podcasts | Podcast generator written in Go | Audio Utils library
kandi X-RAY | podcasts Summary
kandi X-RAY | podcasts Summary
Podcast generator written in Go.
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Top functions reviewed by kandi - BETA
- formatDuration formats a time . Duration as a string .
- Image adds an image to the feed
- NewFeedURL sets a new feed URL
- MarshalXML marshals Duration to XML
- Owner sets the owner of the feed
- Summary sets the Summary
- Subtitle sets the subtitle
- Author option sets the author
- Block sets the block to true
- Complete sets the complete flag
podcasts Key Features
podcasts Examples and Code Snippets
Lines of Code : 103License : Permissive (MIT)
Copypackage main
import (
"log"
"os"
"time"
"github.com/jbub/podcasts"
)
func main() {
// initialize the podcast
p := &podcasts.Podcast{
Title: "My podcast",
Description: "This is my very simple podcast.",
Language: "EN",
Li Community Discussions
Trending Discussions on podcasts
QUESTION
I'm trying to create a side NavBar(with Bootstrap 5) which I achieved but my text is being hidden behind the navbar. Any tips on how I can fix this?
This is my code for side Navbar:
...ANSWER
Answered 2022-Mar-17 at 22:12Using position: fixed; removes this element from the normal content flow.
This means that the element can now be on top (or under) other elements and is relatively positioned to the body.
If you want to display both besides each other, you're best bet would be to have another flex container around (instead of a fragment).
Here's an example: https://codesandbox.io/s/sharp-mclean-tpropv
QUESTION
I'm implementing authentication to my React project and I'm trying to have the Login form in my Home component. This is how my Home component looks with the Login component attached to it.
...ANSWER
Answered 2022-Jan-09 at 16:51In react-router-dom version 6 useHistory() is replaced by useNavigate()
QUESTION
I downloaded my personal Spotify data from the Spotify website. I converted these data from JSON to a regular R dataframe for further analysis. This personal dataframe has 4 columns:
...ANSWER
Answered 2022-Mar-01 at 14:13It looks like your issue is in artist_id = '', so try the below code to see if it helps get you started (since I don't have reproducible data, not sure if it will help). In this case it should just skip the podcasts, but I'm sure some more codesmithing will allow you to put relevant data in the given list position.
QUESTION
I have a 'shows' screen which has a list of shows, clicking goes to a show detail page. On the detail page, it has 3 tabs, but one is hidden if feedurl is blank. This throws an error when navigating to various shows that have feedurl's and then don't have feedsurls:
...ANSWER
Answered 2022-Feb-04 at 14:07Could you please try replacing your .Screen code with this? I never used react native or react navigation but this is what I found with a little bit of research.
QUESTION
I want to receive the data from this link: https://rapidapi.com/DIlyanBarbov/api/crypto-news-live/
This is my objects:
...ANSWER
Answered 2021-Dec-17 at 17:07With a model such as
QUESTION
I'm using the Listen Notes podcast-api in Next.js api routes. I want the user query from my front-end form to interact with the Next.js api. So when a user inputs "history", it will send that to the api to look for podcasts that are about that topic. I tried adding params to axios request but that doesn't seem to work.
Front-end:
...ANSWER
Answered 2021-Dec-02 at 18:15Check if API on you NextJs app, is receiving correctly the environment variable process.env.REACT_APP_API_KEY. Use console.log to test.
Reference : https://nextjs.org/docs/basic-features/environment-variables
Another check is the API path, cause NextJs use your own method to path this, you know ?!
Reference : https://nextjs.org/docs/api-routes/introduction
Hope this tips help you ;)
QUESTION
so I have created custom post types in WordPress called podcasts with different packages and most of it has been completed now what I'm trying to do is to "get each available podcast / item title underneath the package" for example I've 3 packages called Basic, Starter and Exclusive and I want to display all items available in Basic package underneath the Basic Bundle and same for Starter and Exclusive. I have mentioned the code below currently it's showing all the item titles.
...ANSWER
Answered 2021-Nov-13 at 03:35I guess this is what you're looking for
QUESTION
I have a 2-million long list of names of Podcasts. Also, I have a huge text corpus scraped from a sub-Reddit (Posts, comments, threads etc.) where the podcasts from our list are being mentioned a lot by the users. The task I'm trying to solve is, I've to count the number of mentions by each name in our corpora. In other words, generate a dictionary of (name: count) pairs.
