Metadata-Version: 2.1
Name: deepair-dev-utils
Version: 0.0.2
Summary: This is a sub modular package for developer utilities
Home-page: https://bitbucket.org/deepair/
Author: DeepAir Dev
Author-email: naman@deepair.io
License: UNKNOWN
Description: ## Deep Developer Utilities
        
        This package consists of developer utilities specifically used for data operations and handeling within deep air environment.
        
        ## Package structure
        
        `deepair_dev_utils`
        .
        ├── general
        │   ├── __init__.py
        │   └── tools.py
        ├── __init__.py
        └── loader
            ├── __init__.py
            └── tools.py
        
        2 directories, 5 files
        
        ## Dependencies
        
        **Note**: The following python3 packages are necessary for this package to run:
        
        * numpy
        * scipy
        * pandas
        * sklearn
        * tqdm
        
        ## Function Declarations
        
        Here are the signatures for the functions in the package that can be used for deepair-dev.
        
        ### general.py
        
        Below are the functions that can be accessed by importing this module as `from deepair_dev_utils.general.tools import <function_name>`.
        
        `log`:
        ```
        def log(message):
            '''
                prints message on console
                input :
                    message     : msg to print (string)
            '''
        ```
        
        `get_data`:
        ```
        def get_data(path):
            '''
                Single file loader function
                input :
                    path     : abs path to load from (string)
            '''
        ```
        
        `daterange`:
        ```
        def daterange(s_date, e_date):
            '''
                To return a list of all the dates from
                start date to end date (excluding end date)
                input :
                    s_date     : start date (datetime)
                    e_date     : end date (datetime)
                returns :
                    list of dates
            '''
        ```
        
        ### Loader
        
        This subpackage contains tools for loading data as `Handler`.
        
        #### Handler
        
        Below are the functions that can be accessed by importing this module as `from deepair_dev_utils.loader.tools import Handler`.
        
        Then create an object to access the fuctions. example `obj = Handler()` and then `obj.<function_name>`
        
        `__init__`:
        ```
        def __init__(self, verbose=True):
            '''
                Handlder (class) constructor.
                inputs:
                    verbose: Indicator for log and progress bar (bool)
            '''
        ```
        
        `loader`:
        ```
        def loader(self, dir_path, start_date, end_date,
                   prefix='', postfix='', ext='.csv'):
            '''
                Primary loader function to load the data from start date to
                end date in concatinated (single dataframe) format.
                inputs:
                    dir_path    : absolute path to the directory path (series)
                    start_date  : load start date in dd-mm-yyyy format (string)
                    end_date    : load end date in dd-mm-yyyy format (string)
                    prefix      : file prefix [if necessary] (string)
                    postfix     : file postfix [if necessary] (string)
                    ext         : file extension [default is .csv] (string)
                return:
                    df:  loaded concatenated dataframe (pandas df)
            '''
        ```
        
        `single_loader`:
        ```
        def single_loader(self, dir_path, start_date, end_date,
                          prefix='', postfix='', ext='.csv'):
            '''
                Single loader function to load the data from start date to
                end date in individual datewise (each dataframe is of one date)
                format.
                inputs:
                    dir_path    : absolute path to the directory path (series)
                    start_date  : load start date in dd-mm-yyyy format (string)
                    end_date    : load end date in dd-mm-yyyy format (string)
                    prefix      : file prefix [if necessary] (string)
                    postfix     : file postfix [if necessary] (string)
                    ext         : file extension [default is .csv] (string)
                return:
                    data:  list of data frames datewise (list)
            '''
        ```
        
        `batch_loader`:
        ```
        def batch_loader(self, dir_path, start_date, end_date,
                         batch_size=1, prefix='', postfix='', ext='.csv'):
            '''
                Batch loader function to load the data from start date to
                end date in batches (each dataframe is in the form of batch datewise)
                format.
                inputs:
                    dir_path    : absolute path to the directory path (series)
                    start_date  : load start date in dd-mm-yyyy format (string)
                    end_date    : load end date in dd-mm-yyyy format (string)
                    batch_size  : batch size (int)
                    prefix      : file prefix [if necessary] (string)
                    postfix     : file postfix [if necessary] (string)
                    ext         : file extension [default is .csv] (string)
                return:
                    data:  list of data frames datewise (list)
            '''
        ```
        
        `_load_action`:
        ```
        def _load_action(self, df):
            '''
                @abstractmethod
                User defined Bottle neck pipeline within load.
                NOTE -> Default job of this function is pass i.e. do nothing
                inputs:
                    df:  Dataframe to apply this method on (pandas df)
                return:
                    df:  Modified dataframe (pandas df)
            '''
        ```
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
