[Tutor] Tensorflow Installation in Python Embedded Environment

[Swetha M]

Hi,

I recently came across an issue while installing tensorflow library on Python Embedded environment(64-bit).
During installation, there was a library - 'termcolor' which showed up as error saying, module does not exist.
Then I tried installing only termcolor library thinking there can be version issue with tensorflow package. Same Error came up.
Since it used a cached version I thought there was a compatibility contradiction with the python environment in my system.
I tried all means to remove cached version, didn't work. And I had anaconda running, so I thought there was some environment path clash and stuff while trying to download from http.

I opened another command prompt, installed termcolor in the python environment of me system and it was installed successfully.

Then in the previous command prompt where installation of termcolor was failing, I tried the same command and it was installed without any errors.
Then I installed tensorflow and it was installed successfully too.

Although I was able to install, I would really like to know the root cause of this issue. I have attached some screenshots for reference. I would really appreciate any help on this particular issue.

Just for your notice, same scenario experienced in lower versions of python embedded too. (3.7)

Also, I have a few general queries:
Are there any differences at all between python installed in the system and using embedded package?
Can I use heavy libraries like tensorflow in the embedded environment?
Are there any performance related differences between those two methods?

Any help on these queries would be very helpful.

Thank You,

Regards,
Swetha M


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