""" pdoc has a search box which allows users to quickly find relevant parts in the documentation. This feature is implemented entirely client-side so that pdoc can still be hosted statically, and works without any third-party services in a privacy-preserving way. When a user focuses the search box for the first time, pdoc will fetch the search index (`search.js`) and use that to answer all upcoming queries. ##### Single-Page Documentation If pdoc is documenting a single module only, search functionality will be disabled. The browser's built-in search functionality will provide a better user experience in these cases. ##### Search Coverage The search functionality covers all documented elements and their docstrings. You may find documentation objects using their name, arguments, or type annotations; the source code is not considered. ##### Search Performance pdoc uses [Elasticlunr.js](https://github.com/weixsong/elasticlunr.js) to implement search. To improve end user performance, pdoc will attempt to precompile the search index when building the documentation. This only works if `nodejs` is available, and pdoc gracefully falls back to client-side index building if this is not the case. If your search index reaches a size where compilation times are meaningful and `nodejs` cannot be invoked, pdoc will let you know and print a notice when building your documentation. In this case it should be enough to install a recent version of [Node.js](https://nodejs.org/) on your system and make a `nodejs` or `node` available on your PATH. There are no other additional dependencies. pdoc only uses `node` to interpret a local JS file, it does not download any additional packages. You can test if your search index is precompiled by clicking the search box (so that the search index is fetched) and then checking your browser's developer console. ##### Search Index Size The search index can be relatively large as it includes all docstrings. For larger projects, you should make sure that you have [HTTP compression](https://en.wikipedia.org/wiki/HTTP_compression) and caching enabled. `search.js` usually compresses to about 10% of its original size. For example, pdoc's own precompiled search index compresses from 312kB to 27kB. ##### Disabling Search If you wish to disable the search functionality, you can pass `--no-search` when invoking pdoc. """ from __future__ import annotations from collections.abc import Callable from collections.abc import Mapping import html import json from pathlib import Path import shutil import subprocess import textwrap import pdoc.doc from pdoc.render_helpers import format_signature from pdoc.render_helpers import to_html from pdoc.render_helpers import to_markdown def make_index( all_modules: Mapping[str, pdoc.doc.Module], is_public: Callable[[pdoc.doc.Doc], bool], default_docformat: str, ) -> list[dict]: """ This method compiles all currently documented modules into a pile of documentation JSON objects, which can then be ingested by Elasticlunr.js. """ documents = [] for modname, module in all_modules.items(): def make_item(doc: pdoc.doc.Doc, **kwargs) -> dict[str, str]: # TODO: We could be extra fancy here and split `doc.docstring` by toc sections. ret = { "fullname": doc.fullname, "modulename": doc.modulename, "qualname": doc.qualname, "kind": doc.kind, "doc": to_html(to_markdown(doc.docstring, module, default_docformat)), **kwargs, } return {k: v for k, v in ret.items() if v} # TODO: Instead of building our own JSON objects here we could also use module.html.jinja2's member() # implementation to render HTML for each documentation object and then implement a elasticlunr tokenizer that # removes HTML. It wouldn't be great for search index size, but the rendered search entries would be fully # consistent. def make_index(mod: pdoc.doc.Namespace, **extra): if not is_public(mod): return yield make_item(mod, **extra) for m in mod.own_members: if isinstance(m, pdoc.doc.Variable) and is_public(m): yield make_item( m, annotation=html.escape(m.annotation_str), default_value=html.escape(m.default_value_str), ) elif isinstance(m, pdoc.doc.Function) and is_public(m): if m.name == "__init__": yield make_item( m, signature=format_signature(m.signature_without_self, False), ) else: yield make_item( m, signature=format_signature(m.signature, True), funcdef=m.funcdef, ) elif isinstance(m, pdoc.doc.Class): yield from make_index( m, bases=", ".join(x[2] for x in m.bases), ) else: pass documents.extend(make_index(module)) return documents def precompile_index(documents: list[dict], compile_js: Path) -> str: """ This method tries to precompile the Elasticlunr.js search index by invoking `nodejs` or `node`. If that fails, an unprocessed index will be returned (which will be compiled locally on the client side). If this happens and the index is rather large (>3MB), a warning with precompile instructions is printed. We currently require nodejs, but we'd welcome PRs that support other JavaScript runtimes or – even better – a Python-based search index generation similar to [elasticlunr-rs](https://github.com/mattico/elasticlunr-rs) that could be shipped as part of pdoc. """ raw = json.dumps(documents) try: if shutil.which("nodejs"): executable = "nodejs" else: executable = "node" out = subprocess.check_output( [executable, compile_js], input=raw.encode(), cwd=Path(__file__).parent / "templates", stderr=subprocess.STDOUT, ) index = json.loads(out) index["_isPrebuiltIndex"] = True except Exception as e: if len(raw) > 3 * 1024 * 1024: print( f"pdoc failed to precompile the search index: {e}\n" f"Search will work, but may be slower. " f"This error may only show up now because your index has reached a certain size. " f"See https://pdoc.dev/docs/pdoc/search.html for details." ) if isinstance(e, subprocess.CalledProcessError): print(f"{' Node.js Output ':=^80}") print( textwrap.indent(e.output.decode("utf8", "replace"), " ").rstrip() ) print("=" * 80) return raw else: return json.dumps(index)