I have a setup on a Raspberry Pi (with its native camera) that uses a cronjob to start an ffmpeg session with its output streaming to YouTube. I re-use the same stream key each time, which is written into my ffmpeg scripts. This all works perfectly each week, automatically starting and stopping at the desired time.
However, each week PRIOR to that livestream, I have to "manually" go into YouTube Studio and "schedule" a new future event. This is easy enough, since it lets me "reuse" previous settings -- all I have to change is the Title, date, and time. But I would love to figure out a way to automate that part of the process, as well. I assume it involves using the YouTube Data API, but I'm not well versed in API's, JSON, etc.
(I do have a strong Linux background, bash scripting skills, and general programming background.)
My final solution just needs to:
create the new scheduled event (maybe 12 hours prior to going live), with Title, Date, Time, "Unlisted" status, category, and so forth -- all the usual settings I do manually within Studio
retrieve the assigned URL for the upcoming stream (my script will then email that to me)
So, basically, I'm asking for help getting started with the API, or whatever method is capable of doing this. I would prefer to code it on the same Pi that does the ffmpeg encoding (although in a pinch, I could create the schedule from another computer, even Windows). Any examples would be great.
So far, all I have done is create my Google project, enable the YouTube Data API in the project, and create my API key. But I'm not sure where to go from there.
If Python as implementation language suites you, then I'd recommend to use the Google's APIs Client Library for Python.
Basically, this library is of good quality and (compared to other client libraries) simple to use. It will, for example, insulate you from having to deal explicitly with REST API calls, JSON and the like. Your code will also work under both GNU/Linux and Windows.
You may begin your journey by reading the official getting started doc: YouTube Live Streaming API Overview. Then I recommend absorbing these two important documents: Life of a Broadcast and Understanding Broadcasts and Streams.
Then go read, understand and run the following sample program from Google: create_broadcast.py. Of course, you'll have to adapt that code to your use case.
You'll have to exercise patience and perseverance (since you say you have no prior experience using the YouTube Data API). This API is non-trivial, but it'll pay off to you at the end of your (programming) journey (you mentioned to be versed in programming).
A special mention: for to be able to call the live streaming APIs you will first need to get acquainted with the things related to the so-called OAuth 2.0 authorization and authentication: Implementing OAuth 2.0 Authentication. There's an official document that you need absorb: OAuth 2.0 for Mobile & Desktop Apps.
A few more references: the live streaming API has an official documentation too. The main site documenting the client library is: Google API Client Library for Python Docs. Its source is public, to be found within the client library's public repo under the directory docs.
Also useful is to see the YouTube Data API's list of all instance methods.
Related
I am working on a desktop application using GCP Speech-to-Text API to perform streaming recognition. I'm using Python 3 and Google client libraries, google.cloud.speech. I've started off the transcribe streaming infnite Python sample and built around those concepts, and everything works nicely. I'm now trying to get to the end user access question, as I'm currently using a service account file for development purposes, which I'm obviously not willing to distribute to all users.
Basically, how do I give access to my end users to the Speech-to-Text service for streaming recognition in the least intrusive way possible? I have no need for accessing storage or the like, as I don't access buckets contents and stream all audio directly. I actually don't need any user information, I only need GCP to process the STT requests and send me the responses.
I see 2 solutions that should work on paper, out of the three the documentation mentions (I leave out the service account file ones):
API key
OAuth2
API key
API keys sound like my dream option: it's simple, doesn't require user interaction past initial setup, I can manage such keys in GCP's console, and it should be able to grant access to what I need (as I effectively don't need any user info, an account is mostly irrelevant).
However, how to use an API key using the Google Speech client library totally eludes me. I can see a PUB/SUB Go example, but I can't find any mapping to Python. I'm not even 100% sure it can work, as the Go documentation for the option seems to note it only works for JSON-over-HTTP, and I believe the client library for Speech-to-Text is using gRPC.
Yet, at least with a JSON non-streaming recognize request, I can use such an API key, and successfully did so manually using cURL on the command-line. So I still have a little bit of hope, in case the gRPC restriction either isn't true or doesn't concern my use case.
This part's question would summarize as: "how do I specify an API key using the Python SpeechClient?".
