Fix input validation and clean up minor code issues

[mfinean]

Fixes a few small code issues:

• Input validation: Changed assert statements to raise TypeError/ValueError with descriptive messages. Assertions can be disabled with -O, so they shouldn't be used for input validation.

• Dead code: Removed duplicate self.worker_class_instance = None assignment.

• Magic number: Extracted the 100GB cache size to DEFAULT_CACHE_SIZE_BYTES constant.

• Hardcoded version: The rerun viewer URL now uses the installed package version via importlib.metadata instead of a hardcoded string (resolves the TODO).

Summary by Sourcery

Improve input validation and configuration around benchmarking cache and rerun viewer integration.

Bug Fixes:

• Replace assertion-based input validation with explicit TypeError/ValueError exceptions for benchmark names and input variable lists.
• Remove duplicate worker_class_instance initialization in the benchmark setup.

Enhancements:

• Introduce a DEFAULT_CACHE_SIZE_BYTES constant for the default 100GB benchmark result cache size.
• Derive the rerun viewer URL version from the installed rerun package via importlib.metadata with a safe fallback.

[sourcery-ai]

Reviewer's guide (collapsed on small PRs)

Reviewer's Guide

Refactors input validation to use explicit exceptions instead of assertions, removes a redundant assignment, centralizes the default cache size in a constant, and makes the rerun viewer URL dynamically use the installed rerun package version with a safe fallback.

Sequence diagram for dynamic rerun viewer version resolution

sequenceDiagram
  participant Caller
  participant UtilsRerun
  participant ImportlibMetadata as ImportlibMetadata
  participant Panel

  Caller->>UtilsRerun: rrd_to_pane(url, width, height, version=None)
  UtilsRerun->>UtilsRerun: _get_rerun_version()
  UtilsRerun->>ImportlibMetadata: get_package_version(rerun-sdk)
  alt version lookup succeeds
    ImportlibMetadata-->>UtilsRerun: rerun_version
  else version lookup fails
    ImportlibMetadata-->>UtilsRerun: raises Exception
    UtilsRerun->>UtilsRerun: use fallback 0.20.1
  end
  UtilsRerun->>Panel: pn.pane.HTML(iframe_html)
  Panel-->>Caller: HTMLPane

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Class diagram for updated Bencher initialization and rerun utilities

classDiagram

class BencherModule {
  + DEFAULT_CACHE_SIZE_BYTES int
}

class Bencher {
  - bench_name str
  - worker Any
  - worker_class_instance Any
  - worker_input_cfg Any
  - cache_size int
  - sample_cache Any
  - ds_dynamic dict
  + __init__(bench_name, worker, worker_input_cfg, run_cfg, report)
  + set_worker(worker, worker_input_cfg)
  + plot_sweep(input_vars_in, run_cfg)
}

class UtilsRerun {
  + _get_rerun_version() str
  + rrd_to_pane(url str, width int, height int, version str) HTMLPane
}

BencherModule --> Bencher : uses DEFAULT_CACHE_SIZE_BYTES
UtilsRerun --> Bencher : used in plotting workflows

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File-Level Changes

Change	Details	Files
Replace assertion-based input validation with explicit TypeError/ValueError exceptions carrying descriptive messages.	Validate bench_name type using an isinstance check and raise TypeError with a clear message when invalid instead of using an assert. Ensure list-type input variables in plot_sweep raise ValueError with a descriptive message when empty instead of asserting non-emptiness.	bencher/bencher.py
Clean up configuration defaults and remove dead code in the benchmark class.	Introduce DEFAULT_CACHE_SIZE_BYTES constant for the 100 GB default cache size. Use the shared DEFAULT_CACHE_SIZE_BYTES constant when initializing self.cache_size instead of an inline literal. Remove duplicate initialization of self.worker_class_instance to None in the constructor.	bencher/bencher.py
Resolve hardcoded rerun viewer version by deriving it from the installed package with a robust fallback.	Add a helper function _get_rerun_version that retrieves the rerun-sdk package version via importlib.metadata.version and falls back to a default string on failure. Update rrd_to_pane to use _get_rerun_version when no version is provided instead of a hardcoded version literal.	bencher/utils_rerun.py

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[sourcery-ai]

Hey - I've found 1 issue, and left some high level feedback:

• In _get_rerun_version, catching a broad Exception will hide unexpected issues; consider catching importlib.metadata.PackageNotFoundError (and possibly logging a warning) before falling back to the hardcoded version.
• Since DEFAULT_CACHE_SIZE_BYTES encodes the 100 GB default, you might want to express it as 100 * 1024**3 (and/or update the nearby comment to derive from the constant) to avoid ambiguity if the value changes later.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- In `_get_rerun_version`, catching a broad `Exception` will hide unexpected issues; consider catching `importlib.metadata.PackageNotFoundError` (and possibly logging a warning) before falling back to the hardcoded version.
- Since `DEFAULT_CACHE_SIZE_BYTES` encodes the 100 GB default, you might want to express it as `100 * 1024**3` (and/or update the nearby comment to derive from the constant) to avoid ambiguity if the value changes later.

## Individual Comments

### Comment 1
<location> `bencher/utils_rerun.py:11-13` </location>
<code_context>

+def _get_rerun_version() -> str:
+    """Get the installed rerun package version."""
+    try:
+        return get_package_version("rerun-sdk")
+    except Exception:
+        return "0.20.1"  # Fallback version
+
</code_context>

<issue_to_address>
**issue (bug_risk):** Narrow the exception type when resolving the rerun package version to avoid masking unrelated errors.

Catching `Exception` here can mask real problems (e.g., import errors or environment misconfiguration). Please catch `importlib.metadata.PackageNotFoundError` for the missing-package case instead, and let other exceptions propagate (optionally with a log warning before falling back to the hard-coded version).
</issue_to_address>

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