Skip to main content

Gtalk 'Labs Edition' launched

After toying a lot with IM features in GMail and Google Desktop Gtalk Gadget, Google finally released new version of Gtalk, named 'Gtalk Labs Edition'. This is second release of popular IM client which has given Yahoo! Messenger, AIM and MSN Messenger a run for their money. The success was due to extremely light weight size, a clean and easy interface and simplicity in use.

All of these features seem to be on their way out, if Labs edition is any indicator. I remember the earliest version of Gtalk was 900 kb. The one I have got installed is 3.5 MB. Labs edition is more than 8 MB. However install is still very fast and simple as compared to any other IM client. The interface seems a little crowded but still is passable!

Most of the features of Gtalk Desktop gadget have been incorporated in this version. So you have group chat, tabbed conversations and what I wanted most: good smilies :) There is tighter integration with Orkut and Calendar and you can even
snooze Calendar notifications, just like you do in your Calendar
desktop gadget.

However the big minus: no voice chat and file transfers! If you have to use these, install the normal Gtalk. Though you can run both of them simultaneously without any problem (if you learn how to make out, which is which since the tray icons are same!) Google recommends to have any one of them.

This is currently available only for Windows XP and Vista in English language only. Gtalk Labs Edition can be downloaded here: http://www.google.com/talk/labsedition/index.html

Give it a try. See if you like it.

PS:More I use it, more I dislike it. The worst feature is that you can't copy whatever you have already sent, which was such a nifty feature in Gtalk.


Technorati Tags: , ,

Comments

Popular posts from this blog

How to upload to Google Cloud Storage buckets using CURL

Signed URLs are pretty nifty feature given by Google Cloud Platform to let anyone access your cloud storage (bucket or any file in the bucket) without need to sign in. Official documentation gives step by step details as to how to read/write to the bucket using gsutil or through a program. This article will tell you how to upload a file to the bucket using curl so that any client which doesn't have cloud SDK installed can do this using a simple script. This command creates a signed PUT URL for your bucket. gsutil signurl -c 'text/plain' -m PUT serviceAccount.json gs://test_bucket_location Here is my URL: https://storage.googleapis.com/test_sl?GoogleAccessId=my-project-id@appspot.gserviceaccount.com&Expires=1490266627&Signature=UfKBNHWtjLKSBEcUQUKDeQtSQV6YCleE9hGG%2BCxVEjDOmkDxwkC%2BPtEg63pjDBHyKhVOnhspP1%2FAVSr%2B%2Fty8Ps7MSQ0lM2YHkbPeqjTiUcAfsbdcuXUMbe3p8FysRUFMe2dSikehBJWtbYtjb%2BNCw3L09c7fLFyAoJafIcnoIz7iJGP%2Br6gAUkSnZXgbVjr6wjN%2FIaudXIqA...

Running Apache Beam pipeline using Spark Runner on a local standalone Spark Cluster

The best thing about Apache Beam ( B atch + Str eam ) is that multiple runners can be plugged in and same pipeline can be run using Spark, Flink or Google Cloud Dataflow. If you are a beginner like me and want to run a simple pipeline using Spark Runner then whole setup may be tad daunting. Start with Beam's WordCount examples  which help you quickstart with running pipelines using different types of runners. There are code snippets for running the same pipeline using different types of runners but here the code is running on your local system using Spark libraries which is good for testing and debugging pipeline. If you want to run the pipeline on a Spark cluster you need to do a little more work! Let's start by setting up a simple standalone single-node cluster on our local machine. Extending the cluster is as easy as running a command on another machine, which you want to add to cluster. Start with the obvious: install spark on your machine! (Remember to have Java a...

Example of Using SimpleHttpOperator to make POST call

Airflow has SimpleHttpOperator which can be used to invoke REST APIs. However using this operator is not exactly straightforward. Airflow needs to be told about the connection parameters and all the other information that is needed to connect to external system. For this we need to create Connections. Open 'Connections' page through Admin->Connections link.  Expand the dropdown to see the various types of connection options available. For a REST call, create an HTTP connection. Give the host URL and any other details if required. Now when we write our task using SimpleHttpOperator we will need to refer to the connection that was just created. The task below is making a post call to  https://reqres.in/api/users  API and passing it some data in JSON format. myHttpTask = SimpleHttpOperator(  task_id='get_op',  method='POST',  http_conn_id='dcro',  data=json.dumps({    "name":"Morpheus",    " job ":" L...