I am thinking to add a job board to my website to show all recent Computer Science positions. I looked at a few options like web scraping. but it will cost a lot. Is there any free or low cost option to access to the job listings? I found the Indeed API is not accessible any more.
https://developer.indeed.com/docs/publisher-jobs/job-search
There are some free and low-cost options to access job listings.
You can use CareerJet API, Adzuna API, Google Custom Search API where you can retrieve job listings for your job board. In most cases you need to sign up with them to retrieve job postings.
You can use RSS feed.
You can also partner with those job listing companies.
Related
I'm studying GCP and reading about different ways to communicate and manage cloud functions I end up wondering when to use each of the services that offer GCP.
So, I have been reading about GCP Composer, GCP Workflows, Cloud Pub/Sub and I don't see clearly when to use each one, or use simple HTTP calls.
I understand that it depends a lot on the application that you are building, but for example, If I'm building a payment gateway and some functions should be fired after the payment was verified, like sending emails, making not related business logic, adding the purchase to a sales platform. So which one should be the way I manage this flow and in which case would be better to use the others? Should I use events to create an async flow with Pub/Sub, or use complex solutions like composer and workflows? or just simple HTTP calls?
As always, it depends!! Even in your use case, it depends! Ok, after a payment you want to send an email, make business logic, adding the order to your databases,...
But, is all theses actions can be done in parallel, or you need to execute them in a certain order and if a step fails, you stop the process?
In the first case, you can use Cloud PubSub with 1 message published (payment OK) and then a fan out to several functions in parallel. Else, you can use workflow to test the response of the fonction and then to call, or not the following fonctions. With composer you can perform much more checks and actions.
You can also imagine to send another email 24h after to thank the customer for their order, and use Cloud Task to delayed an action.
You talked about Cloud Functions, but you also have other solutions to host code on GCP: App Engine and Cloud Run. Cloud function is, most of the time, single purpose. Sending an email is perfect for a function.
Now, if you have "set of functions" to browse your stock, view the object details, review the price, and book an object (validate an order "books" the order content in your warehouse), the "functions" are all single purpose but related to the same domain: warehouse management. Thus you can create a webserver that propose different path to manage the warehouse (a microservice for the warehouse if you prefer) and host it on CloudRun or App Engine.
Each product has its strength and weakness. You will also see this when you will learn about the storage on GCP. Most of the time, you can achieve things with several product, but if you don't use the right one, it will be slower, or cost much more.
I want to plan an architecture based on GCP cloud platform. Below are the subject areas what I have to cover. Can someone please help me to find out the proper services which will perform that operation?
Data ingestion (Batch, Real-time, Scheduler)
Data profiling
AI/ML based data processing
Analytical data processing
Elastic search
User interface
Batch and Real-time publish
Security
Logging/Audit
Monitoring
Code repository
If I am missing something which I have to take care then please add the same too.
GCP offers many products with functionality that can overlap partially. What product to use would depend on the more specific use case, and you can find an overview about it here.
That being said, an overall summary of the services you asked about would be:
1. Data ingestion (Batch, Real-time, Scheduler)
That will depend on where your data comes from, but the most common options are Dataflow (both for batch and streaming) and Pub/Sub for streaming messages.
2. Data profiling
Dataprep (which actually runs on top of Dataflow) can be used for data profiling, here is an overview of how you can do it.
3. AI/ML based data processing
For this, you have several options depending on your needs. For developers with limited machine learning expertise there is AutoML that allows to quickly train and deploy models. For more experienced data scientists there is ML Engine, that allows training and prediction of custom models made with frameworks like TensorFlow or scikit-learn.
Additionally, there are some pre-trained models for things like video analysis, computer vision, speech to text, speech synthesis, natural language processing or translation.
Plus, it’s even possible to perform some ML tasks in GCP’s data warehouse, BigQuery in SQL language.
4. Analytical data processing
Depending on your needs, you can use Dataproc, which is a managed Hadoop and Spark service, or Dataflow for stream and batch data processing.
BigQuery is also designed with analytical operations in mind.
5. Elastic search
There is no managed Elastic search service directly provided by GCP, but you can find several options on the marketplace, like an API service or a Kubernetes app for Google’s Kubernetes Engine.
6. User interface
If you are referring to a user interface for your own use, GCP’s console is what you’d be using. If you are referring to a UI for end-users, I’d suggest using App Engine.
If you are referring to a UI for data exploration, there is Datalab, which is essentially a managed notebook service, and Data Studio, where you can build plots of your data in real time.
