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<@ULVA73B9P> Where does prefect pull the code and ...
# ask-marvin
t
@Marvin Where does prefect pull the code and run in a local server setup. I am doing a pull code from git and it says git command not found.
m
It seems you're experiencing an issue with Prefect trying to use Git in a local server setup, but the 
git
command is not found. This usually occurs when the Git command-line tool isn't installed on your system, or it's not accessible in your system's PATH. Here's the rundown on how Prefect handles Git-related operations and what might be causing the error: 1. Prefect's Interaction with Git: - When pulling code from a Git repository, Prefect uses the Git command-line tool to clone repositories. If your system doesn't have this tool installed or if it's not in your PATH, Prefect won't be able to execute its commands. 2. Checking Git Installation: - Ensure Git is installed on your system. You can verify this by running 
git --version
in your terminal. If it's not installed, you can download it from git-scm.com. 3. Adding Git to PATH: - If Git is installed but not recognized, make sure it's included in your system's PATH. This setup allows other programs to use Git's command-line functions. 4. Specific Prefect Documentation on Git Use: - Prefect documentation explains how Git can be used for storing and retrieving flow code. You might find these sections helpful: Prefect 2.x Managing Integrations and Prefect 3.x Deployment. By ensuring that Git is correctly set up, you should be able to resolve the "git command not found" error in Prefect's local server setup. If Prefect were a deep philosopher, it would probably lament the comedy in not finding its essential command—not unlike a chef without ingredients! Let me know if there's anything else you need help with!
n
this is likely because the machine running your worker (where you ran 
prefect worker start
) does not have the git cli installed
t
but my ubuntu server has git installed for all users
@Marvin tell me how to resolve this error: Nov 15 165955 prefect-vm poetry[29394]: 165955.093 | INFO | prefect.flow_runs.worker - Worker 'ProcessWorker eefe6a39-3ea3-415e-987a-41f36bc0109f' submitting flow run 'e791412f-f3f4> Nov 15 165955 prefect-vm poetry[29394]: 165955.293 | INFO | prefect.flow_runs.worker - Opening process... Nov 15 165955 prefect-vm poetry[29394]: 165955.336 | INFO | prefect.flow_runs.worker - Completed submission of flow run 'e791412f-f3f4-483e-9fe2-6f2f44b1e30a' Nov 15 165958 prefect-vm poetry[29394]: 165958.786 | ERROR | prefect.engine - Engine execution of flow run 'e791412f-f3f4-483e-9fe2-6f2f44b1e30a' exited with unexpected exception Nov 15 165958 prefect-vm poetry[29394]: Traceback (most recent call last): Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/deployments/steps/core.py", line 161, in run_steps Nov 15 165958 prefect-vm poetry[29394]: step_output = await run_step(step, upstream_outputs) Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/deployments/steps/core.py", line 132, in run_step Nov 15 165958 prefect-vm poetry[29394]: result = await from_async.call_soon_in_new_thread( Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/_internal/concurrency/calls.py", line 321, in aresult Nov 15 165958 prefect-vm poetry[29394]: return await asyncio.wrap_future(self.future) Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/_internal/concurrency/calls.py", line 383, in _run_async Nov 15 165958 prefect-vm poetry[29394]: result = await coro Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/_internal/retries.py", line 43, in wrapper Nov 15 165958 prefect-vm poetry[29394]: return await func(*args, **kwargs) Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/utilities/asyncutils.py", line 389, in ctx_call Nov 15 165958 prefect-vm poetry[29394]: result = await async_fn(*args, **kwargs) Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/deployments/steps/pull.py", line 132, in git_clone Nov 15 165958 prefect-vm poetry[29394]: await storage.pull_code() Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/runner/storage.py", line 228, in pull_code Nov 15 165958 prefect-vm poetry[29394]: await self._clone_repo() Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/runner/storage.py", line 252, in _clone_repo Nov 15 165958 prefect-vm poetry[29394]: await run_process(cmd) Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/anyio/_core/_subprocesses.py", line 85, in run_process Nov 15 165958 prefect-vm poetry[29394]: async with await open_process( Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/anyio/_core/_subprocesses.py", line 184, in open_process Nov 15 165958 prefect-vm poetry[29394]: return await get_async_backend().open_process( Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/anyio/_backends/_asyncio.py", line 