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 and listings: get signature-level file/class outlines, immediate git-visible directory children, or package types and child packages.
  • 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.
query_code(pattern=None, *, union=None, intersect=None, except_=None, inside=None, not_inside=None, where=None, languages=None, steps=None, limit=None, result_detail=None, schema_version=None, execution_mode=None) Query normalized code structure, compose compatible typed branches, and optionally explain or profile execution.
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_declarations_by_location([{"path": ..., "line": ..., "column": ...}]) Resolve references to declaration contracts at known file locations.
get_definitions_by_location([{"path": ..., "line": ..., "column": ...}]) Resolve references to concrete definitions at known file locations.
get_definitions_by_reference([{"symbol": ..., "context": ..., "target": ...}]) Resolve copied references inside symbol source blocks.
get_type_by_location(path, *, line=..., column=...) Resolve the type of an expression or identifier at a known file location.
get_summaries(targets) Signature-level file/class outlines; immediate directory children; or exact-package types and direct child packages.
list_symbols(file_patterns) Skim the symbols declared in matching files.
scan_usages_by_reference(symbols, *, include_tests=False, paths=None) Find references to known symbols.
scan_usages_by_location(targets, *, include_tests=False, paths=None) Find references from declaration line/column targets.
rename_symbol(path, *, line=..., column=..., new_name=...) Return a non-mutating edit plan for a symbol rename.
usage_graph(*, include_tests=False, paths=None) Whole-workspace caller/callee graph; each edge carries its {path, line} call sites.
most_relevant_files(seed_files, *, limit=20, include_tests=True, ...) Rank files related to seed files, optionally excluding test and test-support files before applying the limit.
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).
activate_workspace(path) / get_active_workspace() Switch / read the active workspace root.
get_file_contents(file_paths) Read whole files by path.
find_filenames(patterns, *, limit=None) Find files by path glob.
search_file_contents(patterns, *, file_path=None, context_lines=None, case_insensitive=False) Grep contents with context.
find_files_containing(patterns, *, limit=None, case_insensitive=False) Find files whose contents match.
list_files(directory_path="", *, max_entries=None) List files under a directory.
jq(file_path, filter_expr, *, max_files=None, matches_per_file=None) Run a jq filter over JSON files.
xml_skim(file_path, *, max_files=None) Summarize XML element structure.
xml_select(file_path, xpath, *, output=XmlSelectOutput.TEXT, attr_name=None, max_files=None) Evaluate an XPath over XML files.
compute_cyclomatic_complexity(file_paths, *, threshold=None) Per-function cyclomatic complexity.
compute_cognitive_complexity(file_paths, *, threshold=None) Per-function cognitive complexity.
report_comment_density_for_code_unit(fq_name, *, max_lines=None) Comment density for one symbol.
report_comment_density_for_files(file_paths, *, max_top_level_rows=None, max_files=None) Comment density per file.
report_exception_handling_smells(file_paths, *, min_score=None, max_findings=None, options=None) Suspicious exception handlers.
report_test_assertion_smells(file_paths, *, min_score=None, max_findings=None, options=None) Low-value test assertions.
report_structural_clone_smells(file_paths, *, min_score=None, max_findings=None, options=None) Structural code clones.
report_long_method_and_god_object_smells(file_paths, *, max_findings=None, max_files=None, options=None) Oversized functions / god objects.
report_dead_code_and_unused_abstraction_smells(*, file_paths=None, fq_names=None, min_score=None, max_findings=None, options=None) Likely dead code (Rust).
report_secret_like_code(*, max_findings=None, max_commits=None, include_history_only=False, include_low_confidence=False) Secret-looking strings in files / history.
analyze_git_hotspots(*, since_days=None, since_iso=None, until_iso=None, max_commits=None, max_files=None) Churn × complexity hotspots.

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

The slopcop tools return a CodeQualityReport (.report), and the rest return structured dataclasses from bifrost_searchtools.models. The per-rule tuning knobs on the smell reports are passed through options (keys map 1:1 to the Rust tool arguments).

Location navigation results expose a NavigationOperation. Declarations use DeclarationLookupResult.declarations; definitions use DefinitionLookupResult.definitions. Their statuses distinguish no_declaration, no_definition, and ambiguous. Reference-based definition lookup is unchanged, and there is no declaration-by-reference method.

