Fiddler聽vs聽Python

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Fiddler
Fiddler

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Python

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Fiddler vs Python: What are the differences?

Developers describe Fiddler as "A free web debugging tool *". It is a free web debugging proxy for any browser, system or platform. It helps you debug web applications by capturing network traffic between the Internet and test computers. The tool enables you to inspect incoming and outgoing data to monitor and modify requests and responses before the browser receives them. On the other hand, *Python** is detailed as "A clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java". Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.

Fiddler can be classified as a tool in the "API Tools" category, while Python is grouped under "Languages".

Python is an open source tool with 25.3K GitHub stars and 10.5K GitHub forks. Here's a link to Python's open source repository on GitHub.

According to the StackShare community, Python has a broader approval, being mentioned in 2831 company stacks & 3641 developers stacks; compared to Fiddler, which is listed in 4 company stacks and 4 developer stacks.

- No public GitHub repository available -

What is Fiddler?

It is a free web debugging proxy for any browser, system or platform. It helps you debug web applications by capturing network traffic between the Internet and test computers. The tool enables you to inspect incoming and outgoing data to monitor and modify requests and responses before the browser receives them.

What is Python?

Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
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Why do developers choose Fiddler?
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      What tools integrate with Fiddler?
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        What are some alternatives to Fiddler and Python?
        Charles
        Charles is a web proxy (HTTP Proxy / HTTP Monitor) that runs on your own computer. Your web browser (or any other Internet application) is then configured to access the Internet through Charles, and Charles is then able to record and display for you all of the data that is sent and received.
        Postman
        It is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide.
        Amazon API Gateway
        Amazon API Gateway handles all the tasks involved in accepting and processing up to hundreds of thousands of concurrent API calls, including traffic management, authorization and access control, monitoring, and API version management.
        Insomnia REST Client
        Insomnia is a powerful REST API Client with cookie management, environment variables, code generation, and authentication for Mac, Window, and Linux.
        Paw
        Paw is a full-featured and beautifully designed Mac app that makes interaction with REST services delightful. Either you are an API maker or consumer, Paw helps you build HTTP requests, inspect the server's response and even generate client code.
        See all alternatives
        Decisions about Fiddler and Python
        Hampton Catlin
        Hampton Catlin
        VP of Engineering at Rent The Runway | 9 upvotes 109.9K views
        atRent the RunwayRent the Runway
        Ruby
        Ruby
        Python
        Python
        Java
        Java

        At our company, and I've noticed a lot of other ones... application developers and dev-ops people tend to use Ruby and our statisticians and data scientists love Python . Like most companies, our stack is kind of split that way. Ruby is used as glue in most of our production systems ( Java being the main backend language), and then all of our data scientists and their various pipelines tend towards Python

        See more
        Ajit Parthan
        Ajit Parthan
        CTO at Shaw Academy | 3 upvotes 6.1K views
        atShaw AcademyShaw Academy
        PHP
        PHP
        Python
        Python
        #Etl

        Multiple systems means there is a requirement to cart data across them.

        Started off with Talend scripts. This was great as what we initially had were PHP/Python script - allowed for a more systematic approach to ETL.

        But ended up with a massive repository of scripts, complex crontab entries and regular failures due to memory issues.

        Using Stitch or similar services is a better approach: - no need to worry about the infrastructure needed for the ETL processes - a more formal mapping of data from source to destination as opposed to script developer doing his/her voodoo magic - lot of common sources and destination integrations are already builtin and out of the box

        etl @{etlasaservice}|topic:1323|

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        Visual Studio Code
        Visual Studio Code
        GitHub
        GitHub
        Linux
        Linux
        JavaScript
        JavaScript
        Swift
        Swift
        Java
        Java
        PHP
        PHP
        Python
        Python
        XML
        XML
        JSON
        JSON
        Git
        Git
        SVN (Subversion)
        SVN (Subversion)

        I use Visual Studio Code because at this time is a mature software and I can do practically everything using it.

        • It's free and open source: The project is hosted on GitHub and it鈥檚 free to download, fork, modify and contribute to the project.

        • Multi-platform: You can download binaries for different platforms, included Windows (x64), MacOS and Linux (.rpm and .deb packages)

        • LightWeight: It runs smoothly in different devices. It has an average memory and CPU usage. Starts almost immediately and it鈥檚 very stable.

        • Extended language support: Supports by default the majority of the most used languages and syntax like JavaScript, HTML, C#, Swift, Java, PHP, Python and others. Also, VS Code supports different file types associated to projects like .ini, .properties, XML and JSON files.

        • Integrated tools: Includes an integrated terminal, debugger, problem list and console output inspector. The project navigator sidebar is simple and powerful: you can manage your files and folders with ease. The command palette helps you find commands by text. The search widget has a powerful auto-complete feature to search and find your files.

