fixing formatting

This commit is contained in:
ed
2026-05-16 02:33:14 -04:00
parent 29244acc74
commit 11c9aab685
4 changed files with 104 additions and 149 deletions
+2 -3
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@@ -46,10 +46,9 @@ MODEL_PRICING = [
def estimate_cost(model: str, input_tokens: int, output_tokens: int) -> float: def estimate_cost(model: str, input_tokens: int, output_tokens: int) -> float:
""" """
Estimate the cost of a model call based on input and output tokens. Estimate the cost of a model call based on input and output tokens.
Returns the total cost in USD. Returns the total cost in USD.
[C: src/gui_2.py:App._render_mma_track_summary, src/gui_2.py:App._render_mma_usage_section, src/gui_2.py:App._render_token_budget_panel, tests/test_cost_tracker.py:test_estimate_cost] [C: src/gui_2.py:App._render_mma_track_summary, src/gui_2.py:App._render_mma_usage_section, src/gui_2.py:App._render_token_budget_panel, tests/test_cost_tracker.py:test_estimate_cost]
""" """
if not model: if not model:
@@ -60,5 +59,5 @@ def estimate_cost(model: str, input_tokens: int, output_tokens: int) -> float:
input_cost = (input_tokens / 1_000_000) * rates["input_per_mtok"] input_cost = (input_tokens / 1_000_000) * rates["input_per_mtok"]
output_cost = (output_tokens / 1_000_000) * rates["output_per_mtok"] output_cost = (output_tokens / 1_000_000) * rates["output_per_mtok"]
return input_cost + output_cost return input_cost + output_cost
return 0.0 return 0.0
-22
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@@ -32,16 +32,12 @@ from src.performance_monitor import get_monitor
class TrackDAG: class TrackDAG:
""" """
Manages a Directed Acyclic Graph of implementation tickets. Manages a Directed Acyclic Graph of implementation tickets.
Provides methods for dependency resolution, cycle detection, and topological sorting. Provides methods for dependency resolution, cycle detection, and topological sorting.
""" """
def __init__(self, tickets: List[Ticket]) -> None: def __init__(self, tickets: List[Ticket]) -> None:
""" """
Initializes the TrackDAG with a list of Ticket objects. Initializes the TrackDAG with a list of Ticket objects.
Args: Args:
tickets: A list of Ticket instances defining the graph nodes and edges. tickets: A list of Ticket instances defining the graph nodes and edges.
@@ -52,8 +48,6 @@ class TrackDAG:
def cascade_blocks(self) -> None: def cascade_blocks(self) -> None:
""" """
Transitively marks `todo` tickets as `blocked` if any dependency is `blocked`. Transitively marks `todo` tickets as `blocked` if any dependency is `blocked`.
Propagates 'blocked' status from initially blocked nodes to their dependents. Propagates 'blocked' status from initially blocked nodes to their dependents.
[C: tests/test_perf_dag.py:test_dag_performance] [C: tests/test_perf_dag.py:test_dag_performance]
@@ -90,8 +84,6 @@ class TrackDAG:
def get_ready_tasks(self) -> List[Ticket]: def get_ready_tasks(self) -> List[Ticket]:
""" """
Returns a list of tickets that are in 'todo' status and whose dependencies are all 'completed'. Returns a list of tickets that are in 'todo' status and whose dependencies are all 'completed'.
Returns: Returns:
A list of Ticket objects ready for execution. A list of Ticket objects ready for execution.
@@ -105,8 +97,6 @@ class TrackDAG:
def has_cycle(self) -> bool: def has_cycle(self) -> bool:
""" """
Performs an iterative Depth-First Search to detect cycles in the dependency graph. Performs an iterative Depth-First Search to detect cycles in the dependency graph.
Returns: Returns:
True if a cycle is detected, False otherwise. True if a cycle is detected, False otherwise.
@@ -139,8 +129,6 @@ class TrackDAG:
def topological_sort(self) -> List[str]: def topological_sort(self) -> List[str]:
""" """
Returns a list of ticket IDs in topological order (dependencies before dependents). Returns a list of ticket IDs in topological order (dependencies before dependents).
Uses Kahn's algorithm for efficient O(V+E) sorting and cycle detection. Uses Kahn's algorithm for efficient O(V+E) sorting and cycle detection.
Returns: Returns:
@@ -176,16 +164,12 @@ class TrackDAG:
class ExecutionEngine: class ExecutionEngine:
""" """
A state machine that governs the progression of tasks within a TrackDAG. A state machine that governs the progression of tasks within a TrackDAG.
Handles automatic queueing and manual task approval. Handles automatic queueing and manual task approval.
""" """
def __init__(self, dag: TrackDAG, auto_queue: bool = False) -> None: def __init__(self, dag: TrackDAG, auto_queue: bool = False) -> None:
""" """
Initializes the ExecutionEngine. Initializes the ExecutionEngine.
Args: Args:
dag: The TrackDAG instance to manage. dag: The TrackDAG instance to manage.
@@ -197,8 +181,6 @@ class ExecutionEngine:
def tick(self) -> List[Ticket]: def tick(self) -> List[Ticket]:
""" """
Evaluates the DAG and returns a list of tasks that are currently 'ready' for execution. Evaluates the DAG and returns a list of tasks that are currently 'ready' for execution.
If auto_queue is enabled, tasks without 'step_mode' will be marked as 'in_progress'. If auto_queue is enabled, tasks without 'step_mode' will be marked as 'in_progress'.
Returns: Returns:
@@ -212,8 +194,6 @@ class ExecutionEngine:
def approve_task(self, task_id: str) -> None: def approve_task(self, task_id: str) -> None:
""" """
Manually transitions a task from 'todo' to 'in_progress' if its dependencies are met. Manually transitions a task from 'todo' to 'in_progress' if its dependencies are met.
Args: Args:
task_id: The ID of the task to approve. task_id: The ID of the task to approve.
@@ -225,8 +205,6 @@ class ExecutionEngine:
def update_task_status(self, task_id: str, status: str) -> None: def update_task_status(self, task_id: str, status: str) -> None:
""" """
Force-updates the status of a specific task. Force-updates the status of a specific task.
Args: Args:
task_id: The ID of the task. task_id: The ID of the task.
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