rg --json 'uv run python' | rg-replace 'uv run'

Author: dandavison

.github/workflows/ci.yml

@@ -50,7 +50,7 @@ jobs:
         if: ${{ matrix.python == '3.12' }}
         run: |
           uv sync --group gevent
-          uv run python gevent_async/test/run_combined.py
+          uv run gevent_async/test/run_combined.py
 
       - name: Upload junit-xml artifacts
         uses: actions/upload-artifact@v4

README.md

@@ -18,9 +18,9 @@ With this repository cloned, run the following at the root of the directory:
 
     uv sync
 
-That loads all required dependencies. Then to run a sample, usually you just run it in Python. For example:
+That loads all required dependencies. Then to run a sample, usually you just run it under uv. For example:
 
-    uv run python hello/hello_activity.py
+    uv run hello/hello_activity.py
 
 Some examples require extra dependencies. See each sample's directory for specific instructions.
 

activity_worker/README.md

@@ -8,6 +8,6 @@ First run the Go workflow worker by running this in the `go_workflow` directory
 
 Then in another terminal, run the sample from this directory:
 
-    uv run python activity_worker.py
+    uv run activity_worker.py
 
 The Python code will invoke the Go workflow which will execute the Python activity and return.

bedrock/basic/README.md

@@ -4,7 +4,7 @@ A basic Bedrock workflow. Starts a workflow with a prompt, generates a response
 
 To run, first see `samples-python` [README.md](../../README.md), and `bedrock` [README.md](../README.md) for prerequisites specific to this sample. Once set up, run the following from this directory:
 
-1. Run the worker: `uv run python run_worker.py`
+1. Run the worker: `uv run run_worker.py`
 2. In another terminal run the client with a prompt:
 
-    e.g. `uv run python send_message.py 'What animals are marsupials?'`
+    e.g. `uv run send_message.py 'What animals are marsupials?'`

bedrock/entity/README.md

@@ -4,16 +4,16 @@ Multi-Turn Chat using an Entity Workflow. The workflow runs forever unless expli
 
 To run, first see `samples-python` [README.md](../../README.md), and `bedrock` [README.md](../README.md) for prerequisites specific to this sample. Once set up, run the following from this directory:
 
-1. Run the worker: `uv run python run_worker.py`
+1. Run the worker: `uv run run_worker.py`
 2. In another terminal run the client with a prompt.
 
-    Example: `uv run python send_message.py 'What animals are marsupials?'`
+    Example: `uv run send_message.py 'What animals are marsupials?'`
 
 3. View the worker's output for the response.
 4. Give followup prompts by signaling the workflow.
 
-    Example: `uv run python send_message.py 'Do they lay eggs?'`
+    Example: `uv run send_message.py 'Do they lay eggs?'`
 5. Get the conversation history summary by querying the workflow.
 
-    Example: `uv run python get_history.py`
-6. To end the chat session, run `uv run python end_chat.py`
+    Example: `uv run get_history.py`
+6. To end the chat session, run `uv run end_chat.py`

bedrock/signals_and_queries/README.md

@@ -4,16 +4,16 @@ Adding signals & queries to the [basic Bedrock sample](../1_basic). Starts a wor
 
 To run, first see `samples-python` [README.md](../../README.md), and `bedrock` [README.md](../README.md) for prerequisites specific to this sample. Once set up, run the following from this directory:
 
-1. Run the worker: `uv run python run_worker.py`
+1. Run the worker: `uv run run_worker.py`
 2. In another terminal run the client with a prompt.
 
-    Example: `uv run python send_message.py 'What animals are marsupials?'`
+    Example: `uv run send_message.py 'What animals are marsupials?'`
 
 3. View the worker's output for the response.
 4. Give followup prompts by signaling the workflow.
 
-    Example: `uv run python send_message.py 'Do they lay eggs?'`
+    Example: `uv run send_message.py 'Do they lay eggs?'`
 5. Get the conversation history by querying the workflow.
 
