Locust: Scalable User Load Testing tool Written in Python


Locust is an easy to use, scriptable and scalable performance testing tool. You define the behaviour of your users in regular Python code, instead of being constrained by a UI or domain specific language that only pretends to be real code. This makes Locust infinitely expandable and very developer friendly.

To get started right away, head over to the documentation.


Write user test scenarios in plain old Python

If you want your users to loop, perform some conditional behaviour or do some calculations, you just use the regular programming constructs provided by Python. Locust runs every user inside its own greenlet (a lightweight process/coroutine). This enables you to write your tests like normal (blocking) Python code instead of having to use callbacks or some other mechanism. Because your scenarios are “just python” you can use your regular IDE, and version control your tests as regular code (as opposed to some other tools that use XML or binary formats)

from locust import HttpUser, task, between

class QuickstartUser(HttpUser):
    wait_time = between(1, 2)

    def on_start(self):"/login", json={"username":"foo", "password":"bar"})

    def hello_world(self):

    def view_item(self):
        for item_id in range(10):
            self.client.get(f"/item?id={item_id}", name="/item")

Distributed & Scalable - supports hundreds of thousands of users

Locust makes it easy to run load tests distributed over multiple machines. It is event-based (using gevent), which makes it possible for a single process to handle many thousands concurrent users. While there may be other tools that are capable of doing more requests per second on a given hardware, the low overhead of each Locust user makes it very suitable for testing highly concurrent workloads.

Web-based UI

Locust has a user friendly web interface that shows the progress of your test in real-time. You can even change the load while the test is running. It can also be run without the UI, making it easy to use for CI/CD testing.

Locust UI charts Locust UI stats Locust UI workers Locust UI start test

Can test any system

Even though Locust primarily works with web sites/services, it can be used to test almost any system or protocol. Just write a client for what you want to test, or explore some created by the community.


Locust's code base is intentionally kept small and doesn't solve everything out of the box. Instead, we try to make it easy to adapt to any situation you may come across, using regular Python code. If you want to send reporting data to that database & graphing system you like, wrap calls to a REST API to handle the particulars of your system or run a totally custom load pattern, there is nothing stopping you!




Open source licensed under the MIT license (see LICENSE file for details).

Author: locustio
Source Code:
License: MIT License


What is GEEK

Buddha Community

Locust: Scalable User Load Testing tool Written in Python

Dotnet Script: Run C# Scripts From The .NET CLI

dotnet script

Run C# scripts from the .NET CLI, define NuGet packages inline and edit/debug them in VS Code - all of that with full language services support from OmniSharp.

NuGet Packages

dotnet-script (global tool)Nugetnet6.0, net5.0, netcoreapp3.1
Dotnet.Script (CLI as Nuget)Nugetnet6.0, net5.0, netcoreapp3.1
Dotnet.Script.CoreNugetnetcoreapp3.1 , netstandard2.0



The only thing we need to install is .NET Core 3.1 or .NET 5.0 SDK.

.NET Core Global Tool

.NET Core 2.1 introduced the concept of global tools meaning that you can install dotnet-script using nothing but the .NET CLI.

dotnet tool install -g dotnet-script

You can invoke the tool using the following command: dotnet-script
Tool 'dotnet-script' (version '0.22.0') was successfully installed.

The advantage of this approach is that you can use the same command for installation across all platforms. .NET Core SDK also supports viewing a list of installed tools and their uninstallation.

dotnet tool list -g

Package Id         Version      Commands
dotnet-script      0.22.0       dotnet-script
dotnet tool uninstall dotnet-script -g

Tool 'dotnet-script' (version '0.22.0') was successfully uninstalled.


choco install dotnet.script

We also provide a PowerShell script for installation.

(new-object Net.WebClient).DownloadString("") | iex

Linux and Mac

curl -s | bash

If permission is denied we can try with sudo

curl -s | sudo bash


A Dockerfile for running dotnet-script in a Linux container is available. Build:

cd build
docker build -t dotnet-script -f Dockerfile ..

And run:

docker run -it dotnet-script --version


You can manually download all the releases in zip format from the GitHub releases page.


Our typical helloworld.csx might look like this:

Console.WriteLine("Hello world!");

That is all it takes and we can execute the script. Args are accessible via the global Args array.

dotnet script helloworld.csx


Simply create a folder somewhere on your system and issue the following command.

dotnet script init

This will create main.csx along with the launch configuration needed to debug the script in VS Code.

├── .vscode
│   └── launch.json
├── main.csx
└── omnisharp.json

We can also initialize a folder using a custom filename.

dotnet script init custom.csx

Instead of main.csx which is the default, we now have a file named custom.csx.

