I have a problem with my Dash application put in a server of a remote office. Two users running the app will experience interactions with each other due to table import followed by table pricing (the code for pricing is around 10,000 lines and pull out 8 tables). While looking on the internet, I saw that to solve this problem, it was enough to create html.Div preceded by the conversation of dataframes in JSON. However, this solution is not possible because I have to store 9 tables totaling 200,000 rows and 500 columns. So, I looked into the cache solution. However, this option does not create errors but increases the execution time of the program considerably. Going from a table of 20,000 vehicles to 200,000 it increases the compute time by almost * 1,000 and it is horrible every time I change the settings of the graphics.
I use cache filesystem and i used the exemple 4 of this : https://dash.plotly.com/sharing-data-between-callbacks. By doing some time calculations, I noticed that it is not accessing the cache that is the problem (about 1sec) but converting the JSON tables to dataframe (almost 60 seconds per callback). About 60 seconds is the time also corresponding to the pricing, so it is the same to call the cache in a callback as it is to price in a callback.
1/ do you have an idea that would save a dataframe not a JSON in the form of a cache or with a technique like the invisible html.Div or a cookie system or whatever other methods ?
2/ with the Redis or Memcached, we have to provide return json?
2/ If so, how do we set it up, taking example 4 from the previous link because I have an error "redis.exceptions.ConnectionError: Error 10061 connecting to localhost: 6379. No connection could be established because l target computer expressly refused it. " ?
3/ Do you also know if turning off the application automatically deletes the cache without following the default_timeout?