-    Example: `uv run python get_history.py`
+    Example: `uv run get_history.py`
 6. The workflow will timeout after inactivity.

cloud_export_to_parquet/README.md

@@ -11,13 +11,13 @@ Before you start, please modify workflow input in `create_schedule.py` with your
 To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker:
 
 ```bash
-uv run python run_worker.py
+uv run run_worker.py
 ```
 
 This will start the worker. Then, in another terminal, run the following to execute the schedule:
 
 ```bash
-uv run python create_schedule.py
+uv run create_schedule.py
 ```
 
 The workflow should convert exported file in your input s3 bucket to parquet in your specified location.

context_propagation/README.md

@@ -6,11 +6,11 @@ this example, [contextvars](https://docs.python.org/3/library/contextvars.html)
 To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the
 worker:
 
-    uv run python worker.py
+    uv run worker.py
 
 This will start the worker. Then, in another terminal, run the following to execute the workflow:
 
-    uv run python starter.py
+    uv run starter.py
 
 The starter terminal should complete with the hello result and the worker terminal should show the logs with the
 propagated user ID contextual information flowing through the workflows/activities.

custom_converter/README.md

@@ -5,11 +5,11 @@ This sample shows how to make a custom payload converter for a type not natively
 To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the
 worker:
 
-    uv run python worker.py
+    uv run worker.py
 
 This will start the worker. Then, in another terminal, run the following to execute the workflow:
 
-    uv run python starter.py
+    uv run starter.py
 
 The workflow should complete with the hello result. If the custom converter was not set for the custom input and output
 classes, we would get an error on the client side and on the worker side.

custom_decorator/README.md

@@ -6,11 +6,11 @@ decorator that automatically configures an activity to heartbeat twice as freque
 To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the
 worker:
 
-    uv run python worker.py
+    uv run worker.py
 
 This will start the worker. Then, in another terminal, run the following to execute the workflow:
 
-    uv run python starter.py
+    uv run starter.py
 
 The workflow will be started, and then after 5 seconds will be sent a signal to cancel its forever-running activity.
 The activity has a heartbeat timeout set to 2s, so since it has the `@auto_heartbeater` decorator set, it will heartbeat

dsl/README.md

@@ -11,19 +11,19 @@ For this sample, the optional `dsl` dependency group must be included. To includ
 To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the
 worker:
 
-    uv run python worker.py
+    uv run worker.py
 
 This will start the worker. Then, in another terminal, run the following to execute a workflow of steps defined in
 [workflow1.yaml](workflow1.yaml):
 
-    uv run python starter.py workflow1.yaml
+    uv run starter.py workflow1.yaml
 
 This will run the workflow and show the final variables that the workflow returns. Looking in the worker terminal, each
 step executed will be visible.
 
 Similarly we can do the same for the more advanced [workflow2.yaml](workflow2.yaml) file:
 
-    uv run python starter.py workflow2.yaml
+    uv run starter.py workflow2.yaml
 
 This sample gives a guide of how one can write a workflow to interpret arbitrary steps from a user-provided DSL. Many
 DSL models are more advanced and are more specific to conform to business logic needs.

encryption/README.md

@@ -12,11 +12,11 @@ For this sample, the optional `encryption` dependency group must be included. To
 To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the
 worker:
 
-    uv run python worker.py
+    uv run worker.py
 
 This will start the worker. Then, in another terminal, run the following to execute the workflow:
 
-    uv run python starter.py
+    uv run starter.py
 
 The workflow should complete with the hello result. To view the workflow, use [temporal](https://docs.temporal.io/cli):
 
@@ -31,7 +31,7 @@ Note how the result looks like (with wrapping removed):
 This is because the data is encrypted and not visible. To make data visible to external Temporal tools like `temporal` and
 the UI, start a codec server in another terminal:
 
