Google Translate API demo tested with Python 3.9.x. I want to say this may not work so well with Python 3.10 for some reason but if you follow the guide I referenced otherwise, you should be in business. Highly recommended that you create a new Python environment before engaging with any serious development if you haven't done so.

google_translate_api_demo.ipynb

One limitation with TextBlob sentence tokenizer is that it really only works great in latin-based languages and stumbles a bit with multi-byte punctuation such as Cyrillic, Hanzi/Phono-semantic, and Asian-based UTF-8 strings. This is where spaCy is a better choice but this requires a bit more planning to setup and execute since you have to load more libraries and deal with context a bit more selectively. So, if you have a specific care you want to handle, you should be able to extend the above examples with a switch statement to use better sentence handling prior to translation.

Here's a good starting point if you want better sentence handling for non-latin based languages:
https://spacy.io/api/sentencizer

An example of using this (on English at least):

nlp  = spacy.load('en_core_web_sm') # See supported language models here: https://spacy.io/usage/models
doc = nlp(text)
for sent in doc.sents:
    print(sent.text)