};
#as var {{variable}} {{type}};

// ~~

#define DeclareStack( {{type}}, {{name}} )
#as
    // -- TYPES

    type {{name}}Stack struct
    {
        ElementArray []{{type}};
    }

    // -- INQUIRIES

    func ( stack * {{name}}Stack ) IsEmpty(
        ) bool
    {
        return len( stack.ElementArray ) == 0;
    }

    // -- OPERATIONS

    func ( stack * {{name}}Stack ) Push(
        element {{type}}
        )
    {
        stack.ElementArray = append( stack.ElementArray, element );
    }

    // ~~

    func ( stack * {{name}}Stack ) Pop(
        ) {{type}}
    {
        local
            element : {{type}};

        element = stack.ElementArray[ len( stack.ElementArray ) - 1 ];

        stack.ElementArray = stack.ElementArray[ : len( stack.ElementArray ) - 1 ];

        return element;
    }
#end

// ~~

#define DeclareStack( {{type}} )
#as DeclareStack( {{type}}, {{type:PascalCase}} )

// -- TYPES

DeclareStack( string )
DeclareStack( int32 )

// -- FUNCTIONS

func HandleRootPage(
    response_writer http.ResponseWriter,
    request * http.Request
    )
{
    local
        boolean : bool;
    local
        natural : uint;
    local
        integer : int;
    local
        real : float64;
    local
        escaped_html_text,
        escaped_url_text,
        text : string;
    local
        integer_stack : Int32Stack;

    boolean = true;
    natural = 10;
    integer = 20;
    real = 30.0;
    text = "text";
    escaped_url_text = "&escaped text?";
    escaped_html_text = "<escaped text/>";

    integer_stack.Push( 10 );
    integer_stack.Push( 20 );
    integer_stack.Push( 30 );

    #write response_writer
        <!DOCTYPE html>
        <html lang="en">
            <head>
                <meta charset="utf-8">
                <title><%= request.URL.Path %></title>
            </head>
            <body>
                <% if ( boolean ) { %>
                    <%= "URL : " + request.URL.Path %>
                    <br/>
                    <%@ natural %>
                    <%# integer %>
                    <%& real %>
                    <br/>
                    <%~ text %>
                    <%^ escaped_url_text %>
                    <%= escaped_html_text %>
                    <%= "<%% ignored %%>" %>
                    <%% ignored %%>
                <% } %>
                <br/>
                Stack :
                <br/>
                <% for !integer_stack.IsEmpty() { %>
                    <%# integer_stack.Pop() %>
                <% } %>
            </body>
        </html>
    #end
}

// ~~

func main()
{
    http.HandleFunc( "/", HandleRootPage );

    #if DebugMode
        WriteLine( "Listening on http://localhost:HttpPort" );
    #end

    log.Fatal(
        http.ListenAndServe( ":HttpPort", nil )
        );
}

Syntax

#define directive

Constants and generic code can be defined with the following syntax :

#define old code
#as new code

#define old code
#as
    new
    code
#end

#define
    old
    code
#as new code

#define
    old
    code
#as
    new
    code
#end

#define parameter

The #define directive can contain one or several parameters :

{{variable name}} : hierarchical code (with properly matching brackets and parentheses)
{{variable name#}} : statement code (hierarchical code without semicolon)
{{variable name$}} : plain code
{{variable name:boolean expression}} : conditional hierarchical code
{{variable name#:boolean expression}} : conditional statement code
{{variable name$:boolean expression}} : conditional plain code

They can have a boolean expression to require they match specific conditions :

HasText text
HasPrefix prefix
HasSuffix suffix
HasIdentifier text
false
true
!expression
expression && expression
expression || expression
( expression )

The #define directive must not start or end with a parameter.

