pip install td.client | Command Usages and Alternative

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pip install td.client is the command to install the latest version for Treasure data API. Actually, this is a great framework for the Customer Data Platform.  This CDP puts 360 aspects of customer data. Well, the scope of this article is to see the functionality of the above command with its variations and alternative. So let’s begin.

pip install td.client –

1. Usages  td-client –

Let’s run the above command. As I explained to you already, it installs the latest version for the td-client. At the time of publishing this article, the latest version for td-client is 1.2.1. But maybe when you are reading this article, The latest version can be changed. Hence this can cause incompatibility with any code base which u found on the internet randomly. So please take care.

installing td-client
installing td-client

 

2. Platform Variation with td-client  –

The same command fails sometimes in a specific environment. It is because it needs admin rights to run the command. Now you need to follow the below tricks to deal with such errors.

Window platform – We need to open cmd in administration mode and then run the above command.

Linux or Unix-based environment –  Typically we configure servers with Linux or a similar environment. All we need to add sudo keyword before the command. It provides admin rights.

 

3. Version Specification with td-client-

As I explained, the above command installs the latest version. It is rare but sometimes it causes incompatibility. Here we need a specific version for the module. Using pip we can achieve like below-

pip install td-client==1.2.0

Here we specifically mentioned the version as 1.2.0. If we call without the version, then it installs and 1.2.1 ( because currently, the latest version is 1.2.1).

td-client installation version specific
td-client installation version specific

 

I hope now most of the aspects of installing the td-client package is now clear to you. In case you need more assistance, feel free to drop an email or comment back to us.

Thanks 

Data Science Learner Team

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