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2 changes: 1 addition & 1 deletion README.md
Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@ async def impress_protein_bind() -> None:
pipelines based on protein quality degradation.
"""
manager: ImpressManager = ImpressManager(
execution_backend=RadicalExecutionBackend(
execution_backend = await RadicalExecutionBackend(
{'gpus':2,
'cores': 32,
'runtime' : 13 * 60,
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8 changes: 4 additions & 4 deletions docs/getting-started/quick-start.md
Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@ We use:

asyncio — Python’s built-in asynchronous library.

RadicalExecutionBackend — runs tasks in parallel.
await RadicalExecutionBackend — runs tasks in parallel.

ImpressBasePipeline — base class for defining a pipeline.

Expand Down Expand Up @@ -115,7 +115,7 @@ We now create a function that starts N pipelines at once.
```python
async def run():
manager = ImpressManager(
execution_backend=RadicalExecutionBackend({'resource': 'local.localhost'})
execution_backend = await RadicalExecutionBackend({'resource': 'local.localhost'})
)

# start 3 pipelines in parallel and wait for them to finish
Expand All @@ -129,7 +129,7 @@ async def run():

Here:

We initialize an ImpressManager with a RadicalExecutionBackend to enable parallel task execution.
We initialize an ImpressManager with a await RadicalExecutionBackend to enable parallel task execution.

We call start() and provide a list of pipeline setups, each with a unique name (p1, p2, p3) and our ProteinPipeline class.

Expand Down Expand Up @@ -186,7 +186,7 @@ class ProteinPipeline(ImpressBasePipeline):

async def run_pipeline():
manager = ImpressManager(
execution_backend=RadicalExecutionBackend({'resource': 'local.localhost'})
execution_backend = await RadicalExecutionBackend({'resource': 'local.localhost'})
)

await manager.start(
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2 changes: 1 addition & 1 deletion docs/pipelines/pre_built-pipelines.md
Original file line number Diff line number Diff line change
Expand Up @@ -136,7 +136,7 @@ async def adaptive_decision(pipeline: ProteinBindingPipeline) -> Optional[Dict[s
```python
async def impress_protein_bind() -> None:
manager: ImpressManager = ImpressManager(
execution_backend=RadicalExecutionBackend({
execution_backend = await RadicalExecutionBackend({
'gpus': 2, # GPU allocation per pipeline
'cores': 32, # CPU cores per pipeline
'runtime': 13 * 60, # 13 hours maximum runtime
Expand Down