#as parameter

The #as directive can use the value of the #define parameters :

{{variable name}}
{{variable name:filter function}}
{{variable name:filter function:filter function:...}}

Their value can be changed through one or several filter functions :

LowerCase
UpperCase
MinorCase
MajorCase
SnakeCase
PascalCase
CamelCase
RemoveComments
RemoveBlanks
PackStrings
PackIdentifiers
ReplacePrefix old_prefix new_prefix
ReplaceSuffix old_suffix new_suffix
ReplaceText old_text new_text
ReplaceIdentifier old_identifier new_identifier
AddPrefix prefix
AddSuffix suffix
RemovePrefix prefix
RemoveSuffix suffix
RemoveText text
RemoveIdentifier identifier

#if directive

Conditional code can be defined with the following syntax :

#if boolean expression
    #if boolean expression
        ...
    #else
        ...
    #end
#else
    #if boolean expression
        ...
    #else
        ...
    #end
#end

The boolean expression can use the following operators :

false
true
!expression
expression && expression
expression || expression
( expression )

#write directive

Templated HTML code can be sent to a stream writer using the following syntax :

#write writer expression
    <% code %>
    <%@ natural expression %>
    <%# integer expression %>
    <%& real expression %>
    <%~ text expression %>
    <%= escaped text expression %>
    <%! removed content %>
    <%% ignored tags %%>
#end

Limitations

There is no operator precedence in boolean expressions.
The --join option requires to end the statements with a semicolon.
The #writer directive is only available for the Go language.

Installation

Install the DMD 2 compiler (using the MinGW setup option on Windows).

Build the executable with the following command line :

dmd -m64 generis.d

Command line

generis [options]

Options

--prefix # : set the command prefix
--parse INPUT_FOLDER/ : parse the definitions of the Generis files in the input folder
--process INPUT_FOLDER/ OUTPUT_FOLDER/ : reads the Generis files in the input folder and writes the processed files in the output folder
--trim : trim the HTML templates
--join : join the split statements
--create : create the output folders if needed
--watch : watch the Generis files for modifications
--pause 500 : time to wait before checking the Generis files again
--tabulation 4 : set the tabulation space count
--extension .go : generate files with this extension

Examples

generis --process GS/ GO/

Reads the Generis files in the GS/ folder and writes Go files in the GO/ folder.

generis --process GS/ GO/ --create

Reads the Generis files in the GS/ folder and writes Go files in the GO/ folder, creating the output folders if needed.

generis --process GS/ GO/ --create --watch

Reads the Generis files in the GS/ folder and writes Go files in the GO/ folder, creating the output folders if needed and watching the Generis files for modifications.

generis --process GS/ GO/ --trim --join --create --watch

Reads the Generis files in the GS/ folder and writes Go files in the GO/ folder, trimming the HTML templates, joining the split statements, creating the output folders if needed and watching the Generis files for modifications.

Version

2.0

Author: Senselogic
Source Code: https://github.com/senselogic/GENERIS
License: View license

#go #golang #code

Ray Patel

1625843760

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Shardul Bhatt

1626775355

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities.

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.

5 Reasons to Utilize Python for Programming Web Apps

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.

Simple to read and compose

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.

Utilized by the best

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.

Massive community support

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.

Progressive applications

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

Seahub | The Web End Of Seafile Server Written in Python

What is GEEK

Buddha Community

A Simple Wrapper Around Amplify AppSync Simulator

Basic usage

Override (or mock) values

Key-value mock notation

Limitations

Relational Database

Sample VTL for a create mutation

Sample VTL for an update mutation

Sample resolver for delete mutation

Sample mutation response VTL with support for handling AWSDateTime

Using Variable Map

Generis: Versatile Go Code Generator

Description

Sample

Syntax

#define directive

#define parameter

#as parameter

#if directive

#write directive

Limitations

Installation

Command line

Options

Examples

Version

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

Python Packages

Lambda, Map, Filter functions in python

Why use Python for Software Development

5 Reasons to Utilize Python for Programming Web Apps

Summary