# lazymap
A lazy mapping whose values are evaluated when accessed
## Installation
You can install this package with pip.
```sh
$ pip install lazymap
```
## Links
[](https://abrahammurciano.github.io/python-lazymap)
[](https://github.com/abrahammurciano/python-lazymap.git)
[](https://pypi.org/project/lazymap/)
## Usage
A `LazyMap` is a mapping whose values can be evaluated only when they are accessed. This is useful when you need a mapping which might not need to evaluate all of its values, but it is unknown which values will be needed.
Not all values of a `LazyMap` need to be lazily evaluated. You can also store regular values in a `LazyMap`.
`LazyMap` also supports caching of values, so that they are only evaluated once, although this can be disabled on a per-object or per-key basis.
### Importing
```python
from lazymap import LazyMap
```
### Creating a LazyMap
You can initialize a `LazyMap` and provide it with initial static values, initial lazy values, a default factory function for missing keys, and any combination of the above. Additionally you can enable (default) or disable caching for the entire `LazyMap`.
If a default factory function is provided, it will be called with the key as an argument when a key is accessed which is not in the `LazyMap`.
```python
static = LazyMap({"a": 1, "b": 2})
lazy = LazyMap({"c": lambda: 3})
default = LazyMap(default=lambda key: key * 2)
uncached = LazyMap({"random": lambda: randint(0, 100)}, cache=False)
```
### Creating a LazyMap from keys and a function
You can initialize a `LazyMap` from a set of keys and a function which will be used to evaluate the value of each key. This way, the values are only evaluated when they are accessed.
You can also pass `allow_missing=True` to the `fromkeys` constructor to also use the function as a default factory function for missing keys.
```python
def expensive(key):
print(f'Calculating value for key {key}...')
return key * 2
from_keys = LazyMap.fromkeys((1, 2, 3), expensive)
```
### Adding values to a LazyMap
You can add **non-lazy** values to a `LazyMap` just like you would a dictionary.
```python
lazy_map = LazyMap()
lazy_map["a"] = 1 # not lazy
```
You can also add **lazy** values to a `LazyMap` with the `lazy` method.
```python
def get_b():
print('Calculating value of x...')
sleep(1)
return 42
lazy_map.lazy("x", get_x) # lazy
print(lazy_map["x"]) # Calls get_x
```
### Caching values
By default, the lazy values of a `LazyMap` are only evaluated once. The value is then cached and returned on subsequent accesses.
You can also pass `cache=True` or `cache=False` when adding a lazy key with `lazy()` to override the default caching behaviour for that key.
```python
lazy_map = LazyMap()
def get_value():
sleep(1)
return randint(0, 100)
lazy_map.lazy("cached", get_value)
lazy_map.lazy("uncached", get_value, cache=False)
print(lazy_map["cached"]) # 42
print(lazy_map["cached"]) # 42
print(lazy_map["uncached"]) # 69
print(lazy_map["uncached"]) # 13
```
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"description": "# lazymap\n\nA lazy mapping whose values are evaluated when accessed\n\n## Installation\n\nYou can install this package with pip.\n```sh\n$ pip install lazymap\n```\n\n## Links\n\n[](https://abrahammurciano.github.io/python-lazymap)\n\n[](https://github.com/abrahammurciano/python-lazymap.git)\n\n[](https://pypi.org/project/lazymap/)\n\n## Usage\n\nA `LazyMap` is a mapping whose values can be evaluated only when they are accessed. This is useful when you need a mapping which might not need to evaluate all of its values, but it is unknown which values will be needed.\n\nNot all values of a `LazyMap` need to be lazily evaluated. You can also store regular values in a `LazyMap`.\n\n`LazyMap` also supports caching of values, so that they are only evaluated once, although this can be disabled on a per-object or per-key basis.\n\n### Importing\n\n```python\nfrom lazymap import LazyMap\n```\n\n### Creating a LazyMap\n\nYou can initialize a `LazyMap` and provide it with initial static values, initial lazy values, a default factory function for missing keys, and any combination of the above. Additionally you can enable (default) or disable caching for the entire `LazyMap`.\n\nIf a default factory function is provided, it will be called with the key as an argument when a key is accessed which is not in the `LazyMap`.\n\n```python\nstatic = LazyMap({\"a\": 1, \"b\": 2})\nlazy = LazyMap({\"c\": lambda: 3})\ndefault = LazyMap(default=lambda key: key * 2)\nuncached = LazyMap({\"random\": lambda: randint(0, 100)}, cache=False)\n```\n\n### Creating a LazyMap from keys and a function\n\nYou can initialize a `LazyMap` from a set of keys and a function which will be used to evaluate the value of each key. This way, the values are only evaluated when they are accessed.\n\nYou can also pass `allow_missing=True` to the `fromkeys` constructor to also use the function as a default factory function for missing keys.\n\n```python\ndef expensive(key):\n\tprint(f'Calculating value for key {key}...')\n\treturn key * 2\n\nfrom_keys = LazyMap.fromkeys((1, 2, 3), expensive)\n```\n\n### Adding values to a LazyMap\n\nYou can add **non-lazy** values to a `LazyMap` just like you would a dictionary.\n\n```python\nlazy_map = LazyMap()\nlazy_map[\"a\"] = 1 # not lazy\n```\n\nYou can also add **lazy** values to a `LazyMap` with the `lazy` method.\n\n```python\ndef get_b():\n\tprint('Calculating value of x...')\n\tsleep(1)\n\treturn 42\n\nlazy_map.lazy(\"x\", get_x) # lazy\nprint(lazy_map[\"x\"]) # Calls get_x\n```\n\n### Caching values\n\nBy default, the lazy values of a `LazyMap` are only evaluated once. The value is then cached and returned on subsequent accesses.\n\nYou can also pass `cache=True` or `cache=False` when adding a lazy key with `lazy()` to override the default caching behaviour for that key.\n\n```python\nlazy_map = LazyMap()\n\ndef get_value():\n\tsleep(1)\n\treturn randint(0, 100)\n\nlazy_map.lazy(\"cached\", get_value)\nlazy_map.lazy(\"uncached\", get_value, cache=False)\n\nprint(lazy_map[\"cached\"]) # 42\nprint(lazy_map[\"cached\"]) # 42\nprint(lazy_map[\"uncached\"]) # 69\nprint(lazy_map[\"uncached\"]) # 13\n```",
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