        • Extensible and configurable: There are many extensions available for every language supported, including syntax highlighters, IntelliSense and code completion, and debuggers. There are also extension to manage application configuration and architecture like Docker and Jenkins.

        • Integrated with Git: You can visually manage your project repositories, pull, commit and push your changes, and easy conflict resolution.( there is support for SVN (Subversion) users by plugin)

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        Ajit Parthan
        Ajit Parthan
        CTO at Shaw Academy | 1 upvotes 4.7K views
        atShaw AcademyShaw Academy
        PHP
        PHP
        Python
        Python

        Multiple systems means there is a requirement to cart data across them.

        Started off with Talend scripts. This was great as what we initially had were PHP/Python script - allowed for a more systematic approach to ETL.

        But ended up with a massive repository of scripts, complex crontab entries and regular failures due to memory issues.

        Using Stitch or similar services is a better approach: - no need to worry about the infrastructure needed for the ETL processes - a more formal mapping of data from source to destination as opposed to script developer doing his/her voodoo magic - lot of common sources and destination integrations are already builtin and out of the box

        See more
        Eric Colson
        Eric Colson
        Chief Algorithms Officer at Stitch Fix | 19 upvotes 878.6K views
        atStitch FixStitch Fix
        Kafka
        Kafka
        PostgreSQL
        PostgreSQL
        Amazon S3
        Amazon S3
        Apache Spark
        Apache Spark
        Presto
        Presto
        Python
        Python
        R Language
        R Language
        PyTorch
        PyTorch
        Docker
        Docker
        Amazon EC2 Container Service
        Amazon EC2 Container Service
        #AWS
        #Etl
        #ML
        #DataScience
        #DataStack
        #Data

        The algorithms and data infrastructure at Stitch Fix is housed in #AWS. Data acquisition is split between events flowing through Kafka, and periodic snapshots of PostgreSQL DBs. We store data in an Amazon S3 based data warehouse. Apache Spark on Yarn is our tool of choice for data movement and #ETL. Because our storage layer (s3) is decoupled from our processing layer, we are able to scale our compute environment very elastically. We have several semi-permanent, autoscaling Yarn clusters running to serve our data processing needs. While the bulk of our compute infrastructure is dedicated to algorithmic processing, we also implemented Presto for adhoc queries and dashboards.

        Beyond data movement and ETL, most #ML centric jobs (e.g. model training and execution) run in a similarly elastic environment as containers running Python and R code on Amazon EC2 Container Service clusters. The execution of batch jobs on top of ECS is managed by Flotilla, a service we built in house and open sourced (see https://github.com/stitchfix/flotilla-os).

        At Stitch Fix, algorithmic integrations are pervasive across the business. We have dozens of data products actively integrated systems. That requires serving layer that is robust, agile, flexible, and allows for self-service. Models produced on Flotilla are packaged for deployment in production using Khan, another framework we've developed internally. Khan provides our data scientists the ability to quickly productionize those models they've developed with open source frameworks in Python 3 (e.g. PyTorch, sklearn), by automatically packaging them as Docker containers and deploying to Amazon ECS. This provides our data scientist a one-click method of getting from their algorithms to production. We then integrate those deployments into a service mesh, which allows us to A/B test various implementations in our product.

        For more info:

        #DataScience #DataStack #Data

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        Node.js
        Node.js
        JavaScript
        JavaScript
        Django
        Django
        Python
        Python

        Django or NodeJS? Hi, I鈥檓 thinking about which software I should use for my web-app. What about Node.js or Django for the back-end? I want to create an online preparation course for the final school exams in my country. At the beginning for maths. The course should contain tutorials and a lot of exercises of different types. E.g. multiple choice, user text/number input and drawing tasks. The exercises should change (different levels) with the learning progress. Wrong questions should asked again with different numbers. I also want a score system and statistics. So far, I have got only limited web development skills. (some HTML, CSS, Bootstrap and Wordpress). I don鈥檛 know JavaScript or Python.

        Possible pros for Python / Django: - easy syntax, easier to learn for me as a beginner - fast development, earlier release - libraries for mathematical and scientific computation

        Possible pros for JavaScript / Node.js: - great performance, better choice for real time applications: user should get the answer for a question quickly

        Which software would you use in my case? Are my arguments for Python/NodeJS right? Which kind of database would you use?

        Thank you for your answer!

        Node.js JavaScript Django Python

        See more
        Go
        Go
        Python
        Python
        PostgreSQL
        PostgreSQL
        TypeScript
        TypeScript
        JavaScript
        JavaScript
        NATS
        NATS
        Docker
        Docker
        Git
        Git

        Go is a high performance language with simple syntax / semantics. Although it is not as expressive as some other languages, it's still a great language for backend development.

