Black Lives Matter. Please consider donating to Black Girls Code today.
Dash HoloViews is now available! Check out the docs.

Updating global dataframe periodically


I’m connecting to firebase (a real time database), creating a global pandas DataFrame and using this to generate various plots.

All I want to do is re-run one query every x minutes to keep this DataFrame fresh but every example I’ve seen implies you either need to:

a) Run a seperate query in every callback
b) Convert the data to json and hide it in a div

I thought this would be straightforward to do without resorting to the above…am I missing something?


There is also
c) Re-run the query every x minutes and save it to a .csv file in a separate process. Replace your dataframe variable (e.g. df) in your code with a function like:

def df():
   return pd.read_csv(...)

d) Cache the query with flask caching, see Replace your dataframe variable (e.g. df) in your code with a function like (pseucode, I haven’t run this myself):

@cache.memoize(timeout=60*5) # 5 minutes
def compute_df():
   # [...] run query
   return df.to_json() # serialize so that it can be easily written to a file for caching

def get_df():
    return pd.read_json(compute_df())

df = get_df()

Sorry for trying to awake this old thread but I have a very similar problem where the data of interest in coming from Kafka. Thus I had a look at this code which is linked in the “Show and Tell” thread. But it is also using a global DF that is updated. Just for clarification: This is not the way to go, right?

Global variables like are not safe in Dash. I explain why in the user guide:

To update global dataframe periodically, I recommend checking out this example:

1 Like

Thanks for the clarification, Chris! Yes, your (btw great) user guide made me realise that I should do it in a different way. But the linked project from “Show & Tell” made me wonder whether it would be okay in some cases. The solution based on Redis and Celery looks interesting, thanks!

@chriddyp i wonder how can i apply mysql instead of redis in the example you gave. any hint?