Predictive Modelling Metadata Interchange Format
Python support for dataset metadata for predictive modelling and data analysis.
The pmmif package provides two levels of support.
.pmm Metadata Files
Classes for reading and writing extended metadata to .pmm JSON files.
Pandas DataFrame Support
Classes for associating Pandas DataFrames with additional type and tags annotation metadata, including support for persisting additional metadata alongside feather datafiles.
Documentation
1 maintainer
Metadata
1 maintainer
Release files for pmmif 0.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pmmif-0.2.1.tar.gz | 22.9 kB | Without provenance | Details for pmmif-0.2.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| pmmif-0.2.1-py3-none-any.whl | Python 3 | none | any | Details for pmmif-0.2.1-py3-none-any.whl |
Total release size: 49.0 kB
Release files / pmmif-0.2.1.tar.gz
| Download URL | pmmif-0.2.1.tar.gz |
|---|---|
| Size | 22.9 kB |
| Tags | Source |
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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/6.2.0 CPython/3.13.5
|
Release files / pmmif-0.2.1-py3-none-any.whl
| Download URL | pmmif-0.2.1-py3-none-any.whl |
|---|---|
| Size | 26.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
0e2da909eb2760d4fd7aa74c50331842c192ed15aeab70abaf3ece0cc8e58ed9
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|
BLAKE2b-256 checksum How to use checksums |
9d49888992f1ece579c30f386b9894a1428d0654781aa0ede13a340f0e999e57
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.13.5
|
Security for pmmif 0.2.1
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