├── .vscode
│   └── launch.json
├── custom.csx
└── omnisharp.json

Note: Executing dotnet script init inside a folder that already contains one or more script files will not create the main.csx file.

Running scripts

Scripts can be executed directly from the shell as if they were executables.

foo.csx arg1 arg2 arg3


Just like all scripts, on OSX/Linux you need to have a #! and mark the file as executable via chmod +x foo.csx. If you use dotnet script init to create your csx it will automatically have the #! directive and be marked as executable.

The OSX/Linux shebang directive should be #!/usr/bin/env dotnet-script

#!/usr/bin/env dotnet-script
Console.WriteLine("Hello world");

You can execute your script using dotnet script or dotnet-script, which allows you to pass arguments to control your script execution more.

foo.csx arg1 arg2 arg3
dotnet script foo.csx -- arg1 arg2 arg3
dotnet-script foo.csx -- arg1 arg2 arg3

Passing arguments to scripts

All arguments after -- are passed to the script in the following way:

dotnet script foo.csx -- arg1 arg2 arg3

Then you can access the arguments in the script context using the global Args collection:

foreach (var arg in Args)

All arguments before -- are processed by dotnet script. For example, the following command-line

dotnet script -d foo.csx -- -d

will pass the -d before -- to dotnet script and enable the debug mode whereas the -d after -- is passed to script for its own interpretation of the argument.

NuGet Packages

dotnet script has built-in support for referencing NuGet packages directly from within the script.

#r "nuget: AutoMapper, 6.1.0"


Note: Omnisharp needs to be restarted after adding a new package reference

Package Sources

We can define package sources using a NuGet.Config file in the script root folder. In addition to being used during execution of the script, it will also be used by OmniSharp that provides language services for packages resolved from these package sources.

As an alternative to maintaining a local NuGet.Config file we can define these package sources globally either at the user level or at the computer level as described in Configuring NuGet Behaviour

It is also possible to specify packages sources when executing the script.

dotnet script foo.csx -s https://SomePackageSource

Multiple packages sources can be specified like this:

dotnet script foo.csx -s https://SomePackageSource -s https://AnotherPackageSource

Creating DLLs or Exes from a CSX file

Dotnet-Script can create a standalone executable or DLL for your script.

SwitchLong switchdescription
-o--outputDirectory where the published executable should be placed. Defaults to a 'publish' folder in the current directory.
-n--nameThe name for the generated DLL (executable not supported at this time). Defaults to the name of the script.
 --dllPublish to a .dll instead of an executable.
-c--configurationConfiguration to use for publishing the script [Release/Debug]. Default is "Debug"
-d--debugEnables debug output.
-r--runtimeThe runtime used when publishing the self contained executable. Defaults to your current runtime.

The executable you can run directly independent of dotnet install, while the DLL can be run using the dotnet CLI like this:

dotnet script exec {path_to_dll} -- arg1 arg2


We provide two types of caching, the dependency cache and the execution cache which is explained in detail below. In order for any of these caches to be enabled, it is required that all NuGet package references are specified using an exact version number. The reason for this constraint is that we need to make sure that we don't execute a script with a stale dependency graph.

Dependency Cache

In order to resolve the dependencies for a script, a dotnet restore is executed under the hood to produce a project.assets.json file from which we can figure out all the dependencies we need to add to the compilation. This is an out-of-process operation and represents a significant overhead to the script execution. So this cache works by looking at all the dependencies specified in the script(s) either in the form of NuGet package references or assembly file references. If these dependencies matches the dependencies from the last script execution, we skip the restore and read the dependencies from the already generated project.assets.json file. If any of the dependencies has changed, we must restore again to obtain the new dependency graph.

Execution cache

In order to execute a script it needs to be compiled first and since that is a CPU and time consuming operation, we make sure that we only compile when the source code has changed. This works by creating a SHA256 hash from all the script files involved in the execution. This hash is written to a temporary location along with the DLL that represents the result of the script compilation. When a script is executed the hash is computed and compared with the hash from the previous compilation. If they match there is no need to recompile and we run from the already compiled DLL. If the hashes don't match, the cache is invalidated and we recompile.

You can override this automatic caching by passing --no-cache flag, which will bypass both caches and cause dependency resolution and script compilation to happen every time we execute the script.

Cache Location

The temporary location used for caches is a sub-directory named dotnet-script under (in order of priority):

  1. The path specified for the value of the environment variable named DOTNET_SCRIPT_CACHE_LOCATION, if defined and value is not empty.
  2. Linux distributions only: $XDG_CACHE_HOME if defined otherwise $HOME/.cache
  3. macOS only: ~/Library/Caches
  4. The value returned by Path.GetTempPath for the platform.



