I finished Foundations. What does this track add?
The second layer of primitives. Foundations gave you variables, control flow, lists, dicts, functions, comprehensions on small in-memory inputs. Patterns adds the primitives that show up the moment your script touches real data: opening files, handling errors, parsing CSV and JSON, working with dates, and a richer toolbelt for functions and dicts.
Same shape as Foundations? Same way of teaching?
Identical. Each lesson teaches one concept on the smallest possible input — a generic list of numbers, a 3-row CSV, a tiny JSON dict. No work-app contexts. No products. By day 30 you'll have the kit needed to write a 100-line script that reads a file, transforms it, handles failures, and writes output.
And the questions below?
Six prompts on the concepts this track teaches. Rate each from 1 (strongly disagree) to 5 (strongly agree) based on where you are today. The same six come back on day 30 — the delta is the answer to "did this track work for me?"
Foundations covered the smallest pieces — print, variables, types, conditionals, loops, lists, dicts, functions, list/dict comprehensions, basic try/except, basic file reading. Patterns goes one level deeper.
Week 1 — Files and errors as first-class concerns. open modes, the with statement, the specific exception types you'll meet (KeyError, ValueError, FileNotFoundError), and list comprehensions with filters.
Week 2 — Function patterns and dict patterns. Default arguments, keyword arguments, *args / **kwargs, dict comprehensions, nested dicts, and the import system for pulling in the standard library.
Week 3 — Standard-library data formats. csv.DictReader for CSV files, json.load / json.dump for JSON, re.search / re.findall for regex, sorted(key=...) for ranking, datetime for parsing dates. Week ends with a synthesis that composes 6 prior primitives on a generic CSV.
Week 4 — The everyday toolbelt. pathlib for paths that work on every OS, **dict for argument forwarding, enumerate and zip for cleaner iteration, slicing for fast list/string surgery, defaultdict and Counter from collections, and one final synthesis.
Deferred to Python Mastery (track 3): classes, decorators, generators, custom context managers, type hints, pytest, async/await, packaging.
None of those are needed to do real work with files, errors, dicts, and the standard library. You'll have enough.
Rate each statement honestly. Don't research, don't guess what the right answer should be. The same prompts return on day 30 — the delta is yours to keep.
I finished Foundations. What does this track add?
The second layer of primitives. Foundations gave you variables, control flow, lists, dicts, functions, comprehensions on small in-memory inputs. Patterns adds the primitives that show up the moment your script touches real data: opening files, handling errors, parsing CSV and JSON, working with dates, and a richer toolbelt for functions and dicts.
Same shape as Foundations? Same way of teaching?
Identical. Each lesson teaches one concept on the smallest possible input — a generic list of numbers, a 3-row CSV, a tiny JSON dict. No work-app contexts. No products. By day 30 you'll have the kit needed to write a 100-line script that reads a file, transforms it, handles failures, and writes output.
And the questions below?
Six prompts on the concepts this track teaches. Rate each from 1 (strongly disagree) to 5 (strongly agree) based on where you are today. The same six come back on day 30 — the delta is the answer to "did this track work for me?"
Foundations covered the smallest pieces — print, variables, types, conditionals, loops, lists, dicts, functions, list/dict comprehensions, basic try/except, basic file reading. Patterns goes one level deeper.
Week 1 — Files and errors as first-class concerns. open modes, the with statement, the specific exception types you'll meet (KeyError, ValueError, FileNotFoundError), and list comprehensions with filters.
Week 2 — Function patterns and dict patterns. Default arguments, keyword arguments, *args / **kwargs, dict comprehensions, nested dicts, and the import system for pulling in the standard library.
Week 3 — Standard-library data formats. csv.DictReader for CSV files, json.load / json.dump for JSON, re.search / re.findall for regex, sorted(key=...) for ranking, datetime for parsing dates. Week ends with a synthesis that composes 6 prior primitives on a generic CSV.
Week 4 — The everyday toolbelt. pathlib for paths that work on every OS, **dict for argument forwarding, enumerate and zip for cleaner iteration, slicing for fast list/string surgery, defaultdict and Counter from collections, and one final synthesis.
Deferred to Python Mastery (track 3): classes, decorators, generators, custom context managers, type hints, pytest, async/await, packaging.
None of those are needed to do real work with files, errors, dicts, and the standard library. You'll have enough.
Rate each statement honestly. Don't research, don't guess what the right answer should be. The same prompts return on day 30 — the delta is yours to keep.
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