2532, in open_process Nov 15 165958 prefect-vm poetry[29394]: process = await asyncio.create_subprocess_exec( Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/usr/lib/python3.11/asyncio/subprocess.py", line 218, in create_subprocess_exec Nov 15 165958 prefect-vm poetry[29394]: transport, protocol = await loop.subprocess_exec( Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/usr/lib/python3.11/asyncio/base_events.py", line 1694, in subprocess_exec Nov 15 165958 prefect-vm poetry[29394]: transport = await self._make_subprocess_transport( Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/usr/lib/python3.11/asyncio/unix_events.py", line 207, in _make_subprocess_transport Nov 15 165958 prefect-vm poetry[29394]: transp = _UnixSubprocessTransport(self, protocol, args, shell, Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/usr/lib/python3.11/asyncio/base_subprocess.py", line 36, in init Nov 15 165958 prefect-vm poetry[29394]: self._start(args=args, shell=shell, stdin=stdin, stdout=stdout, Nov 15 165958 prefect-vm poetry[29394]: File "/usr/lib/python3.11/asyncio/unix_events.py", line 810, in _start Nov 15 165958 prefect-vm poetry[29394]: self._proc = subprocess.Popen( Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/usr/lib/python3.11/subprocess.py", line 1024, in init Nov 15 165958 prefect-vm poetry[29394]: self._execute_child(args, executable, preexec_fn, close_fds, Nov 15 165958 prefect-vm poetry[29394]: File "/usr/lib/python3.11/subprocess.py", line 1901, in _execute_child Nov 15 165958 prefect-vm poetry[29394]: raise child_exception_type(errno_num, err_msg, err_filename) Nov 15 165958 prefect-vm poetry[29394]: FileNotFoundError: [Errno 2] No such file or directory: 'git'
m
Your message was too long by 1815 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:
tell me how to resolve this error:
Nov 15 165955 prefect-vm poetry[29394]: 165955.093 | INFO | prefect.flow_runs.worker - Worker 'ProcessWorker eefe6a39-3ea3-415e-987a-41f36bc0109f' submitting flow run 'e791412f-f3f4> Nov 15 165955 prefect-vm poetry[29394]: 165955.293 | INFO | prefect.flow_runs.worker - Opening process... Nov 15 165955 prefect-vm poetry[29394]: 165955.336 | INFO | prefect.flow_runs.worker - Completed submission of flow run 'e791412f-f3f4-483e-9fe2-6f2f44b1e30a' Nov 15 165958 prefect-vm poetry[29394]: 165958.786 | ERROR | prefect.engine - Engine execution of flow run 'e791412f-f3f4-483e-9fe2-6f2f44b1e30a' exited with unexpected exception Nov 15 165958 prefect-vm poetry[29394]: Traceback (most recent call last): Nov 15 165958 prefect-vm poetry[29394]:
t
@Marvin tell me how to resolve this error: Nov 15 165958 prefect-vm poetry[29394]: ^^^^^^^^^^^^^^^^^ Nov 15 165958 prefect-vm poetry[29394]: File "/usr/lib/python3.11/subprocess.py", line 1024, in init Nov 15 165958 prefect-vm poetry[29394]: self._execute_child(args, executable, preexec_fn, close_fds, Nov 15 165958 prefect-vm poetry[29394]: File "/usr/lib/python3.11/subprocess.py", line 1901, in _execute_child Nov 15 165958 prefect-vm poetry[29394]: raise child_exception_type(errno_num, err_msg, err_filename) Nov 15 165958 prefect-vm poetry[29394]: FileNotFoundError: [Errno 2] No such file or directory: 'git'
m
The error you're experiencing, 
FileNotFoundError: [Errno 2] No such file or directory: 'git'
, commonly indicates that the Git command-line tool isn't installed on your server or it's not in your system's PATH, which is necessary for Prefect to access and use Git. Here's how you can resolve the issue: 1. Install Git: - If Git is not installed, you’ll need to install it. On a Debian-based system, you can do this using:
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sudo apt update
     sudo apt install git
- For other systems, you can download and install Git from the official Git website. 2. Ensure Git is in PATH: - If Git is installed but not recognized, add it to your system's PATH. You can verify this by running 
git --version
in your terminal. It should return the version number. - If it returns an error, you’ll need to add Git’s installation folder to your system’s PATH environment variable. 3. Documentation References: - Prefect documentation highlights the need for Git in managing integrations and storing code. More details can be found here: - Prefect 2.x Integrations - Prefect 3.x Git-based Storage Concept 4. Related Issues: - There are related GitHub issues discussing file path issues in Prefect, such as those involving storage blocks and deployment paths. You might find this GitHub issue relevant as it covers similar 
FileNotFoundError
in different contexts. By following these steps, you should be able to resolve the missing 'git' command issue. A system without Git is like a poet without a quill—nothing gets written! If you encounter further issues, feel free to ask for more assistance.