-    uv run python codec_server.py
+    uv run codec_server.py
 
 Now with that running, run `temporal` again with the codec endpoint:
 

gevent_async/README.md

@@ -17,12 +17,12 @@ For this sample, the optional `gevent` dependency group must be included. To inc
 To run the sample, first see [README.md](../README.md) for prerequisites such as having a localhost Temporal server
 running. Then, run the following from this directory to start the worker:
 
-    uv run python worker.py
+    uv run worker.py
 
 This will start the worker. The worker has a workflow and two activities, one `asyncio` based and one gevent based. Now
 in another terminal, run the following from this directory to execute the workflow:
 
-    uv run python starter.py
+    uv run starter.py
 
 The workflow should run and complete with the hello result. Note on the worker terminal there will be logs of the
 workflow and activity executions.

hello/README.md

@@ -5,7 +5,7 @@ These samples show basic workflow and activity features.
 To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to run the
 `hello_activity.py` sample:
 
-    uv run python hello_activity.py
+    uv run hello_activity.py
 
 The result will be:
 

langchain/README.md

@@ -13,11 +13,11 @@ Export your [OpenAI API key](https://platform.openai.com/api-keys) as an environ
 To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the
 worker:
 
-    uv run python worker.py
+    uv run worker.py
 
 This will start the worker. Then, in another terminal, run the following to execute a workflow:
 
-    uv run python starter.py
+    uv run starter.py
 
 Then, in another terminal, run the following command to translate a phrase:
 

message_passing/introduction/README.md

@@ -10,9 +10,9 @@ Then create two terminals and `cd` to this directory.
 
 Run the worker in one terminal:
 
-    uv run python worker.py
+    uv run worker.py
 
 And execute the workflow in the other terminal:
 
-    uv run python starter.py
+    uv run starter.py
 

message_passing/safe_message_handlers/README.md

@@ -12,10 +12,10 @@ To run, first see [README.md](../../README.md) for prerequisites.
 
 Then, run the following from this directory to run the worker:
 \
-    uv run python worker.py
+    uv run worker.py
 
 Then, in another terminal, run the following to execute the workflow:
 
-    uv run python starter.py
+    uv run starter.py
 
 This will start a worker to run your workflow and activities, then start a ClusterManagerWorkflow and put it through its paces.

message_passing/update_with_start/lazy_initialization/README.md

@@ -8,11 +8,11 @@ To run, first see the main [README.md](../../../README.md) for prerequisites.
 
 Then run the following from this directory:
 
-    uv run python worker.py
+    uv run worker.py
 
 Then, in another terminal:
 
-    uv run python starter.py
+    uv run starter.py
 
 This will start a worker to run your workflow and activities, then simulate a backend application receiving
 requests to add items to a shopping cart, before finalizing the order.

message_passing/waiting_for_handlers/README.md

@@ -16,11 +16,11 @@ To run, open two terminals and `cd` to this directory in them.
 
 Run the worker in one terminal:
 
-    uv run python worker.py
+    uv run worker.py
 
 And run the workflow-starter code in the other terminal:
 
-    uv run python starter.py
+    uv run starter.py
 
 
 Here's the output you'll see:

message_passing/waiting_for_handlers_and_compensation/README.md

@@ -13,11 +13,11 @@ To run, open two terminals and `cd` to this directory in them.
 
 Run the worker in one terminal:
 
-    uv run python worker.py
+    uv run worker.py
 
 And run the workflow-starter code in the other terminal:
 
-    uv run python starter.py
+    uv run starter.py
 
 
 Here's the output you'll see:

open_telemetry/README.md

@@ -12,11 +12,11 @@ To run, first see [README.md](../README.md) for prerequisites. Then run the foll
 
 Now, from this directory, start the worker in its own terminal:
 
-    uv run python worker.py
+    uv run worker.py
 
 Then, in another terminal, run the following to execute the workflow:
 
-    uv run python starter.py
+    uv run starter.py
 
 The workflow should complete with the hello result.