Lodash Differences¶

Naming Conventions¶

pydash adheres to the following conventions:

Function names use snake_case instead of camelCase.
Any Lodash function that shares its name with a reserved Python keyword will have an _ appended after it (e.g. filter in Lodash would be filter_ in pydash).
Lodash’s toArray() is pydash’s to_list().
Lodash’s functions() is pydash’s callables(). This particular name difference was chosen in order to allow for the functions.py module file to exist at root of the project. Previously, functions.py existed in pydash/api/ but in v2.0.0, it was decided to move everything in api/ to pydash/. Therefore, to avoid import ambiguities, the functions() function was renamed.
Lodash’s is_native() is pydash’s is_builtin(). This aligns better with Python’s builtins terminology.

There are a few differences between extra callback style support:

Pydash has an explicit shallow property access of the form ['some_property'] as in pydash.map_([{'a.b': 1, 'a': {'b': 3}}, {'a.b': 2, 'a': {'b': 4}}], ['a.b']) would evaulate to [1, 2] and not [3, 4] (as would be the case for 'a.b').

In addition to porting Lodash, pydash contains functions found in lodashcontrib, lodashdeep, lodashmath, and underscorestring.

Some of pydash’s functions behave differently:

pydash.utilities.memoize() uses all passed in arguments as the cache key by default instead of only using the first argument.