t
@Marvin i see Can't connect to Server API at http://127.0.0.1:4200/api on the ui while running prefect on self hosted server
m
It looks like you're encountering a common issue when trying to connect to the Prefect API on a self-hosted server. The error message "Can't connect to Server API at http://127.0.0.1:4200/api" suggests there might be a configuration or network issue. Here's how you can resolve it: 1. Server Instance Setup: - Ensure your Prefect server is properly running. You can start it using the command:
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prefect server start
- Verify that there are no errors when starting the server and check the terminal output for any issues. 2. Check the API URL Configuration: - Make sure your Prefect configuration specifies the correct API URL. For a local setup, it should typically be:
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PREFECT_API_URL="<http://127.0.0.1:4200/api>"
- You can set this environment variable within your terminal session or in a configuration file, if applicable. 3. Network and Firewall Settings: - Confirm that there are no firewall settings blocking access to the port 
4200
. Your local machine should allow connections to this port. - If you have proxies configured in your environment, verify that they are set correctly or adjust your NO_PROXY settings to allow local connections. 4. Refer to Documentation: - The Prefect documentation provides guidelines for hosting a server and configuring the API URL. Check out: - Prefect 2.x Settings - Prefect 3.x Self-hosting By ensuring your server is running, the API URL is correctly set, and network settings permit access, you should resolve the connectivity issue. It's all about making sure the bits and bytes find their way home! If the issue persists, double-check your system's setup against the documentation. If you need further assistance, feel free to ask!
t
@Marvin if my server is hosted via reverse proxy on prefect.google.com but my prefect server start is hosted on 0.0.0.0 and port 4200, what should my api url be
m
When hosting your Prefect server behind a reverse proxy, your API URL should point to the external URL that's accessible via the proxy. Since your server is exposed through 
<http://prefect.google.com>
, that's the URL your applications and clients should use to connect to the API. Here's how you should configure your API URL: - API URL: 
<http://prefect.google.com/api>
This URL assumes that the reverse proxy is configured to forward requests made to 
/api
to your internal Prefect server running on 
<http://0.0.0.0:4200>
. Make sure your reverse proxy is set up correctly to map paths and handle traffic to the appropriate backend services. Also, ensure that all necessary headers and connection protocols are managed correctly by your reverse proxy to facilitate the seamless routing of requests. With these settings, everything should work smoothly, and you'll seem like a network magician to anyone observing your setup! If there are any hiccups, let me know, and I'll gladly assist further!
