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3130131310 of 39584 results
61675.
* prioritized_methods - prioritize methods to resolve dispatch ambiguities
Description
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Located in Package: python-peak.rules
61676.
utilities from the Python Enterprise Application Kit
Summary
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Located in Package: python-peak.util
61677.
The Python Enterprise Application Kit (PEAK) is a set of Python libraries to help develop large-scale Python applications.
Description
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Located in Package: python-peak.util
61678.
PEAK includes libraries and frameworks to support: component integration, component configuration , document-driven testing, event-driven programming, storage management and persistence, domain modelling, and much more.
Description
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Located in Package: python-peak.util
61679.
This package provides a subset of utilities related to PEAK, and commonly found as dependencies for PEAK-based components. In particular, this package provides:
Description
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Located in Package: python-peak.util
61680.
* AddOns - dynamic mixins with private attribute and methods
* BytecodeAssembler - code object generation assembling bytecode
* Extremes - absolute max and min values (PEP 326 implementation)
* SymbolType - symbol type, i.e., enumerations
Description
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Located in Package: python-peak.util
61681.
version-agnostic decorators support for Python
Summary
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Located in Package: python-peak.util.decorators
61682.
DecoratorTools provides decorator facilities for Python 2.3 and above. It provides class and function decorators as well as support for decorating arbitrary assignments, synchronized methods, and more.
Description
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Located in Package: python-peak.util.decorators
61683.
DecoratorTools is part of the PEAK (Python Enterprise Architecture Kit) framework and provides the peak.util.decorators module.
Description
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Located in Package: python-peak.util.decorators
61684.
Python Environment for Bayesian Learning
Summary
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Located in Package: python-pebl
3130131310 of 39584 results

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