        Python is expressive and battery-included, and pre-installed in most linux distros, making it a great language for scripting.

        PostgreSQL: Rock-solid RDBMS with NoSQL support.

        TypeScript saves you from all nonsense semantics of JavaScript , LOL.

        NATS: fast message queue and easy to deploy / maintain.

        Docker makes deployment painless.

        Git essential tool for collaboration and source management.

        See more
        Omar Melendrez
        Omar Melendrez
        Front-end developer | 4 upvotes 4.4K views
        Vue.js
        Vue.js
        React
        React
        Node.js
        Node.js
        C#
        C#
        Python
        Python
        #Fullstack
        #Vscode

        I'm #Fullstack here and work with Vue.js, React and Node.js in some projects but also C# for other clients. Also started learning Python. And all this with just one tool!: #Vscode I have used Atom and Sublime Text in the past and they are very good too, but for me now is just vscode. I think the combination of vscode with the free available extensions that the community is creating makes a powerful tool and that's why vscode became the most popular IDE for software development. You can match it to your own needs in a couple of minutes. Did I mention you can style it your way? Amazing tool!

        See more
        Tom Klein
        Tom Klein
        CEO at Gentlent | 4 upvotes 45.4K views
        atGentlentGentlent
        JavaScript
        JavaScript
        Node.js
        Node.js
        PHP
        PHP
        HTML5
        HTML5
        Sass
        Sass
        nginx
        nginx
        React
        React
        PostgreSQL
        PostgreSQL
        Ubuntu
        Ubuntu
        ES6
        ES6
        TypeScript
        TypeScript
        Google Compute Engine
        Google Compute Engine
        Socket.IO
        Socket.IO
        Electron
        Electron
        Python
        Python

        Our most used programming languages are JavaScript / Node.js for it's lightweight and fast use, PHP because everyone knows it, HTML5 because you can't live without it and Sass to write great CSS. Occasionally, we use nginx as a web server and proxy, React for our UX, PostgreSQL as fast relational database, Ubuntu as server OS, ES6 and TypeScript for Node, Google Compute Engine for our infrastructure, and Socket.IO and Electron for specific use cases. We also use Python for some of our backends.

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        Praveen Mooli
        Praveen Mooli
        Engineering Manager at Taylor and Francis | 12 upvotes 685.2K views
        MongoDB Atlas
        MongoDB Atlas
        Java
        Java
        Spring Boot
        Spring Boot
        Node.js
        Node.js
        ExpressJS
        ExpressJS
        Python
        Python
        Flask
        Flask
        Amazon Kinesis
        Amazon Kinesis
        Amazon Kinesis Firehose
        Amazon Kinesis Firehose
        Amazon SNS
        Amazon SNS
        Amazon SQS
        Amazon SQS
        AWS Lambda
        AWS Lambda
        Angular 2
        Angular 2
        RxJS
        RxJS
        GitHub
        GitHub
        Travis CI
        Travis CI
        Terraform
        Terraform
        Docker
        Docker
        Serverless
        Serverless
        Amazon RDS
        Amazon RDS
        Amazon DynamoDB
        Amazon DynamoDB
        Amazon S3
        Amazon S3
        #Backend
        #Microservices
        #Eventsourcingframework
        #Webapps
        #Devops
        #Data

        We are in the process of building a modern content platform to deliver our content through various channels. We decided to go with Microservices architecture as we wanted scale. Microservice architecture style is an approach to developing an application as a suite of small independently deployable services built around specific business capabilities. You can gain modularity, extensive parallelism and cost-effective scaling by deploying services across many distributed servers. Microservices modularity facilitates independent updates/deployments, and helps to avoid single point of failure, which can help prevent large-scale outages. We also decided to use Event Driven Architecture pattern which is a popular distributed asynchronous architecture pattern used to produce highly scalable applications. The event-driven architecture is made up of highly decoupled, single-purpose event processing components that asynchronously receive and process events.

        To build our #Backend capabilities we decided to use the following: 1. #Microservices - Java with Spring Boot , Node.js with ExpressJS and Python with Flask 2. #Eventsourcingframework - Amazon Kinesis , Amazon Kinesis Firehose , Amazon SNS , Amazon SQS, AWS Lambda 3. #Data - Amazon RDS , Amazon DynamoDB , Amazon S3 , MongoDB Atlas

        To build #Webapps we decided to use Angular 2 with RxJS

        #Devops - GitHub , Travis CI , Terraform , Docker , Serverless

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        Adam Bavosa
        Adam Bavosa
        Python
        Python
        JavaScript
        JavaScript
        asyncio
        asyncio
        PubNub
        PubNub

        I love Python and JavaScript . You can do the same JavaScript async operations in Python by using asyncio. This is particularly useful when you need to do socket programming in Python. With streaming sockets, data can be sent or received at any time. In case your Python program is in the middle of executing some code, other threads can handle the new socket data. Libraries like asyncio implement multiple threads, so your Python program can work in an asynchronous fashion. PubNub makes bi-directional data streaming between devices even easier.