t
@Marvin Can't connect to Server API at http://prefect.google.com/api. Check that it's accessible from your machine. this popup returns when i am logged into prefect
m
The error message you're encountering suggests that your reverse proxy may not be correctly configured to forward requests to your Prefect server. Here's a step-by-step guide to resolving this issue: 1. Verify Reverse Proxy Configuration: - Ensure your reverse proxy is set to forward requests from 
<http://prefect.google.com/api>
to your internal server running on 
<http://0.0.0.0:4200/api>
. - Depending on your reverse proxy (like Nginx or Traefik), the configuration might look something like this: For Nginx:
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server {
         listen 80;

         server_name <http://prefect.google.com|prefect.google.com>;

         location /api {
             proxy_pass <http://localhost:4200;>
             proxy_set_header Host $host;
             proxy_set_header X-Real-IP $remote_addr;
             proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
             proxy_set_header X-Forwarded-Proto $scheme;
         }
     }
2. Check Prefect Settings: - Set the 
PREFECT_API_URL
to your external proxy URL:
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PREFECT_API_URL="<http://prefect.google.com/api>"
- Set the 
PREFECT_UI_API_URL
if applicable to ensure the UI connects to the right API endpoint. 3. Network and Firewall: - Confirm that your network or firewall settings are allowing traffic through the necessary ports. 4. Useful Documentation and Tips: - Refer to Prefect 2.x Guides and Prefect 3.x Settings for more detailed instructions on configuring API URLs and reverse proxies while hosting Prefect. By ensuring your reverse proxy correctly routes requests to the Prefect API and your environment variables point to the external URL, you should be able to resolve this connectivity issue. It's a bit like making sure all paths lead to the right destination—like a well-mannered postal system for your network requests! If this doesn't resolve the issue, feel free to reach out for more help.
t
@Marvin refactor you ouptut as i am using caddy for reverse proxy and ouath2 proxy
m
Great, if you're using Caddy with OAuth2 proxy, the configuration will differ from typical Nginx setups. Here’s how you can set it up: 1. Caddy Configuration: - You'll need to configure Caddy to handle requests and forward them to your local Prefect server. Here's a basic example:
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plaintext
     <http://prefect.google.com|prefect.google.com> {
         reverse_proxy /api/* localhost:4200 {
             header_up X-Real-IP {remote}
             header_up X-Forwarded-For {host}
             header_up X-Forwarded-Port {server_port}
             header_up X-Forwarded-Proto {scheme}
         }

         route /* {
             # OAuth2 proxy configuration block
             oauth2_proxy {
                 client_id     YOUR_CLIENT_ID
                 client_secret YOUR_CLIENT_SECRET
                 # config your provider details here
             }
             reverse_proxy localhost:4200
         }
     }
2. Prefect API URL: - Ensure your Prefect API URL is set to the external URL:
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PREFECT_API_URL="<http://prefect.google.com/api>"
3. Verify OAuth2 Proxy Configuration: - Make sure your OAuth2 proxy is set up correctly, providing the necessary client IDs and secrets for authentication. 4. Documentation and Tips: - Review the Caddy documentation for more information on configuring reverse proxies and headers. - Check OAuth2 proxy documentation for setting up your provider and configuration options. This setup ensures that Caddy correctly handles and forwards requests, and that your Prefect installation is aware of the correct API endpoint. A Caddy-powered Prefect server should hum along nicely with this setup. If Aristotle had configured servers, he'd have used Caddy’s simplicity too—more time for philosophy, less time for debugging! If you need further assistance, just let me know.
t
@Marvin why can i not add a block from ui, i have the extras such as github, slack, shell already installed
m
If you're unable to add a block from the UI, even after installing extras like GitHub, Slack, and Shell, a few potential issues and troubleshooting steps are worth considering: 1. Block Types Not Registered: - If a block isn't visible in the UI, check if it's registered. You can use the CLI to ensure block types are registered using:
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prefect block register -m <module_name>
2. UI Bugs or Configuration: - There might be UI-related issues where blocks aren't displayed due to a bug. Specifically, issues can arise when block class fields are complex types like 
Union
. Check this GitHub issue that mentions UI errors with such field types. 3. Permissions and Roles: - Ensure that your user account has sufficient permissions to add or modify blocks. Sometimes role-based access control settings might need updating to allow greater functionality within the UI. 4. Confirm Installations: - Verify that the extra modules (GitHub, Slack, Shell) are installed correctly and compatible with your Prefect version. Use:
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shell
     pip show prefect-github prefect-slack prefect-shell
- Check for available updates to these integrations as updates might include necessary fixes. 5. Log and Debugging Details: - Check your browser's developer console (DevTools). It might show errors when interacting with the UI, providing clues about what's not working. 6. Documentation Insight: - Consult the Prefect documentation on using blocks and relevant configurations. By ensuring that the blocks are registered correctly and checking for any UI-related issues, you should be able to resolve the problem. Fingers crossed that everything clicks into place—you deserve a perfectly functioning Prefect UI! If issues persist, more detailed checks or even reaching out to Prefect support might be necessary.
