PyPI 官网下载 | atlantis-2021.7.21.tar.gz

# ***Atlantis*** ***Atlantis*** is a Python library for simplifying programming with Python for data science. # Installation You can just use pip to install Atlantis: `pip install atlantis` # Modules - [***collections***](#collections) helps with working with collections. - [***colour***](about_colour.md) simplifies using colours. - [***ds (datascience)***](#ds-data-science) provides tools for: - data wrangling, - validation, - tuning, - sampling, - evaluation, - clustering, and - parallel processing of machine learning models. - [***functions***](about_functions.md) manages higher order functions. - [***hash***](about_hash.md) simplifies and standardizes hashing. - [***text***](about_text.md) makes working with texts and strings easy. - [***time***](about_time.md) - provides methods for interacting with time and date as well as - progress bars ## *collections* This module of the package [***atlantis***](README.md) helps with working with collections. ### *`flatten`* ```python from atlantis.collections import flatten flatten([1, 2, [3, 4, [5, 6], 7], 8]) ``` returns: `[1, 2, 3, 4, 5, 6, 7, 8]` ### *`List`* This class inherits from Python's list class but implements a few additional functionalities. ```python from atlantis.collections import List l = List(1, 2, 3, 4, 2, [1, 2], [1, 2]) ``` Flattening: ```python l.flatten() >>> List: [1, 2, 3, 4, 2, 1, 2, 1, 2] ``` Finding duplicates: ```python l.get_duplicates() >>> List: [2, List: [1, 2]] ``` **Note:** the ***list*** elements of a ***List*** automatically get converted to ***Lists***, recursively. ## *ds* (Data Science) This module provides data science tools for: - data wrangling, - validation, - tuning, - sampling, - evaluation, - clustering, and - parallel processing of machine learning models. ### *KMeans* Clustering I have used the `KMeans` class from both *sklearn* and that of *pyspark* and was frustrated by two problems: (a) even though the two classes do exactly the same thing their interfaces are vastly different and (b) some of the simplest operations are very hard to do with both classes. I solved this problem by creating my own `KMeans` class that is a wrapper aroung both of those classes and uses the appropriate one automatically without complicating it for the data scientist programmer. ### Clustering Optimization