Implements, through hashing, decision making that is deterministic on input, but probabilistic across a set of inputs.
For example, suppose a set of components in a distributed system wish to emit a log entry for 1% of requests - but each component should log the same 1% of requests, they could do so as such:
if hashdial.decide(request.id, 0.01):
log_request(request)
Take a look at the documentation for more.
Release files for hashdial 1.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hashdial-1.0.3.tar.gz | 3.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hashdial-1.0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.8 kB
Release files / hashdial-1.0.3.tar.gz
| Download URL | hashdial-1.0.3.tar.gz |
|---|---|
| Size | 3.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.6.7
|
Release files / hashdial-1.0.3-py3-none-any.whl
| Download URL | hashdial-1.0.3-py3-none-any.whl |
|---|---|
| Size | 5.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.6.7
|