Tag: Python
-
Pandas datetime filtering: Rows before now with pd.Timestamp.now()
Have a Python Pandas series with datetime values, and want all those until now? Compare with pd.Timestamp.now(): This returns the rows from df where the “when” column is before now.
-
Pandas .str.contains: Finding and filtering rows by substring
Want to check whether a Python Pandas series contains another string? Use .str.contains: This returns a boolean series, whose index matches that of df. Keep only those rows containing ‘a’:
-
Python keyword-only parameters: Setting default values
Keyword-only parameters in a Python function can have a default: Now call it: Remember: parameters with defaults come *after* those without.
-
Python keyword-only parameters: Using * and *args in def
Any Python function parameters after *args are keyword-only: Want to give k a value? Use a keyword argument: Don’t need *args? Just use *, and k is keyword only:
-
Type hints for *args in Python: Annotate the element type
How to annotate *args in Python? Just set the elements’ type; we know it’s a tuple: Normally, tuples contain different types. In args, we assume all values have the same type.
-
Python *args: Collecting positional arguments into a tuple
Classic use of Python’s *args: Invoke it with separate int arguments: and *not* with a list containing ints:
-
Python *args: Accepting any number of positional arguments
Want your Python function to take any number of positional args? Use *args: – Can be any name, but args is traditional– The * is only in the function definition– It’s a tuple– Don’t grab elements by index; iterate over them– It might be empty– Pronounce it “splat args”
-
Positional vs keyword arguments in Python function calls
How are arguments assigned to parameters when calling a Python function? There are two ways: – Positional, based on order– Keyword, i.e., name=value, assigned by name Want to mix and match? Fine, but all positional must come before all keyword:
-
Python 3.15 lazy imports: Deferring module load until first use
Every import in Python executes the module, from start to finish. Meaning? Big modules slow down your program’s startup time. Coming in Python 3.15 this October: “lazy import”, which delays the load until a name is used: lazy import MODULElazy from MODULE import NAME
-
Python dict keys: Why custom objects work but lists don’t
Mutable builtins in Python cannot be dict keys. But your (mutable) classes can!