7. Batch and Real-time publish
The publishing service in GCP, for both synchronous and asynchronous messages is Pub/Sub.
8. Security
Most security concerns in GCP are addressed here. Which is a wide topic by itself and should probably need a separate question.
9. Logging/Audit
GCP uses Stackdriver for logging of most of its products, and provides many ways to process and analyze those logs.
10. Monitoring
Stackdriver also has monitoring features.
11. Code repository
For this there is Cloud Source Repositories, which integrate with GCP’s automated build system and can also be easily synched with a Github repository.
12. Analytical data warehouse
You did not ask for this one, but I think it's an important part of a data analysis stack.
In the case of GCP, this would be BigQuery.
I am working with my team to prep a project for a potential client. We've researched Amazon MWS API, and we're trying to develop an algorithm using the data scraped from this API.
Just want to make sure we understand the research correctly:
Is it possible to scrape data from Amazon.com like the plugins RevSeller or HowMany do? Then can we add that data to a database for use in an algorithm to determine whether or not an Amazon reseller should invest in reselling a product?
Thanks!
I am doing a similar project. I don't know the specifics of RevSeller or HowMany, but another very popular plugin is Amzpecty. If you use a tool like Fiddler, you can see the HTTP traffic and figure out what it does. They basically scrape out the ASIN and offer listing ID's on the current page you are looking at and one-by-one call the Amazon Product Advertising API, which is not the same thing as MWS. Out of that data returned, they produce a nice overlay that tells you all kinds of important stuff.
Instead of a browser plugin, I'm just writing an app that makes HTTP calls based on a list of ASIN's to the PA API and then I can run the results through my own algorithms. Hope that gives you a starting point.
For my master thesis I have to develop a web service that constantly monitors user interaction in a web application (recording, for example, the most clicked buttons or the most visited pages). The main goal of this project is to generate a set of behavioral profiles.
I have some experience with web services, but I feel I need some sort of starting point with this kind of project (similar projects, existing thesis or articles). Hope someone can help.
Assuming you are talking about restFul web services, a good starting point would be to list down all APIs that you think you will need in terms of GET, POST, PUT, DELETE methods.
For example, you might first need a list of all the buttons, links and pages in the website you are supposed to monitor (lets say getAllItems). Then for such individual items, you need to code to capture the 'onclick', 'onbuttonpress' etc events (lets say getOnClickForButtonA). You will have to save all this information periodically in a database.
When you have enough information in the database, you can write code to read this and generate some stats out of it.
So, a set of services to gather all info.
Set of services to store all this info.
Set of services to analyze gathered info.
Hope this helps!
I operate a number of content websites that have several million user sessions and need a reliable way to monitor some real-time metrics on particular pieces of content (key metrics being: pageviews/unique pageviews over time, unique users, referrers).
The use case here is for the stats to be visible to authors/staff on the site, as well as to act as source data for real-time content popularity algorithms.
We already use Google Analytics, but this does not update quickly enough (4-24 hours depending on traffic volume). Google Analytics does offer a real-time reporting API, but this is currently in closed beta (I have requested access several times, but no joy yet).
New Relic appears to offer a few analytics products, but they are quite expensive ($149/500k pageviews - we have several times this).
Other answers I found on StackOverflow suggest building your own, but this was 3-5 years ago. Any ideas?
Heard some good things about Woopra and they offer 1.2m page views for the same price as Relic.
https://www.woopra.com/pricing/
If that's too expensive then it's live loading your logs and using an elastic search service to read them to get he data you want but you will need access to your logs whilst they are being written to.
A service like Loggly might suit you which would enable you to "live tail" your logs (view whilst being written) but again there is a cost to that.
Failing that you could do something yourself or get someone on freelancer to knock something up for you enabling logs to be read and displayed in a format you recognise.
https://www.portent.com/blog/analytics/how-to-read-a-web-site-log-file.htm
If the metrics that you need to track are just limited to the ones that you have listed (Page Views, Unique Users, Referrers) you may think of collecting the logs of your web servers and using a log analyzer.
There are several free tools available on the Internet to get real-time statistics out of those logs.
Take a look at www.elastic.co, for example.
Hope this helps!
Google Analytics offers real time data viewing now, if that's what you want?
https://support.google.com/analytics/answer/1638635?hl=en
I believe their API is now released as we are now looking at incorporating this!
If you have access to web server logs then you can actually set up Elastic Search as a search engine and along with log parser as Logstash and Kibana as Front end tool for analyzing the data.
For more information: please go through the elastic search link.
Elasticsearch weblink