Based on our record, Pandas seems to be a lot more popular than Buildbot. While we know about 198 links to Pandas, we've tracked only 9 mentions of Buildbot. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Buildbot is a versatile CI framework designed to automate all aspects of the software development cycle, enhancing efficiency and reliability. As an open-source platform, it is highly customizable, allowing teams to tailor the automation process to their specific needs. Buildbot excels in integrating various stages of development, from code integration, testing, to deployment, ensuring a seamless and coherent... - Source: dev.to / 4 months ago
If you want more than the builtin CIs in Github and Gitlab, https://buildbot.net is the way. Source: about 1 year ago
If you don't have one already integrated with your source control, buildbot is pretty nice and doesn't force you to use docker like most others. Source: over 1 year ago
Https://buildbot.net/ existed before Jenkins Hudson and was quite well known. Source: over 1 year ago
I have used python based CI tool buildbot which is a great tool but we want to move away from buildbot only because in some scenarios we want to compile low-level microseconds which are in c++ to a different architecture. Buildbot doesn't have such a feature. - Source: dev.to / almost 2 years ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 9 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 2 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / about 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 4 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development
NumPy - NumPy is the fundamental package for scientific computing with Python
Travis CI - Focus on writing code. Let Travis CI take care of running your tests and deploying your apps.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.
OpenCV - OpenCV is the world's biggest computer vision library