18 Matching Annotations
  1. Oct 2020
    1. Use Streamlit if you want to get going as quickly possible and don’t have strong opinions or many custom requirements.Use Dash if you need something more flexible and mature, and you don’t mind spending the extra engineering time.

      Streamlit vs Dash

    2. Here’s a table showing the tradeoffs:

      Comparison of dashboard tech stack as of 10/2020:

  2. Sep 2020
    1. We use the em dash to create a strong break in the structure of a sentence. We can use these dashes in pairs, as we would use parentheses—that is, to enclose a word, or a phrase, or a clause (as we’ve done here)—or they can be used alone to detach one end of a sentence from its main body.
  3. Jul 2020
    1. Use it betweenwords that indicate a duration, such as hourly time or months or years. Useit where you would otherwise use the word “to.”

      En Dash guidelines

    2. The em dash is twice as long as the en dash, approximately the width of acapital letter M.

      Em dash guidelines

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  4. May 2020
    1. Hot Reloading refers to the ability to automatically update a running web application when changes are made to the application’s code.

      Hot Reloading is what provides a great experience with updating your Dash code inside the Jupyter Notebooks

    2. JupyterDash supports three approaches to displaying a Dash application during interactive development.

      3 display modes of Dash using Jupyter Notebooks:

      1. app.run_server(mode='external')
      2. app.run_server(mode='inline')
      3. app.run_server(mode='jupyterlab')
    3. # Run app and display result inline in the notebookapp.run_server(mode='inline')

      Moreover, you can display your Dash result inside a Jupyter Notebook using IPython.display.IFrame with this line:

      app.run_server(mode='inline')
      

    4. If running the server blocks the main thread, then it’s not possible to execute additional code cells without manually interrupting the execution of the kernel.JupyterDash resolves this problem by executing the Flask development server in a background thread. This leaves the main execution thread available for additional calculations. When a request is made to serve a new version of the application on the same port, the currently running application is automatically shut down first. This makes is possible to quickly update a running application by simply re-executing the notebook cells that define it.

      How Dash can run inside Jupyter Notebooks

    5. You can also try it out, right in your browser, with binder.

      Dash can be tried out inside a Jupyter Notebook right in your browser using binder.

    6. Then, copy any Dash example into a Jupyter notebook cell and replace the dash.Dash class with the jupyter_dash.JupyterDash class.

      To use Dash in Jupyter Notebooks, you have to import:

      from jupyter_dash import JupyterDash
      

      instead of:

      import dash
      

      Therefore, all the imports could look like that for a typical Dash app inside a Jupyter Notebook:

      import plotly.express as px
      from jupyter_dash import JupyterDash
      import dash_core_components as dcc
      import dash_html_components as html
      from dash.dependencies import Input, Output
      
  5. Apr 2020
    1. Most people are surprised to learn that of Plotly’s 50 engineers, the vast majority are React developers. This is because Dash is primarily a frontend library — there are far more lines of JavaScript (Typescript) than Python, R, or Julia code. Plotly only has 3 full-time Python developers, 2 full-time R developers, and 0 full-time Julia developers.

      Who works behind Plotly/Dash: 50 engineers:

      • 45 JavaScript (?)
      • 3 Python
      • 2 R
      • 0 Julia
    2. Behind the scenes, when a Python, R or Julia engineer creates a Dash app, they are actually creating a React Single Page Application (“SPA”).
    3. With Dash, any open-source React UI component can be pulled from npm or GitHub, stirred with water, transmogrified into a Dash component, then imported into your Dash app as a Python, R, or Julia library. C’est magnifique! 👨‍🍳 Dash makes the richness and innovation of the React frontend ecosystem available to Python, R, and Julia engineers for the first time.

      Dash components are based on React

  6. Mar 2020
    1. Currently Shiny is far more mature than Dash. Dash doesn’t have a proper layout tool yet, and also not build in theme, so if you are not familiar with Html and CSS, your application will not look good (You must have some level of web development knowledge). Also, developing new components will need ReactJS knowledge, which has a steep learning curve.

      Shiny > Dash:

      • Dash isn't yet as stabilised
      • Shiny has much more layout options, whereas in Dash you need to utilise HTML and CSS
      • developing new components in Dash needs ReactJS knowledge (not so easy)
  7. Feb 2020
    1. grammar : a punctuation mark — that is used especially to indicate a break in the thought or structure of a sentence
  8. Jan 2020