OAuth2
This sounds like my second-best option, as it uselessly asks the user for authentication while I don't actually need any personal data. Yet, I still have serious issues I'm struggling to overcome:
How do I reliably store info that prevent me from having to re-ask the user for authorization every single time the app runs? google_auth_oauthlib's InstalledAppFlow doesn't seem to provide such feature, so I'm rolling my own based on google.oauth2.credentials.Credentials.from_authorized_user_file() after having saved them with the to_json() the first time I obtained them with InstalledAppFlow. I'm however confident this will not last, and I'm really not sure how to check whether the credentials are still good before I fail to use an API with them (e.g. I can't seem to be able to rely on Credentials.valid before they actually get used).
There seem to be no specific Speech-to-Text scopes, and the required one is way broader than what I need, leading to an overly complex and frightening authorization request. And no, without this scope I cannot access the Speech-to-Text API, I tried :)
Summary
To summarize: what is my best and least-intrusive option to provide credentials to be able to use GCP Speech-to-Text in my desktop application?
First my apologies if this is a dumb question, or has been asked before. I've been searching for a couple of days and can't find an answer. This usually means I'm asking a dumb question. ;-)
I have a rPi and touchscreen in my kitchen; it displays helpful things like appointments for next 7 days, weather next 7 days, news headlines, etc. It's a web app I wrote in Angular 7, and it queries a NodeJS v8 backend which I also wrote. This was a hobby project to learn Angular and Node.
The Node app performs all interactions with the outside world, using Google's Calendar API to get appointments, Yahoo Weather API, newsapi.org. All of these integrations followed the same pattern -- obtain some apikey token, and use that when invoking some API method to get the requested data in a JSON wad.
Now, I would like to also get the grocery list from my Echo. After reviewing Amazon's Alexa API documentation, it doesn't appear that I can do this the same way as the previous three integrations I did. Must I really write a "skill" for this, though I never intend to invoke it on the Echo?
And if so, could you point to a decent sample? None of the samples provided by Amazon utilize the Lists API.
Yes, you must create a skill in order to receive access_token. And then - Out of Session Interaction feature might be useful.
Im looking to work on some of the public datasets available on Kaggle.
Is it possible to access kaggle datasets through its API using RStudio??
cheers,
sup
Kaggle just launched their public API in February 2018 (so earlier this year). According to their Github repository, Kaggle/kaggle-api, Kaggle has (at least to date) made their API accessible "using a command line tool implemented in Python".
I too was excited to discover the existence of Kaggle's API, and, similarly, was also interested if someone had written an API wrapper package for interfacing with Kaggle's API in R. I couldn't find anyone who had, so I wrote one myself, which you can find here: https://github.com/mkearney/kaggler. It's literally been less than a week since I created the repo, so I can't speak to its reliability yet, but that for now it appears to be the best place to start. And, for the record, as long as people are willing to use it, I have every intention of maintaining at least minimal levels of support for the package (assuming no enthusiastic third parties step in with their own R packages), but the API itself is new so it could still be a few months before there is any real stable option.
;;
Also, although I understood exactly what you meant by your question, I think it's worth pointing out that, technically, Rstudio is an integrated development environment (IDE) and not necessarily the source/library/program that connects you to non-Rstudio web APIs. What you're actually looking for is an R extension/library/package that is designed to act as a wrapper/client/interface for Kaggle's API. Of course, this distinction is mostly trivial because if you work in Rstudio (an excellent, open-sourced R-centric IDE) to communicate with external API's like Kaggle's, then you are "access[ing] kaggle datasets through its API using RStudio". But for the sake of giving credit where credit is due, it'd be more accurate to say that you are hoping to leverage {Rstudio} and the {pkgname} package to communicate with Kaggle's API via the R environment.
I'm sure many of you are familiar with the IBM i5 series emulator (looks like this poop)
My company uses this religiously and there is no Biz logic in it so anytime somone in our finance dpt makes a human error it accepts it and adds it to the database. Not to mention its ugly, hard to use, not intuitive, etc....
I would like to create a frontend for this interface so that we can control the logic before its submitted to the system (we dont control the system itself) so in effect I need to make my own emulator app.
However I cant seem to find any information on how to interface with the i series, namely login, send commands, and view or gather data from the screens it would normally send back.
Any suggestions?
The problem is not the iSeries but the software package your company is running on it.
