shareable

Dynamic python object access & manipulation across threads/processes

Installation: requires python3.8+

pip install shareable

Example:

# make a test class:
class Test:
    def __init__(self, name, age):
        self.name = name
        self.age = age
        
    def get_details(self):
        return self.name, self.age

# in terminal 1
>>> from shareable import Shareable
>>> test = Test('DB Cooper', 50)
>>> s = Shareable(test)
>>> s
'Shareable(DB Cooper, 50)'

# in terminal 2: 
>>> from shareable import Shareable
>>> s = Shareable()
'Connection established'
>>> print(s['name'])
'DB Cooper'
>>> s['name'] = 'new name'

# back in terminal 1:
'Connection established'
>>> print(s['name'])
'new name'
>>> print(s.methods())
'["age", "get_details", "name"]'

Support for complex objects:

>>> import pandas as pd
>>> import numpy as np
>>> df = pd.DataFrame(np.random.randint(0,100,size=(100, 4)), columns=list('ABCD'))
>>> s = Sharedable(df)
>>> s['info']()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 100 entries, 0 to 99
Data columns (total 4 columns):
 #   Column  Non-Null Count  Dtype
---  ------  --------------  -----
 0   A       100 non-null    int64
 1   B       100 non-null    int64
 2   C       100 non-null    int64
 3   D       100 non-null    int64
dtypes: int64(4)
memory usage: 3.2 KB

# terminal 2:
>>> s = Shareable()
'Connection established'
>>> s['columns']
Index(['A', 'B', 'C', 'D'], dtype='object')

Gracefully handles resources on keyboard or explicit exit:

>>> s = Shareable()
>>> exit()
'Destroyed shared resources'
'Killed all child processes'