The days of debugging scripts using Console.WriteLine are over. One major feature of dotnet script is the ability to debug scripts directly in VS Code. Just set a breakpoint anywhere in your script file(s) and hit F5(start debugging)


Script Packages

Script packages are a way of organizing reusable scripts into NuGet packages that can be consumed by other scripts. This means that we now can leverage scripting infrastructure without the need for any kind of bootstrapping.

Creating a script package

A script package is just a regular NuGet package that contains script files inside the content or contentFiles folder.

The following example shows how the scripts are laid out inside the NuGet package according to the standard convention .

└── contentFiles
    └── csx
        └── netstandard2.0
            └── main.csx

This example contains just the main.csx file in the root folder, but packages may have multiple script files either in the root folder or in subfolders below the root folder.

When loading a script package we will look for an entry point script to be loaded. This entry point script is identified by one of the following.

  • A script called main.csx in the root folder
  • A single script file in the root folder

If the entry point script cannot be determined, we will simply load all the scripts files in the package.

The advantage with using an entry point script is that we can control loading other scripts from the package.

Consuming a script package

To consume a script package all we need to do specify the NuGet package in the #loaddirective.

The following example loads the simple-targets package that contains script files to be included in our script.

#load "nuget:simple-targets-csx, 6.0.0"

using static SimpleTargets;
var targets = new TargetDictionary();

targets.Add("default", () => Console.WriteLine("Hello, world!"));

Run(Args, targets);

Note: Debugging also works for script packages so that we can easily step into the scripts that are brought in using the #load directive.

Remote Scripts

Scripts don't actually have to exist locally on the machine. We can also execute scripts that are made available on an http(s) endpoint.

This means that we can create a Gist on Github and execute it just by providing the URL to the Gist.

This Gist contains a script that prints out "Hello World"

We can execute the script like this

dotnet script

That is a pretty long URL, so why don't make it a TinyURL like this:

dotnet script

Script Location

A pretty common scenario is that we have logic that is relative to the script path. We don't want to require the user to be in a certain directory for these paths to resolve correctly so here is how to provide the script path and the script folder regardless of the current working directory.

public static string GetScriptPath([CallerFilePath] string path = null) => path;
public static string GetScriptFolder([CallerFilePath] string path = null) => Path.GetDirectoryName(path);

Tip: Put these methods as top level methods in a separate script file and #load that file wherever access to the script path and/or folder is needed.


This release contains a C# REPL (Read-Evaluate-Print-Loop). The REPL mode ("interactive mode") is started by executing dotnet-script without any arguments.

The interactive mode allows you to supply individual C# code blocks and have them executed as soon as you press Enter. The REPL is configured with the same default set of assembly references and using statements as regular CSX script execution.

Basic usage

Once dotnet-script starts you will see a prompt for input. You can start typing C# code there.

~$ dotnet script
> var x = 1;
> x+x

If you submit an unterminated expression into the REPL (no ; at the end), it will be evaluated and the result will be serialized using a formatter and printed in the output. This is a bit more interesting than just calling ToString() on the object, because it attempts to capture the actual structure of the object. For example:

~$ dotnet script
> var x = new List<string>();
> x.Add("foo");
> x
List<string>(1) { "foo" }
> x.Add("bar");
> x
List<string>(2) { "foo", "bar" }

Inline Nuget packages

REPL also supports inline Nuget packages - meaning the Nuget packages can be installed into the REPL from within the REPL. This is done via our #r and #load from Nuget support and uses identical syntax.

~$ dotnet script
> #r "nuget: Automapper, 6.1.1"
> using AutoMapper;
> typeof(MapperConfiguration)
> #load "nuget: simple-targets-csx, 6.0.0";
> using static SimpleTargets;
> typeof(TargetDictionary)

Multiline mode

Using Roslyn syntax parsing, we also support multiline REPL mode. This means that if you have an uncompleted code block and press Enter, we will automatically enter the multiline mode. The mode is indicated by the * character. This is particularly useful for declaring classes and other more complex constructs.

~$ dotnet script
> class Foo {
* public string Bar {get; set;}
* }
> var foo = new Foo();

REPL commands

Aside from the regular C# script code, you can invoke the following commands (directives) from within the REPL:

#loadLoad a script into the REPL (same as #load usage in CSX)
#rLoad an assembly into the REPL (same as #r usage in CSX)
#resetReset the REPL back to initial state (without restarting it)
#clsClear the console screen without resetting the REPL state
#exitExits the REPL

Seeding REPL with a script

You can execute a CSX script and, at the end of it, drop yourself into the context of the REPL. This way, the REPL becomes "seeded" with your code - all the classes, methods or variables are available in the REPL context. This is achieved by running a script with an -i flag.

