Alternatives to PyCharm

I liked Sublime Text for its speed, simplicity and keyboard shortcuts which synergize well when working on scripting languages like Ruby and JavaScript. I extended the editor with custom Python scripts that improved keyboard navigability such as autofocusing the sidebar when no files are open, or changing tab closing behavior.

But customization can only get you so far, and there were little things that I still had to use the mouse for, such as scrolling, repositioning lines on the screen, selecting the line number of a failing test stack trace from a separate plugin pane, etc. After 3 years of wearily moving my arm and hand to perform the same repetitive tasks, I decided to switch to Vim for 3 reasons:

• your fingers literally don’t ever need to leave the keyboard home row (I had to remap the escape key though)
• it is a reliable tool that has been around for more than 30 years and will still be around for the next 30 years
• I wanted to "look like a hacker" by doing everything inside my terminal and by becoming a better Unix citizen

The learning curve is very steep and it took me a year to master it, but investing time to be truly comfortable with my #TextEditor was more than worth it. To me, Vim comes close to being the perfect editor and I probably won’t need to switch ever again. It feels good to ignore new editors that come out every few years, like Atom and Visual Studio Code.

We use Visual Studio Code because it allows us to easily and quickly integrate with Git, much like Sublime Merge ,but it is integrated into the IDE. Another cool part about VS Code is the ability collaborate with each other with Visual Studio Live Share which allows our whole team to get more done together. It brings the convenience of the Google Suite to programming, offering something that works more smoothly than anything found on Atom or Sublime Text

UPDATE: Thanks for the great response. I am going to start with VSCode based on the open source and free version that will allow me to grow into other languages, but not cost me a license ..yet.

I have been working with software development for 12 years, but I am just beginning my journey to learn to code. I am starting with Python following the suggestion of some of my coworkers. They are split between Eclipse and IntelliJ IDEA for IDEs that they use and PyCharm is new to me. Which IDE would you suggest for a beginner that will allow expansion to Java, JavaScript, and eventually AngularJS and possibly mobile applications?

I am a QA heading to a new company where they all generally use Visual Studio Code, my experience is with IntelliJ IDEA and PyCharm. The language they use is JavaScript and so I will be writing my test framework in javaScript so the devs can more easily write tests without context switching.

My 2 questions: Does VS Code have Cucumber Plugins allowing me to write behave tests? And more importantly, does VS Code have the same refactoring tools that IntelliJ IDEA has? I love that I have easy access to a range of tools that allow me to refactor and simplify my code, making code writing really easy.

From my point of view, both OpenRefine and Apache Hive serve completely different purposes. OpenRefine is intended for interactive cleaning of messy data locally. You could work with their libraries to use some of OpenRefine features as part of your data pipeline (there are pointers in FAQ), but OpenRefine in general is intended for a single-user local operation.

I can't recommend a particular alternative without better understanding of your use case. But if you are looking for an interactive tool to work with big data at scale, take a look at notebook environments like Jupyter, Databricks, or Deepnote. If you are building a data processing pipeline, consider also Apache Spark.

Edit: Fixed references from Hadoop to Hive, which is actually closer to Spark.

Jupyter Anaconda Pandas IPython

A great way to prototype your data analytic modules. The use of the package is simple and user-friendly and the migration from ipython to python is fairly simple: a lot of cleaning, but no more.

The negative aspect comes when you want to streamline your productive system or does CI with your anaconda environment: - most tools don't accept conda environments (as smoothly as pip requirements) - the conda environments (even with miniconda) have quite an overhead

Our first experience with .NET core was when we developed our OSS feature management platform - Tweek (https://github.com/soluto/tweek). We wanted to create a solution that is able to run anywhere (super important for OSS), has excellent performance characteristics and can fit in a multi-container architecture. We decided to implement our rule engine processor in F# , our main service was implemented in C# and other components were built using JavaScript / TypeScript and Go.