The challenge here is that most of these Podcast names are several words long, For eg: "Utah's Noon News"; "Congress Hears Tech Policy Debates" etc. However, the mentions which Reddit users make are often a crude substring of the original name, for eg: "Utah Noon/ Utah New" or "Congress Tech Debates/ Congress Hears Tech". This makes identifying names from the list quite difficult.
What I've Tried: First, I processed and concatenated all the words in the original podcast names into a single word. For instance, "Congress Hears Tech Policy Debates" -> "Congresshearstechpolicydebates"
As I traversed the subreddit corpus, whenever I found a named-entity or a potential podcast name, I processed its words like this,
"Congress Hears Tech" (assuming this is what I found in the corpora) -> "congresshearstech"
I compared this "congresshearstech" string to all the processed names in the podcast list. I make this comparison using scored calculated on word-spelling similarity. I did this using difflib Python library. Also, there are similarity scores like Leveshtein and Hamming Distance. Eventually, I rewarded the podcast name with similarity score maximum to our corpus-found string.
My problem: The thing is, the above strategy is infact working accurately. However, it's way too slow to do for the entire corpus. Also, my list of names is way too long. Can anyone please suggest a faster algorithm/data structure to compare so many names on such a huge corpus? Is there any deep learning based approach possible here? Something like where I can train a LSTM on the 2 million Podcast names. So, that whenever a possible name is encountered, this trained model can output the closest spelling of any Podcast from our list?
...ANSWER
Answered 2021-Oct-31 at 03:08If exact text matching (with or without your whitespace removal preprocessing) is sufficient, consider the Aho-Corasick string matching algorithm for detecting substring matches (i.e. the podcast names) in a body of text (i.e. the subreddit content). There are many implementations of this algorithm for python, but ahocorapy has a good readme that summarizes how to use it on a dataset.
If fuzzy matching is a requirement (also matching when the mention text of the podcast name is not an exact match), then consider a fuzzy string matching library like thefuzz (aka fuzzywuzzy) if per query-document operations offer sufficient performance. Another approach is to precompute n-grams from the substrings and accumulate the support counts across all n-grams for each document as the fuzzyset package does.
If additional information about the podcasts is available in a knowledge base (i.e. more than just the name is known), then the problem is more like the general NLP task of entity linking but to a custom knowledge base (i.e. the podcast list). This is an area of active research and state of the art methods are discussed on NLP Progress here.
QUESTION
I'm fetching a Website, but all the Special Characters in the String from .getContentText() or .getContentText("UTF-8") are encoded as ’ and such. I've really run out of ideas, and to be honest don't quite understand at which point this Encoding happens. Thanks a lot for your help. I could solve it by "manually" replacing all the occurances, but that doesnt seem very clean.
...ANSWER
Answered 2021-Oct-18 at 09:09Your sample code suggests that you are retrieving the HTML source code of a specific page. That HTML source code uses ’ and friends, so the data will be in that format. It is unclear why you would need to decode those HTML entities.
If you really need to decode the HTML fully in Google Apps Script, you will need a parser of fairly respectable complexity. There are some shortcuts that you can try if your app has an HTML user interface of its own, but it would probably make more sense to use a library like the one by mathiasbynens.
If you only want to replace some HTML entities with their non-encoded equivalents, you may want to just use String.replace().
QUESTION
PyTorch has new functionality torch.inference_mode as of v1.9 which is "analogous to torch.no_grad... Code run under this mode gets better performance by disabling view tracking and version counter bumps."
If I am just evaluating my model at test time (i.e. not training), is there any situation where torch.no_grad is preferable to torch.inference_mode? I plan to replace every instance of the former with the latter, and I expect to use runtime errors as a guardrail (i.e. I trust that any issue would reveal itself as a runtime error, and if it doesn't surface as a runtime error then I assume it is indeed preferable to use torch.inference_mode).
More details on why inference mode was developed are mentioned in the PyTorch Developer Podcast.
...ANSWER
Answered 2021-Oct-13 at 16:54Yes, torch.inference_mode is indeed preferable to torch.no_grad in all situations where inference mode does not throw a runtime error.
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