t
@Marvin here is an error i get while using poetry instead of pip install requirements on pull in prefect.yaml. Nov 16 190748 prefect-vm poetry[3086]: 190748.155 | ERROR | prefect.engine - Engine execution of flow run 'ee514afc-9e02-4d3f-9e86-51260277f915' exited with unexpected exception Nov 16 190748 prefect-vm poetry[3086]: Traceback (most recent call last): Nov 16 190748 prefect-vm poetry[3086]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/deployments/steps/core.py", line 161, in run_steps Nov 16 190748 prefect-vm poetry[3086]: step_output = await run_step(step, upstream_outputs) Nov 16 190748 prefect-vm poetry[3086]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 16 190748 prefect-vm poetry[3086]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/deployments/steps/core.py", line 132, in run_step Nov 16 190748 prefect-vm poetry[3086]: result = await from_async.call_soon_in_new_thread( Nov 16 190748 prefect-vm poetry[3086]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 16 190748 prefect-vm poetry[3086]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/_internal/concurrency/calls.py", line 321, in aresult Nov 16 190748 prefect-vm poetry[3086]: return await asyncio.wrap_future(self.future) Nov 16 190748 prefect-vm poetry[3086]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 16 190748 prefect-vm poetry[3086]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/_internal/concurrency/calls.py", line 383, in _run_async Nov 16 190748 prefect-vm poetry[3086]: result = await coro Nov 16 190748 prefect-vm poetry[3086]: ^^^^^^^^^^ Nov 16 190748 prefect-vm poetry[3086]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/deployments/steps/utility.py", line 193, in run_shell_script Nov 16 190748 prefect-vm poetry[3086]: raise RuntimeError( Nov 16 190748 prefect-vm poetry[3086]: RuntimeError: 
run_shell_script
failed with error code 1: Nov 16 190748 prefect-vm poetry[3086]: Poetry could not find a pyproject.toml file in /tmp/tmpwpnj527pprefect or its parents
m
Your message was too long by 391 tokens - please shorten it and try again. For reference, here's your message at the allowed limit:
here is an error i get while using poetry instead of pip install requirements on pull in prefect.yaml.
