Mezzanine
Pandas
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Mezzanine | Pandas | |
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5 | 393 | |
4,713 | 41,863 | |
- | 1.3% | |
0.0 | 10.0 | |
9 days ago | 3 days ago | |
Python | Python | |
BSD 2-clause "Simplified" License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Mezzanine
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Fabric + buildout as opposed to Fabric + pip + virtualenv
I've recently started playing around with Mezzanine, a django-based CMS. I recently just managed to configure Fabric to get it uploading to my host, webfaction.com, as its a bit more involved automatically creating the website on the shared hosting, and I wanted to automate that process.
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How to deploy Python Scripts to bereveal.com
To give you a better idea of how Python-based applications work on our servers, we’ll show you how to install the Django framework-powered Mezzanine CMS on our platform via SSH.
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Minimal alternative to Django Oscar?
There is also Mezzanine / Cartridge which is kinda like WordPress / WooCommerce in the PHP world, it’s primarily for a website that may have a shop added to it. Be aware that this is also somewhat legacy, last time I checked it was kinda in maintenance mode and the variant system for products was super limited.
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what would be you choice of packages for building an e-commerce site with Django?
Mezzanine / Cartridge is similar to WooCommerce in the WordPress world, if you are wanting to add a shop to an existing site then this is a decent option. The problem with it is that the main dev on it went off to work for Google so it’s more or less in maintenance mode and the product variant system is very basic.
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Adding CMS to an existing Django application
mezzanine is probably a simpler one. it recently just got revived and their 5.0 release is now in rc1 state. There's also django-fiber which seems to be quite simple (not much code, one app to add only)
Pandas
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Deploying a Serverless Dash App with AWS SAM and Lambda
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. Instead, we'll focus on what's necessary to make it run serverless.
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Help Us Build Our Roadmap – Pydantic
there is pull request to integrate in both pydantic extra types and into pandas cose [1]
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Stuff I Learned during Hanukkah of Data 2023
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.
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Introducing Flama for Robust Machine Learning APIs
pandas: A library for data analysis in Python
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
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.
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Mastering Pandas read_csv() with Examples - A Tutorial by Codes With Pankaj
Pandas, a powerful data manipulation library in Python, has become an essential tool for data scientists and analysts. One of its key functions is read_csv(), which allows users to read data from CSV (Comma-Separated Values) files into a Pandas DataFrame. In this tutorial, brought to you by CodesWithPankaj.com, we will explore the intricacies of read_csv() with clear examples to help you harness its full potential.
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What Would Go in Your Dream Documentation Solution?
So, what I'd like to do is write a documentation package in Python to recreate what I've lost. I plan to build upon the fantastic python-docx and docxtpl packages, and I'll probably rely on pandas from much of the tabular stuff. Here are the features I intend to include:
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How do people know when to use what programming language?
Weirdly most of my time spent with data analysis was in the C layers in pandas.
- Read files from s3 using Pandas/s3fs or AWS Data Wrangler?
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10 Github repositories to achieve Python mastery
Explore here.
What are some alternatives?
Wagtail - A Django content management system focused on flexibility and user experience
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
django-cms - The easy-to-use and developer-friendly enterprise CMS powered by Django
tensorflow - An Open Source Machine Learning Framework for Everyone
Plone - The core of the Plone content management system
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
FeinCMS - A Django-based CMS with a focus on extensibility and concise code
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Widgy - A CMS framework for Django built on a heterogenous tree editor.
Keras - Deep Learning for humans
Opps - A Django-based CMS for the magazines, newspappers websites and portals with high-traffic
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration