| Name | contextcache JSON |
| Version |
0.3.0
JSON |
| download |
| home_page | |
| Summary | |
| upload_time | 2023-10-19 13:44:14 |
| maintainer | |
| docs_url | None |
| author | Your Name |
| requires_python | >=3.10,<4.0 |
| license | |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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No coveralls.
|
# contextcache
[](https://github.com/Peter554/contextcache/actions/workflows/ci.yml)
Cache a python function *only in certain contexts*.
## Usage
Here's an example:
```sh
cat example.py
```
```py
import contextcache
# Define a private CacheContextVar to store the cached values. Don't touch this CacheContextVar from anywhere else!
# You need to define a separate CacheContextVar for every function for which you want to enable caching.
# Use `None` as the default.
_double_cache = contextcache.CacheContextVar("double_cache", default=None)
# Use the `enable_caching` decorator to enable context caching for `double`.
@contextcache.enable_caching(_double_cache)
def double(n: int) -> int:
print(f"Doubling {n}, working...")
return n * 2
# Without caching.
print(f"Without caching")
print(double(1))
print(double(1))
# With caching.
with contextcache.use_caching(double):
print(f"\nWith caching")
print(double(1))
print(double(1))
# Without caching, again.
print(f"\nWithout caching, again")
print(double(1))
print(double(1))
```
Here's the output:
```sh
python example.py
```
```
Without caching
Doubling 1, working...
2
Doubling 1, working...
2
With caching
Doubling 1, working...
2
2
Without caching, again
Doubling 1, working...
2
Doubling 1, working...
2
```
See the tests for further examples.
## Caveats
* Function arguments must be hashable.
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"description": "# contextcache\n\n[](https://github.com/Peter554/contextcache/actions/workflows/ci.yml)\n\nCache a python function *only in certain contexts*.\n\n## Usage\n\nHere's an example:\n\n```sh\ncat example.py \n```\n \n```py\nimport contextcache\n\n# Define a private CacheContextVar to store the cached values. Don't touch this CacheContextVar from anywhere else!\n# You need to define a separate CacheContextVar for every function for which you want to enable caching.\n# Use `None` as the default.\n_double_cache = contextcache.CacheContextVar(\"double_cache\", default=None)\n\n\n# Use the `enable_caching` decorator to enable context caching for `double`.\n@contextcache.enable_caching(_double_cache)\ndef double(n: int) -> int:\n print(f\"Doubling {n}, working...\")\n return n * 2\n\n\n# Without caching.\nprint(f\"Without caching\")\nprint(double(1))\nprint(double(1))\n\n# With caching.\nwith contextcache.use_caching(double):\n print(f\"\\nWith caching\")\n print(double(1))\n print(double(1))\n\n# Without caching, again.\nprint(f\"\\nWithout caching, again\")\nprint(double(1))\nprint(double(1))\n```\n\nHere's the output:\n\n```sh\npython example.py\n```\n\n```\nWithout caching\nDoubling 1, working...\n2\nDoubling 1, working...\n2\n\nWith caching\nDoubling 1, working...\n2\n2\n\nWithout caching, again\nDoubling 1, working...\n2\nDoubling 1, working...\n2\n```\n\nSee the tests for further examples.\n\n## Caveats\n\n* Function arguments must be hashable.",
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