Nov 16 190748 prefect-vm poetry[3086]: 190748.155 | ERROR | prefect.engine - Engine execution of flow run 'ee514afc-9e02-4d3f-9e86-51260277f915' exited with unexpected exception Nov 16 190748 prefect-vm poetry[3086]: Traceback (most recent call last): Nov 16 190748 prefect-vm poetry[3086]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/deployments/steps/core.py", line 161, in run_steps Nov 16 190748 prefect-vm poetry[3086]: step_output = await run_step(step, upstream_outputs) Nov 16 190748 prefect-vm poetry[3086]: ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Nov 16 190748 prefect-vm poetry[3086]: File "/home/prefect/source/.venv/lib/python3.11/site-packages/prefect/deployments/steps/core.py", line 132, in run_step Nov 16 190748 prefect-vm poetry[3086]: result = await from_async
t
@Marvin here is an error i get while using poetry instead of pip install requirements on pull in prefect.yaml. Nov 16 190748 prefect-vm poetry[3086]: 190748.155 | ERROR | prefect.engine - Engine execution of flow run 'ee514afc-9e02-4d3f-9e86-51260277f915' exited with unexpected exception Nov 16 190748 prefect-vm poetry[3086]: RuntimeError: 
run_shell_script
failed with error code 1: Nov 16 190748 prefect-vm poetry[3086]: Poetry could not find a pyproject.toml file in /tmp/tmpwpnj527pprefect or its parents
m
The error you're experiencing indicates that Poetry can't locate a 
pyproject.toml
file within the directory being used in your Prefect flow. This file is required by Poetry to manage dependencies. Here’s how to resolve it: 1. Verify Directory Structure: - Ensure that your 
pyproject.toml
file is present in the root of your project directory where your flow and dependencies are managed. - When using Prefect's 
run_shell_script
to install dependencies with Poetry, make sure the script points to the correct directory containing the 
pyproject.toml
file. 2. Prefect Configuration: - In your 
prefect.yaml
, ensure that the pull step specifies the correct path where your 
pyproject.toml
resides. If the file is in a subdirectory, modify the script or change the working directory appropriately. 3. Environment Variables: - Check if any environment variables are affecting directory paths or file availability during script execution. Use 
expand_env_vars: true
if needed to resolve variables at runtime. 4. Documentation Insight: - For more on running scripts and managing dependencies, Prefect's troubleshooting guide and shell commands might offer useful examples and settings. By ensuring the 
pyproject.toml
is in the correct location and accessible during the flow's execution, you should be able to resolve this issue. It's a bit like ensuring the right keys are on the right ring—everything needs to be in its proper place! If you need further help, feel free to ask.
t
@Marvin here is how my pull block looks: pull: - prefect.deployments.steps.git_clone: id: clone-repo repository: https://github.com/org/prefect-data.git branch: staging credentials: "{{ prefect.blocks.github-credentials.data-creds }}" - prefect.deployments.steps.run_shell_script: id: install-dependencies script: poetry install stream_output: true
m
Your pull block looks structured correctly, but the error suggests that the 
poetry install
command can't find the 
pyproject.toml
file, likely because the script is executed in a directory that doesn't contain the file. Here’s how you can troubleshoot and fix the issue: 1. Check Clone Directory: - Ensure that the 
pyproject.toml
file is located in the root directory of the cloned repository (e.g., your GitHub repo 
prefect-data.git
). 2. Specify Working Directory: - Ensure that the 
run_shell_script
step is executed in the correct directory. You might need to change into the directory where the repository is cloned. Modify the script to include a 
cd
command:
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yaml
   pull:
     - prefect.deployments.steps.git_clone:
         id: clone-repo
         repository: "<https://github.com/org/prefect-data.git>"
         branch: staging
         credentials: "{{ prefect.blocks.github-credentials.data-creds }}"

     - prefect.deployments.steps.run_shell_script:
         id: install-dependencies
         script: |
           cd "{{ clone-repo.directory }}"
           poetry install
         stream_output: true
3. Add Variables or Debugging: - Use environment variables to debug paths or add an 
ls
command before 
poetry install
to check whether the script is running in a directory with the 
pyproject.toml
file. 4. Verify Prefect Setup: - Ensure Prefect has the necessary permissions and configurations to read the GitHub repository and execute shell scripts. By making sure the 
run_shell_script
is executed where the 
pyproject.toml
file is located, you should resolve this error. It's like finding your keys—or in this case, your file—in the last place you look! If something still doesn't seem right, don't hesitate to ask for more help.