For example, given the following CSX script:

var msg = "Hello World";

When you run this with the -i flag, Hello World is printed, REPL starts and msg variable is available in the REPL context.

~$ dotnet script foo.csx -i
Hello World

You can also seed the REPL from inside the REPL - at any point - by invoking a #load directive pointed at a specific file. For example:

~$ dotnet script
> #load "foo.csx"
Hello World


The following example shows how we can pipe data in and out of a script.

The UpperCase.csx script simply converts the standard input to upper case and writes it back out to standard output.

using (var streamReader = new StreamReader(Console.OpenStandardInput()))

We can now simply pipe the output from one command into our script like this.

echo "This is some text" | dotnet script UpperCase.csx


The first thing we need to do add the following to the launch.config file that allows VS Code to debug a running process.

    "name": ".NET Core Attach",
    "type": "coreclr",
    "request": "attach",
    "processId": "${command:pickProcess}"

To debug this script we need a way to attach the debugger in VS Code and the simplest thing we can do here is to wait for the debugger to attach by adding this method somewhere.

public static void WaitForDebugger()
    Console.WriteLine("Attach Debugger (VS Code)");

To debug the script when executing it from the command line we can do something like

using (var streamReader = new StreamReader(Console.OpenStandardInput()))
    Write(streamReader.ReadToEnd().ToUpper()); // <- SET BREAKPOINT HERE

Now when we run the script from the command line we will get

$ echo "This is some text" | dotnet script UpperCase.csx
Attach Debugger (VS Code)

This now gives us a chance to attach the debugger before stepping into the script and from VS Code, select the .NET Core Attach debugger and pick the process that represents the executing script.

Once that is done we should see our breakpoint being hit.


By default, scripts will be compiled using the debug configuration. This is to ensure that we can debug a script in VS Code as well as attaching a debugger for long running scripts.

There are however situations where we might need to execute a script that is compiled with the release configuration. For instance, running benchmarks using BenchmarkDotNet is not possible unless the script is compiled with the release configuration.

We can specify this when executing the script.

dotnet script foo.csx -c release


Nullable reference types

Starting from version 0.50.0, dotnet-script supports .Net Core 3.0 and all the C# 8 features. The way we deal with nullable references types in dotnet-script is that we turn every warning related to nullable reference types into compiler errors. This means every warning between CS8600 and CS8655 are treated as an error when compiling the script.

Nullable references types are turned off by default and the way we enable it is using the #nullable enable compiler directive. This means that existing scripts will continue to work, but we can now opt-in on this new feature.

#!/usr/bin/env dotnet-script

#nullable enable

string name = null;

Trying to execute the script will result in the following error

main.csx(5,15): error CS8625: Cannot convert null literal to non-nullable reference type.

We will also see this when working with scripts in VS Code under the problems panel.


Download Details:
Author: filipw
Source Code:
License: MIT License

#dotnet  #aspdotnet  #csharp 

Ray  Patel

Ray Patel


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

Ray  Patel

Ray Patel


Advance Web Penetration Testing Tool For Python

Features 🎭

Admin Panel Finder

Admin Scanner

Dork Generator

Advance Dork Finder

Extract Links

No Redirect

Hash Crack (Online-Database)

Hash Crack (Wordlist)

Whois Lookup

Tcp Port Scan

Geo IP Lookup

Reserve Analysts Search

Csrf Vernavility Checker


WordPress Username Finder

#testing #advance web penetration testing tool for python #python #advance web penetration #testing tool for python #web

Aurelie  Block

Aurelie Block


Top 10 Automation Testing Tools: 2020 Edition

The demand for delivering quality software faster — or “Quality at Speed” — requires organizations to search for solutions in Agile, continuous integration (CI), and DevOps methodologies. Test automation is an essential part of these aspects. The latest World Quality Report 2018–2019 suggests that test automation is the biggest bottleneck to deliver “Quality at Speed,” as it is an enabler of successful Agile and DevOps adoption.

Test automation cannot be realized without good tools; as they determine how automation is performed and whether the benefits of automation can be delivered. Test automation tools is a crucial component in the DevOps toolchain. The current test automation trends have increased in applying artificial intelligence and machine learning (AI/ML) to offer advanced capabilities for test optimization, intelligent test generation, execution, and reporting. It will be worthwhile to understand which tools are best poised to take advantage of these trends.****

#automation-testing #automation-testing-tools #testing #testing-tools #selenium #open-source #test-automation #automated-testing

Shardul Bhatt

Shardul Bhatt


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.


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