PYYAML-cache-manager

A cache manager for caching YAML files

Contents

1. Requirements
2. Usage
   1. Using module
   2. Using class
3. Acquire data if file not found
4. Legislate path

Requirements

• Python 3.5+
• PyYaml Install PyYaml using pip:

pip install pyyaml

Alternatively, path into the repo root:

pip install -r .\requirements.txt

Usage

Using module

Cache a Python class/object:

import yaml_cache_manager as cacher

class Data:
    def __init__(self, data_id, data_name, data_hobbies):
        self.data_id = data_id
        self.data_name = data_name
        self.data_hobbies = data_hobbies


cache_path = 'cache/' # Location where the cached YAML files will be stored
DATA_KEY = 'data_{}' # Name of the file, used as a cache key. We will be formatting this
generic_data = Data(1, 'Greg', {
                       'hobby_1': 'Programming',
                       'hobby_2': 'Running'}) # Data to cache

# Cache data to the path
cacher.cache_yaml(cache_path, DATA_KEY.format(generic_data.data_id), generic_data)

Our cached file will be saved in YAML format as data_1.yml:

!!python/object:__main__.Data
data_hobbies:
  hobby_1: Programming
  hobby_2: Running
data_id: 1
data_name: Greg

Now, we can load that data:

# Load cached data with the key
loaded_data = cacher.get_yaml(cache_path, DATA_KEY.format(generic_data.data_id))
print(loaded_data.data_name) # Will output "Greg"

When it's no longer needed, remove it:

# Remove cached data by key
cacher.remove_yaml(cache_path, DATA_KEY.format(generic_data.data_id))

Using class

Alternatively you can accomplish the same functionality with an instance of the YAMLCacheManager class:

from yaml_cache_manager import YAMLCacheManager

class Data:
    def __init__(self, data_id, data_name, data_hobbies):
        self.data_id = data_id
        self.data_name = data_name
        self.data_hobbies = data_hobbies

cacher = YAMLCacheManager('cache/') # path goes in the contructor instead

DATA_KEY = 'data_{}' # Name of the file, used as a cache key. We will be formatting this
generic_data = Data(1, 'Greg', {
                       'hobby_1': 'Programming',
                       'hobby_2': 'Running'}) # Data to cache

# Cache data to the path
cacher.cache(DATA_KEY.format(generic_data.data_id), generic_data)

# Load cached data with the key
loaded_data = cacher.get(DATA_KEY.format(generic_data.data_id))
print(loaded_data.data_name) # Will output "Greg"

# Remove cached data by key
cacher.remove(DATA_KEY.format(generic_data.data_id))

Acquire data if file not found

Previously, the get() method of the YAMLCacheManager class and the standard get_yaml() method would return None if no file is found. However, you can now pass an optional acquire lambda method parameter which will excecute as the data acquisition before caching it.

acquire parameter usage

def get_employees():
    # Using the sqlite3 module as an example
    cursor = conn.cursor()
    cursor.execute('SELECT * FROM employee;')
    rows = cursor.fetchall()
    return rows

def get_employees_cache(path, key):
    # We pass in a lambda function as the acquire() parameter
    data = cacher.get_yaml(path, key, lambda : get_employees())
    return data

Note that if no data is found from the acquire method, no file will be cached.

Legislate path

There is a bonus legislate_path() method used by the cache manager autmatically, but you may use it yourself in your project where it may be useful. It will ensure there is no / at the beginning, and there is a / at the end. It takes a path paremeter and returns the path as a string

legislate_path() usage

data = yaml.load(open('{}{}.yml'.format(yaml_cache_manager.legislate_path(path), key)))