t
@Marvin while cd into clone-repo directory, i get the following error: FileNotFoundError: [Errno 2] No such file or directory: 'cd'
m
The error occurs because 
cd
is a shell built-in command and might not be recognized directly in some contexts within the 
run_shell_script
step. Prefect executes the entire script as one command, and it may not correctly parse the 
cd
command if used improperly. Here's how to ensure you're using these commands correctly within a Prefect YAML configuration: 1. Ensure Script Shell Execution: - Make sure that you're constructing your shell commands correctly in the script block. The entire script needs to be a single executable shell script, not individual commands. 2. Concatenate Shell Commands: - Use a multi-line string (using the 
|
symbol) to execute multiple shell commands, ensuring they execute in the correct environment:
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yaml
pull:
  - prefect.deployments.steps.git_clone:
      id: clone-repo
      repository: "<https://github.com/org/prefect-data.git>"
      branch: staging
      credentials: "{{ prefect.blocks.github-credentials.data-creds }}"

  - prefect.deployments.steps.run_shell_script:
      id: install-dependencies
      script: |
        # Navigate to the cloned repo directory
        cd "$(dirname '{{ clone-repo.directory }}')"
        # List the files to debug the current directory context
        ls
        # Install dependencies
        poetry install
      stream_output: true
3. Script Debugging: - Include other debugging commands like 
ls
to ensure you're in the correct directory and the 
pyproject.toml
file exists. If the above doesn't resolve the issue, you might want to ensure the 
{{ clone-repo.directory }}
returns the correct path and is available in the context. It can sometimes be about finding the right path for your treasure—like X marking the spot! If anything remains unclear or the issue persists, feel free to reach out again.
t
@Marvin FileNotFoundError: [Errno 2] No such file or directory: 'cd'. I am getting the same error
m
The 
FileNotFoundError: [Errno 2] No such file or directory: 'cd'
error suggests an issue with how the script is executed. It seems the execution environment is interpreting 
cd
as a standalone command instead of part of a shell script. Here's a refined approach to ensure proper execution: 1. Combine Commands Correctly: - Use a script block that explicitly denotes a shell environment and correctly chains the commands. 2. Adjust the Script Content: - You might need to ensure the entire script is executed within a shell context. Here’s how to format the YAML:
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yaml
pull:
  - prefect.deployments.steps.git_clone:
      id: clone-repo
      repository: "<https://github.com/org/prefect-data.git>"
      branch: staging
      credentials: "{{ prefect.blocks.github-credentials.data-creds }}"

  - prefect.deployments.steps.run_shell_script:
      id: install-dependencies
      script: |
        set -e  # Ensure the shell exits if any subcommand fails
        cd "$(dirname "{{ clone-repo.directory }}/repo")"
        ls  # Verify the contents of the current directory
        poetry install
      stream_output: true
### Notes: - 
set -e
: This command ensures that if any of the subsequent commands fail, the script will terminate immediately, making debugging easier. - Path Usage: Ensure 
"{{ clone-repo.directory }}/repo"
accurately reflects the clone directory path. Sometimes additional path adjustments might be required based on the directory structure of your repository. ### Debugging Steps: 1. Verify Clone Directory Path: - Ensure the path used in 
cd
matches the actual path of the cloned repository. Add an extra 
ls -la
before the 
cd
command to see what's available in the current directory. 2. Shell Environment: - Encapsulate the entire string as a shell script by chaining commands properly within the 
script
section. ### Runtime Suggestions: - If the configuration still fails, manually executing similar scripts in a bash shell on your system might provide additional insights into directory path issues or syntax errors. This setup ensures the commands are executed correctly within a shell capable of handling 
cd
, and the correct directory context is maintained for executing 
poetry install
. Let me know if further assistance is needed!
t
@Marvin what is a prefect local recipe, and how is it different from git recipie
m
In Prefect, a local recipe and a git recipe are part of the deployment configuration options specified in the 
prefect.yaml
file. These recipes help set up and manage how your Prefect deployments handle flow code and dependencies. Here's a quick rundown of the two: 1. Local Recipe: - The local recipe configures your deployment to work with code that is available locally, on the file system. This is useful when you want to keep your flow code in the same environment where it will be executed. - Local recipes do not involve fetching code from external repositories but rather work directly with files present on the local server or machine. 2. Git Recipe: - The git recipe, on the other hand, involves pulling flow code from a Git repository. It is particularly useful if your code is stored in a version-controlled environment like GitHub or GitLab. - When initialized in a git repository, the Prefect 
prefect.yaml
file will use the git recipe to handle code deployment by specifying how to clone the repository, manage branches, and handle credentials. When you run 
prefect init
, Prefect can suggest which recipe to use based on your environment structure. If you're already in a git repository, Prefect may automatically choose the git recipe. For further details, you can check the Prefect documentation on prefect.yaml and deployment configuration. Essentially, it's all about structuring your work environment so that Prefect knows where to find and how to handle your code—whether locally or via a distributed version control system like Git. Finding the right recipe is as satisfying as finding the right ingredients for your favorite dish! If there's anything else I can assist with, let me know!