Visual Studio Code worked really well for us as well, it worked well with all our polyglot services and the .Net core integration had great cross-platform developer experience (to be fair, F# was a bit trickier) - actually, each of our team members used a different OS (Ubuntu, macos, windows). Our production deployment ran for a time on Docker Swarm until we've decided to adopt Kubernetes with almost seamless migration process.

After our positive experience of running .Net core workloads in containers and developing Tweek's .Net services on non-windows machines, C# had gained back some of its popularity (originally lost to Node.js), and other teams have been using it for developing microservices, k8s sidecars (like https://github.com/Soluto/airbag), cli tools, serverless functions and other projects...

Our whole DevOps stack consists of the following tools:

• GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
• Respectively Git as revision control system
• SourceTree as Git GUI
• Visual Studio Code as IDE
• CircleCI for continuous integration (automatize development process)
• Prettier / TSLint / ESLint as code linter
• SonarQube as quality gate
• Docker as container management (incl. Docker Compose for multi-container application management)
• VirtualBox for operating system simulation tests
• Kubernetes as cluster management for docker containers
• Heroku for deploying in test environments
• nginx as web server (preferably used as facade server in production environment)
• SSLMate (using OpenSSL) for certificate management
• Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
• PostgreSQL as preferred database system
• Redis as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

• Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
• Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
• Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
• Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
• Scalability: All-in-one framework for distributed systems.
• Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.

Which one of these should I install? I am a beginner and starting to learn to code. I have Anaconda, Visual Studio Code ( vscode recommended me to install Git) and I am learning Python, JavaScript, and MySQL for educational purposes. Also if you have any other pro-tips or advice for me please share.

Yours thankfully, Darkhiem

I am going to learn machine learning and self host an online IDE, the tool that i may use is Python, Anaconda, various python library and etc. which tools should i go for? this may include Java development, web development. Now i have 1 more candidate which are visual studio code online (code server). i will host on google cloud

UPDATE: Thanks for the great response. I am going to start with VSCode based on the open source and free version that will allow me to grow into other languages, but not cost me a license ..yet.

I have been working with software development for 12 years, but I am just beginning my journey to learn to code. I am starting with Python following the suggestion of some of my coworkers. They are split between Eclipse and IntelliJ IDEA for IDEs that they use and PyCharm is new to me. Which IDE would you suggest for a beginner that will allow expansion to Java, JavaScript, and eventually AngularJS and possibly mobile applications?

Have been a Visual Studio Code user since just after launch to the general public, having used the likes of Eclipse and Atom previously. Was amazed how mature it seemed off the bat and was super intrigued by the bootstrapped nature of it having been written/based on Electron/TypeScript, and of course being an open-source app from Microsoft. The features, plugin ecosystem and release frequency are very impressive. I do dev work on both Mac and Windows and don't use anything else now as far as IDEs go.

I use TypeScript because it greatly simplify my refactoring efforts. I regularly re-validate my assumption about application architecture, and strictness of types allow me write make changes safely using just Visual Studio tooling. Integration with existing JavaScript libraries very simple and fast. If I have no time, I could just use any type as output of JS module. When I have more time, I could just submit PR to DefinitelyTyped and it would be quickly accepted. Overall it gives less ambiguity for my code.

.NET Core is #free, #cross-platform, and #opensource. A developer platform for building all types of apps ( #web apps #mobile #games #machinelearning #AI and #Desktop ).

Developers have chosen .NET for:

Productive: Combined with the extensive class libraries, common APIs, multi-language support, and the powerful tooling provided by the Visual Studio family ( Visual Studio and Visual Studio Code ), .NET is the most productive platform for developers.

Any app: From mobile applications running on iOS, Android and Windows, to Enterprise server applications running on Windows Server and Linux, or high-scale microservices running in the cloud, .NET provides a solution for you.

Performance: .NET is fast. Really fast! The popular TechEmpower benchmark compares web application frameworks with tasks like JSON serialization, database access, and server side template rendering - .NET performs faster than any other popular framework.