How to monitor the filesystem and have streamlit updated when some files are modified?

šŸŽˆ Using Streamlit
3

Hey @EricDepagne, welcome to Streamlit!

A few things to know about Streamlitā€™s execution model (apologies if any of this is already obvious):

  • To render your app to the browser, Streamlit runs your Python script from top to bottom. Various st.foo() function calls cause messages to be sent to the browser, which then draws widgets and text and whatnot.
  • When Streamlit detects that your app needs to update, it reruns your script from top-to-bottom again.
  • There are two situations that cause Streamlit to rerun your script:
    • The script itself (or any module it imports or transitively depends on) changes on disk.
    • The user interacts with a widget in the browser.

This is all to say, Streamlit does not consider your app to be ā€œrunningā€ once it finishes its top-to-bottom execution. In your case, the Watchdog thread you spawned was still running in the Streamlit Python process, but Streamlitā€™s script-runner code was no longer executing your app (and in fact, this probably results in a leak, since that Watchdog thread is still watching files, but those callbacks arenā€™t doing anything.)

(Note also that if your app is unconditionally creating a watchdog.Observer instance, a new Observer will be created each time the app is re-run.)

What I think you want to do here is:

  1. Create a watchdog.Observer only once (and not each time Streamlit re-runs the app).
  2. Have that Observer trigger re-runs of your app.

#1 is achievable with some minor abuse of @st.cache, which lets you run a piece of code only once, rather than every time your app is re-run:

@st.cache
def install_monitor():
    watchdog = Watchdog()
    # watchdog.hook = ... <-- We'll deal with this next
    observer = Observer()
    observer.schedule(watchdog, path=ā€™.ā€™, recursive=False)
    observer.start()

#2 is achievable with some major abuse of Streamlitā€™s rerun logic, which uses Watchdog under the hood to detect when source files have changed and your app should be re-run. As we say in New England, this is wicked sketchy and subject to break. Basically, if you create a dummy module (letā€™s just say itā€™s called dummy.py), and import that module from your Streamlit app:

import streamlit as st
import dummy
# ... rest of your app

Then, if the dummy module is modified, Streamlit will re-run your app script, because your app imports dummy. So if your on_modified hook rewrites the contents of dummy.py when a watched file changes, it will trigger a rerun.

Hereā€™s a working example:

import datetime as dt

from watchdog.events import FileSystemEventHandler
from watchdog.observers import Observer

import reload_test.dummy
import streamlit as st


class Watchdog(FileSystemEventHandler):
    def __init__(self, hook):
        self.hook = hook

    def on_modified(self, event):
        self.hook()


def update_dummy_module():
    # Rewrite the dummy.py module. Because this script imports dummy,
    # modifiying dummy.py will cause Streamlit to rerun this script.
    dummy_path = reload_test.dummy.__file__
    with open(dummy_path, "w") as fp:
        fp.write(f'timestamp = "{dt.datetime.now()}"')


@st.cache
def install_monitor():
    # Because we use st.cache, this code will be executed only once,
    # so we won't get a new Watchdog thread each time the script runs.
    observer = Observer()
    observer.schedule(
        Watchdog(update_dummy_module),
        path="reload_test/data",
        recursive=False)
    observer.start()


install_monitor()
st.write("data file updated!", dt.datetime.now())

This is the directory structure Iā€™m using for the above app:

reload_test/
  data/  # <-- modifying a file in here will trigger a rerun
  __init__.py
  app.py
  dummy.py

If you edit any file inside the data/ directory, the appā€™s Watchdog instance will notice that and trigger the update_dummy_module callback. That function will then rewrite dummy.py (I have it just assigning the current timestamp to a dummy variable, so that the contents of dummy.py are different each time the rewrite is triggered). Then Streamlit will notice that dummy.py has been updated, and since your app imports that module, your app will be rerun.

All that said, we have tentative plans to allow triggering re-runs in a less hacky way. As you can tell, this sort of thing isnā€™t a use-case we were anticipating at launch!

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