There ARE advantages to use green screens: it's fast and it's almost unbeatable at data entry, provided you get used to it.
But to answer your question, the iSeries is a J2EE enabled machine: a HTTP server comes installed and depending of the version of the iSeries, WebSphere might be already installed, or are entitled to install it. Then you can use JT400, which is the java toolkit for the os400 containing the jdbc drivers to connect the database and the necessary classes for calling programs.
If you prefer php, there is a flavor of the Zend framework made to work on the iSeries but I never tried it.
I'd recommend that you take a look at both the Attachmate Verastream Host Integrator (VHI) and IBM's Host Access Transformation Services (HATS) products. They effectively just screen scrape the green screen terminals to allow you to pull and push data and provide macro recording and editing tools to automate the process. App integration can be achieved via web services or html/jsp/servlet programming (plus .Net for VHI and EJB's for HATS). They do come with enterprise pricing however which may be an obstacle for some. They do have free trial offerings for evaluation purposes to help determine if they are an appropriate solution to your problem.
What software packages are they using? Most programs that I use in the 5250 emulator has some business logic that error checks the data before adding it to the database. Can you get us some more information so we can direct you in a better direction.
There are vendors that sell products that screen-scrape the 5250 data stream and produces a web front-end. Or you can write your own front-end in the language of your choice and just do SQL calls to the database.
THere's got to be some source code. Start by looking at the menu and menu option your users are accessing and figure that's running behind them.
Use command STRPDM to look for source code - look in different libraries (they are like folders)
You might have source code in a "member" called something like xxxMNUSRC xxxRPGSRC (rpg program source) or xxxCLSRC (cl programs), xxxDDSSRC (display/screen source, physical/logical file source)
Objects a "compiled" objects such as files (tables), screens, priter files (reports)
Stay away from Qxxx and #xxx libraries - those are system libraries.
http://systeminetwork.com/ is a good resource for iSeries related questions.
I'm doing a language web site for my university language center, where students login and see videos to learn English. i have to do it like this,
person is logging in to the system, search using a search area and find the details,lessons and videos relevant to that videos. this functionality exactly matches the youtube scenario.
for implementing twitter like functionality we can use status-net, is there a similer library, statusnet like famous implementation for youtube or a some kind of platform or a framework like codeigniter that we can use to implement youtube like site very easily??
please suggest some options?? a open source one or a commercial one ???
and what is the best video format to use in a such web site?? flv?? mp4?? or mov???
regards,
Rangana
Your best option is to use a 'cloud' based video processing service. Most have a sample project / library for many different languages and frameworks. Here is a list of a few I've tried and liked:
http://zencoder.com/
http://transloadit.com/
http://pandastream.com/
The typical steps involve uploading the video files to a large 'cloud' static asset host (such as S3) through the browser. If you are inexperienced it is best to select a processor that provides an uploader (it will handle putting the files in the right spot). Of the three, Transloadit and Panda both have custom unloaders.
Usually the service will allow you to either pass the encoding settings (what formats and qualities to) output to as parameters or configure them in your account. To support all current HTML5 browsers you just need H264 (.m4a) and OGG (.ogv). However, the new trend in the video world is for WEBM (.webm) so you might want to include it as well.
Next you will receive a unique code from the web service that you must store in persistent storage (database). The web service can be configured to 'callback' (perform an HTTP POST or GET request to your service) once the video is encoded.
Once your recieve a callback you can activate your video and start dislpaying it on your pages. For displaying, if you are inexperienced I'd highly recommend you use one of the following players:
http://sublimevideo.net/
http://longtailvideo.com/
http://videojs.com/
They all do similar things for different prices. My current personal favourite is Sublime Video (it offers cool light box effects and a gorgeous player).
Why do you have to re-implement Youtube when you can just use it for hosting your videos for free? Many online e-learning portals (e.g. Khan academy) do exactly that.
As far as the best video format to use -- go read about H.264/AVC. It's what Youtube currently uses.
I think you will not find already built solution ;)
But it's not really that hard. You can use existing frameworks that will make your life easier while you build account management system, the rest shouldn't be really that hard (assuming you don't really want to re-build the whole Youtube ;D ).
For playing videos, you can use JW Player. A great piece of software, you should check it out.