brokk-bifrost-searchtools 0.6.4

Fast, structured code search and analysis for Python, backed by a native Rust (Tree-sitter) extension

brokk-bifrost-searchtools

Fast, structured code search and analysis for Python, backed by a native Rust extension. This is the Python distribution of bifrost, the Tree-sitter-backed analyzer suite that powers Brokk.

It gives you one in-process client that talks straight to the Rust analyzer (no subprocess, no MCP server) and returns typed results plus ready-to-render text. It understands Java, JavaScript, TypeScript, Rust, Go, Python, C++, C#, PHP, and Scala.

• Install: pip install brokk-bifrost-searchtools
• Import as: bifrost_searchtools

What it does

Index a project once, then ask fast structural questions:

• Symbol search: find classes, functions, and fields by name pattern.
• Locations and sources: jump to a symbol's definition or pull its source.
• Summaries: get a signature-level outline of a file or directory.
• Usages and call graph: scan references to a symbol, or build the whole-workspace caller/callee graph (feed it to PageRank for a code map).
• Most-relevant files: rank the files most related to one or more seed files.
• Semantic search: find code by meaning, using ONNX embeddings and a cross-encoder reranker (opt-in).

Quick start

from bifrost_searchtools import SearchToolsClient

with SearchToolsClient("/path/to/project") as client:
    # Signature-level outline of a file
    print(client.get_summaries(["src/main.py"]).render_text())

    # Find symbols by name pattern
    for file in client.search_symbols(["parse_*"], limit=10).files:
        print(file.path)

    # Rank the files most related to a seed file
    print(client.most_relevant_files(["src/main.py"]).render_text())

The client indexes on first use, keeps the index warm for the session, and watches the filesystem so later queries see your edits. Every result has typed fields plus a render_text() helper.

For a runnable end-to-end demo, examples/searchtools_demo.py declares its dependency inline (PEP 723), so uv fetches the package and runs it with no manual install:

uv run examples/searchtools_demo.py --root /path/to/repo Calculator compute

API overview

SearchToolsClient(root, library_path=None, render_line_numbers=True, manual=False) exposes:

Method	Purpose
search_symbols(patterns, *, include_tests=False, limit=20)	Find symbols by name pattern.
get_symbol_locations(symbols, *, kind_filter=...)	Resolve symbols to definition sites.
get_symbol_ancestors(symbols, *, kind_filter=...)	Walk the enclosing type/scope chain.
get_symbol_sources(symbols, *, kind_filter=...)	Pull full source for symbols.
get_summaries(targets)	Signature-level outline of files / classes / directories.
list_symbols(file_patterns)	Skim the symbols declared in matching files.
scan_usages(symbols, *, include_tests=False, paths=None)	Find references to a symbol.
usage_graph(*, include_tests=False, paths=None)	Whole-workspace caller/callee graph.
most_relevant_files(seed_files, *, limit=20, ...)	Rank files related to seed files.
semantic_search(query, *, k=10)	Meaning-based code search (opt-in).
semantic_search_status()	Report whether the semantic index is ready.
refresh()	Force a full re-index (recovery escape hatch).
update_paths(paths)	Incrementally re-analyze specific paths (with manual=True).

Pass render_line_numbers=False to drop line numbers from rendered text while keeping the structured line metadata on the result objects.

Semantic search

semantic_search(...) finds files by meaning rather than name: function-level chunks are embedded, fused with BM25 and git co-edit signals, then reranked by a cross-encoder. It searches code, not prose.

It is opt-in. Set BIFROST_SEMANTIC_INDEX=auto to enable background indexing; the models load via ONNX and download from the HuggingFace hub on first use. The main bifrost README lists every environment override.

License

LGPL-3.0-or-later. See LICENSE.md.