A declarative interface
for every secret provider.

Stop leaking .env files. Commit what your application expects in secretspec.toml, never the values. Developers, CI, and production can each resolve the same declaration from any of 23 providers.

dill extends Python’s pickle module for serializing and de-serializing Python objects to the majority of the built-in Python types. Serialization is the process of converting an object to a byte stream, and the inverse of which is converting a byte stream back to a Python object hierarchy.

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dill can pickle the following standard types:

    none, type, bool, int, float, complex, bytes, str,
    tuple, list, dict, file, buffer, builtin,
    Python classes, namedtuples, dataclasses, metaclasses,
    instances of classes,
    set, frozenset, array, functions, exceptions

dill can also pickle more ‘exotic’ standard types:

    functions with yields, nested functions, lambdas,
    cell, method, unboundmethod, module, code, methodwrapper,
    methoddescriptor, getsetdescriptor, memberdescriptor, wrapperdescriptor,
    dictproxy, slice, notimplemented, ellipsis, quit

The proliferation of AI-generated and AI-assisted text on the internet is feared to contribute to a degradation in semantic and stylistic diversity, factual accuracy, and other negative developments. We find that by mid-2025, roughly 35% of newly published websites were classified as AI-generated or AI-assisted, up from zero before ChatGPT's launch in late 2022. We also find evidence suggesting that increases in AI-generated text on the internet bring about a decrease in semantic diversity and an increase in positive sentiment. We do not, however, find statistically significant evidence supporting the hypothesis that an increased rate of AI-generated text on the internet decreases factual accuracy or stylistic diversity. Notably, our findings diverge from public perception of AI's impact on the internet.

tldr: instead of invert(1), use hue-rotate(180deg) invert(1).

An extended fork of GNU Unifont with a focus on high compatibility.

Diátaxis identifies four distinct needs, and four corresponding forms of documentation - tutorials, how-to guides, technical reference and explanation. It places them in a systematic relationship, and proposes that documentation should itself be organised around the structures of those needs.