mashroom | Mashroom Server , an Integration Platform for Microfrontends | Runtime Evironment library
kandi X-RAY | mashroom Summary
kandi X-RAY | mashroom Summary
Mashroom Server is a Node.js based Microfrontend Integration Platform. It supports the integration of Express webapps on the server side and composing pages from multiple Single Page Applications on the client side (Browser). It also provides common infrastructure such as security, communication (publish/subscribe), theming, i18n, storage, and logging out of the box and supports custom middleware and services via plugins. Mashroom Server allows it to implemented SPAs (and express webapps) completely independent and without a vendor lock-in, and to use it on arbitrary pages with different configurations and even multiple times on the same page. It also allows it to restrict the access to resources (Pages, Apps) based on user roles. From a technical point of view the core of Mashroom Server is a plugin loader that scans npm packages (package.json) for plugin definitions and loads them at runtime. Such a plugin could be an Express webapp or a SPA or more generally all kind of code it knows how to load, which is determined by the available plugin loaders. Plugin loaders itself are also just plugins, so it is possible to extend the list of known plugin types.
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Top functions reviewed by kandi - BETA
- Main entry point .
- Sort the given header entries
- Returns an array of header entries in a node .
- Push to the to .
- Constructs a TOC entry .
- Returns an array of header entries in the node .
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QUESTION
I have around 70 categories (it can be 20 or 30 also) and I want to be able to parallelize the process using ray but I get an error:
...ANSWER
Answered 2021-Feb-18 at 01:31This error is happening because of sending large objects to redis. merged_df
is a large dataframe and since you are calling get_meal_category
10 times, Ray will attempt to serialize merged_df
10 times. Instead if you put merged_df
into the Ray object store just once, and then pass along a reference to the object, this should work.
EDIT: Since the classifier is also large, do something similar for that as well.
Can you try something like this:
QUESTION
I have following dataframe in Pandas
...ANSWER
Answered 2020-Jul-31 at 07:51You can use apply of pandas from https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html on index. Sharing a similar simpler example, here if your pipe containing string has duplicate labels the following will not work.
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