Exact source positions use 1-based lines and 1-based Unicode code-point columns, with an exclusive end position. Individual usage hits carry line, column, end_line, and end_column; definition, declaration, and nested type candidates carry start_line, start_column, end_line, and end_column. Column fields are absent for aggregate rows or candidates whose exact name token cannot be proven. Byte offsets remain internal.

query_code detail and ranges

query_code is a versioned typed query surface. Omit schema_version for the compatible head, currently v6, or pass schema_version=2 to pin the pre-CFG vocabulary. Pass schema_version=3 to pin CFG without typestate or schema_version=4 to pin typestate without declaration-bounded containment. Pass schema_version=5 to pin containment without value flow. Pass exactly one of pattern, union, intersect, or except_; set operands are complete query-plan dictionaries with compatible terminal domains. A structural pattern or composed set can be followed by ordered steps using enclosing_decl, file_of, imports_of, importers_of, supertypes, subtypes, members, owner, procedure_of, cfg_entry, cfg_exits, cfg_successor_edges, cfg_predecessor_edges, cfg_edge_source, cfg_edge_target, typestate, value_flow, and witness. Import operations traverse one direct project-local edge per step. Hierarchy operations are direct by default and accept a positive depth or transitive: true. Declaration results are limited to declarations indexed by the workspace analyzer, so references into an unindexed library do not manufacture library declarations. Results are tagged as structural matches, declarations, reference sites, call sites, expression sites, receiver analyses, procedures, program points, control edges, typestate findings, typestate witnesses, flow endpoints, flow witnesses, or files. The CFG operations are procedure-local and one-hop. Schema v4 can consume a host-registered typestate protocol/binding pair and project its already-retained bounded witnesses; the Python call sends only protocol_ref. Schema v5 adds inside_decl, which matches containment only until a nested function, method, constructor, or lambda boundary. Schema v6 consumes a host-registered ValueFlowPlan by plan_ref and preserves reachability, exact/may certainty, ambiguity, completion, and budget status as independent diagnostic-neutral fields. It does not classify policy findings. Compact output retains minimal pipeline provenance. Pass result_detail="full" when follow-up tooling needs deterministic IDs and precise ranges.

Omit execution_mode (or pass "results") for the ordinary CodeQueryResult. Pass execution_mode="explain" to receive a CodeQueryExplain containing the normalized query, logical DAG, selected physical plan, and scheduling decision without executing the query. Pass execution_mode="profile" to execute it and receive a CodeQueryProfile; its .result is the ordinary typed result, while .explain, .timings_ns, .work, .cache_layers, .scheduling, and .operators expose structured observations. Explain physical nodes declare any semantic_request, while profile .work.semantic accounts materialization, cache reuse, CFG rows, retained bytes, traversal, and budget exhaustion; .work.semantic.typestate accounts solver reuse, findings, retained witnesses, and termination; .work.semantic.value_flow reports flow solves, meetings, endpoints, witnesses, and termination. Profile timings are elapsed nanoseconds, and temporary_capacity_bytes_lower_bound is deliberately only a lower-bound container-capacity estimate. In the public v2 profile contract, top-level and per-operator .cache_layers are lists of {layer, metrics} records. The nested metrics object has kind="structural_facts" for seed_structural_facts and kind="complete_value" for every other layer. The direct_import_topology layer additionally reports snapshot build files, edges, time, retained bytes, cancellation/unavailability, and request-local fallbacks.

For decorated or annotated declarations, node_range is the matched normalized node's parser-backed range. decorator_ranges are the decorator or annotation role spans extracted by the language adapter. decorated_range is the union of node_range and those decorator ranges. Matching semantics are unchanged by requesting full detail; these fields only make the span policy explicit.

Current structural precision

query_code normalizes common syntax across Python, Java, JavaScript, TypeScript, Go, C/C++, Rust, PHP, Scala, C#, and Ruby, but it is still a syntactic structural query tool. Use these caveats when writing reusable rules or prompts; the public Code Querying guide is the canonical reference:

Area Current behavior
Constructor calls Java object creation and JS/TS new expressions are normalized as call; constructors are also refined as constructor declarations where the adapter can identify them.
Keyword arguments Python, PHP, Scala, C#, and Ruby support normalized kwargs; other adapters report unsupported-role diagnostics.
Imports and aliases Import matching is based on syntactic module/import spans. It does not resolve aliases or follow re-exports.
Receiver and callee callee.name and receiver.name are derived from AST fields and terminal names, not type resolution. Chained calls stay syntactic.
Decorators and annotations Decorators/annotations are exposed through the decorators role. Full detail reports node_range, decorator_ranges, and decorated_range.
Positional arguments args patterns match positional arguments in order as a subsequence; v2 does not require exact positions or arity.
Typed pipelines Declaration, hierarchy, and ownership steps preserve exact indexed identities; import steps follow direct workspace file edges and may be repeated; schema-v3 CFG steps expose source-backed procedure-local points and explicit one-hop edges.
Unsupported capabilities Queries against unsupported normalized kinds or roles return diagnostics instead of silently pretending the language can answer them.

Semantic search

semantic_search(...) searches code by meaning rather than name and returns the three retrieval legs directly: function-oriented vector and BM25 rankings over function-level chunks, plus a file-oriented co-edit ranking. 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 semantic search docs list every environment override.

License

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

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  • Released:
Newer release available (0.8.24)

2 maintainers

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Credits

Author: Brokk

GitHub Statistics

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License expression

LGPL-3.0-or-later
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Requires

Python >=3.12

Tags

code-analysis tree-sitter code-search semantic-search static-analysis symbols

Classifiers

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