        See more
        Helio Junior
        Helio Junior
        Python
        Python
        JavaScript
        JavaScript
        CSS 3
        CSS 3
        #DataScience
        #UXdesign
        #NodeJS
        #Electron

        Python is a excellent tool for #DataScience , but up to now is very poor in #uxdesign . To do some design I'm using JavaScript and #nodejs , #electron stack. The possibility of use CSS 3 to draw interfaces is very awesome and fast. Unfortunatelly Python don't have (yet) a good way to make a #UXdesign .

        See more
        Ruby
        Ruby
        Rails
        Rails
        React
        React
        Redux
        Redux
        Create React App
        Create React App
        Jest
        Jest
        react-testing-library
        react-testing-library
        RSpec
        RSpec
        PostgreSQL
        PostgreSQL
        MongoDB
        MongoDB
        Redis
        Redis
        React Native
        React Native
        Next.js
        Next.js
        Python
        Python
        Bit
        Bit
        JavaScript
        JavaScript

        I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.

        We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.

        Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis 聽for cache and other time sensitive operations.

        We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.

        Since we have different frontend apps we have found useful to have Bit to document visual components and utils in JavaScript.

        See more
        Node.js
        Node.js
        Java
        Java
        Spring Boot
        Spring Boot
        Python
        Python
        Flask
        Flask
        Django
        Django

        Since you said that your middleware will be accessing DB and expose API, you can go with Node.js. It will make your development fast and easy. Suppose in future you will add some business logic you can choose Java with Spring Boot or Python with Flask / Django. NOTE: Language or framework doesn't matter. Choose based on your programming knowledge.

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        Jakub Olan
        Jakub Olan
        DevOps Engineer | 17 upvotes 17.2K views
        ataraclxaraclx
        Java
        Java
        Python
        Python
        C++
        C++
        Node.js
        Node.js
        Rust
        Rust
        Kotlin
        Kotlin
        Go
        Go

        In our company we have think a lot about languages that we're willing to use, there we have considering Java, Python and C++ . All of there languages are old and well developed at fact but that's not ideology of araclx. We've choose a edge technologies such as Node.js , Rust , Kotlin and Go as our programming languages which is some kind of fun. Node.js is one of biggest trends of 2019, same for Go. We want to grow in our company with growth of languages we have choose, and probably when we would choose Java that would be almost impossible because larger languages move on today's market slower, and cannot have big changes.

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        Interest over time
        Reviews of Fiddler and Python
        No reviews found
        How developers use Fiddler and Python
        Avatar of Exchange rates API
        Exchange rates API uses PythonPython

        Beautiful is better than ugly.

        Explicit is better than implicit.

        Simple is better than complex.

        Complex is better than complicated.

        Flat is better than nested.

        Sparse is better than dense.

        Readability counts.

        Special cases aren't special enough to break the rules.

        Although practicality beats purity.

        Errors should never pass silently.

        Unless explicitly silenced.

        In the face of ambiguity, refuse the temptation to guess.

        There should be one-- and preferably only one --obvious way to do it.

        Although that way may not be obvious at first unless you're Dutch.

        Now is better than never.

        Although never is often better than right now.

        If the implementation is hard to explain, it's a bad idea.

        If the implementation is easy to explain, it may be a good idea.

        Namespaces are one honking great idea -- let's do more of those!

        Avatar of Web Dreams
        Web Dreams uses PythonPython

        To me, this is by far the best programming language. Why? Because it鈥檚 the only language that really got me going after trying to get into programming with Java for a while. Python is powerful, easy to learn, and gets you to unsderstand other languages more once you understand it. Did I state I love the python language? Well, I do..

        Avatar of ttandon
        ttandon uses PythonPython

        Backend server for analysis of image samples from iPhone microscope lens. Chose this because of familiarity. The number one thing that I've learned at hackathons is that work exclusively with what you're 100% comfortable with. I use Python extensively at my day job at Wit.ai, so it was the obvious choice for the bulk of my coding.

        Avatar of papaver
        papaver uses PythonPython

        been a pythoner for around 7 years, maybe longer. quite adept at it, and love using the higher constructs like decorators. was my goto scripting language until i fell in love with clojure. python's also the goto for most vfx studios and great for the machine learning. numpy and pyqt for the win.

        Avatar of Blood Bot
        Blood Bot uses PythonPython

        Large swaths of resources built for python to achieve natural language processing. (We are in the process of deprecating the services written in python and porting them over to Javascript and node)

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