Learning Python quickly does not mean memorizing the whole language. It means building a sequence of small programs that force you to use the most important ideas.
Start with values, variables, strings, numbers, booleans, conditionals, and loops. Then learn functions so repeated logic has a name and a testable boundary. After that, practice lists, dictionaries, sets, and tuples with real data rather than isolated exercises.
The next stage is practical Python: read a text file, parse JSON, call an HTTP API, handle exceptions, and write results to a new file. Use a virtual environment from the beginning so installing a package becomes a normal project skill rather than a later repair job.
Build three small projects: a command-line expense tracker, a file-organizing utility, and an API-powered report. Keep each project small enough to finish in a weekend. When stuck, reduce the problem to the smallest input that reproduces the behavior, read the error message, and test one assumption at a time.
After the basics, learn Git, testing with unittest or pytest, and basic debugging. These skills make you productive even before you know a web framework or data-science library.