t
@Marvin how does pull block in prefect.yaml work when local or git recipe is used
m
In Prefect, the 
pull
block within a 
prefect.yaml
file specifies how to prepare your flow's code for execution. It outlines the steps necessary to fetch or prepare the code each time a deployment runs. The behavior of the 
pull
block depends on the recipe being used: 1. Local Recipe: - Objective: Utilize code already present on the local filesystem. - Process: The 
pull
step doesn't need to clone repositories or interact with remote servers. Instead, it might involve setting the working directory using a 
set_working_directory
step. This is used to ensure the execution environment targets the correct local path where your Prefect flow code resides. 2. Git Recipe: - Objective: Fetch the flow code from a Git repository. - Process: Utilizes the 
git_clone
step to retrieve code from a specified Git repository and branch. You provide necessary details like the repository URL and optionally, branch names, and credentials. The flow code is dynamically fetched at runtime, ensuring you always run the latest version defined in the repo. Typical Steps in a Pull Section: - 
set_working_directory:
 Defines where on your system your code should be when the flow is executed or imported. - 
git_clone:
 Clones a given repository and branch to ensure the flow's code is up-to-date. - 
pull_from_{cloud}:
 Pulls a working directory from a cloud storage service (e.g., S3) if needed. References for further reading: - Prefect 2.x Deployment Guide - Prefect 3.x Deployment Concepts The recipe choice affects how Prefect sets up and manages the environment for your flow's code execution, allowing seamless integration with existing development and deployment workflows. If there's anything more specific you need, please let me know!
n
the "recipes" are just boilerplate conducive to certain ways of using 
prefect.yaml
i.e. do you often bake code into images or clone it down at runtime etc there are a bunch of examples here
t
@Marvin why do i get this error when running flows: _pickle.PicklingError: Pickling client objects is explicitly not supported.
m
The error message 
_pickle.PicklingError: Pickling client objects is explicitly not supported
suggests an issue related to trying to serialize an object (in this case, a client object) that's not designed for pickling. This often happens with client objects from libraries such as Google Cloud clients. Here’s how you can tackle this issue: 1. Understand Serialization in Prefect: - Prefect tasks may involve distributed execution, which can require object serialization for task inputs or outputs. - Client objects from libraries often hold state or configuration that cannot be serialized directly, leading to this error. 2. Solution Steps: - Avoid Client Objects in Task Signatures: - Don’t pass client instances directly between tasks. Instead, instantiate client objects within the task where they're needed. - For example, if using a Google Cloud client, create the client within the task function rather than passing it as an argument.
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python
   from prefect import task, flow
   from google.cloud import bigquery

   @task
   def query_data():
       client = bigquery.Client()  # Create the client within the task
       query_string = "SELECT * FROM your_table"
       result = client.query(query_string).result()
       return result

   @flow
   def my_flow():
       result = query_data()
       print(result)
3. Use Proper Serialization: - If your tasks need to pass data that can't be serialized directly, consider using serialization-friendly formats like JSON or handle data exchange using temporary files or cloud storage, which are readable by both source and destination tasks. 4. References and Documentation: - Documentation on Prefect’s pickle serializer explains some benefits and limitations of using pickle in Prefect. - Check related GitHub Issue on Pickling Client Errors for more details and community discussions about handling these errors. By structuring your task implementations to avoid passing non-serializable objects directly between tasks, you can mitigate issues related to pickling errors. It's like making sure you pack safely for a trip—only take things that won’t cause security alerts! If you have more questions, feel free to ask.
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