CherryPy
Django
Flask
web2py
Bottle
Pyramid
Tornado
BlueBream
Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
CherryPy PandasBased on our record, Pandas seems to be a lot more popular than CherryPy. While we know about 198 links to Pandas, we've tracked only 2 mentions of CherryPy. 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.
Generally, what needs to be done to create an Django/Electron app is to package (I'm using pyInstaller)the Django app into an stand-alone executable and then bundle that into an Electron app. The question is which server should be used for this case to server Django before packaging it with pyInstaller? At the moment I'm using cherryPy as a WSGI web server to serve Django. Source: about 2 years ago
I know there are plenty of questions about Flask and CherryPy and static files but I still can't seem to get this working. Source: about 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 / 14 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 / 7 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 / 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 / 5 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
Django - The Web framework for perfectionists with deadlines
NumPy - NumPy is the fundamental package for scientific computing with Python
Flask - a microframework for Python based on Werkzeug, Jinja 2 and good intentions.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
web2py - Web2py is an open source web application framework.
OpenCV - OpenCV is the world's biggest computer vision library