urlx | Golang pkg for URL parsing and normalization | Parser library

How to post a request to get cookie values and post new request by the previously obtained cookie By using Go language

here first post request is generating a variable cookie in the form [SID=pcmPXXx+fidX1xxxX1cuK; Path=/; HttpOnly; SameSite=Strict]"

but i can't send this cookie to another post request (getting error).

sample go file with comments

I used this code until recently

I'm trying to update/get values inside ScrollView, like this follow code:

I am trying to get my azure web app to read the sqlite3 module I installed using npm install sqlite3

if I made a folder called nodetest and make a index.js file with the following code, it works no problem: (meaning require('sqlite3'); doesn't cause an error)

I have dropdowns and Entry controls inside a Load Funcn it is called Everytime button is clicked ! Items get added in stacklayout !

These funcn can be called many a times depending upon the user I have to pass all those values in form or rows in IEnumerable ! Now only 1 row is passing ! 2nd Row is overriding the values first row ! Here is the code:

This is mine api it expects two parameters !

So I am scraping same web pages with BS4, as the data is stored in tables it is pretty simple process. Identify the table and read it using: df1 = pd.read_html(str(table))

Problem is that tables are similar but not always the same, meaning, number of columns is not always the same. E.g. Table on page 1 has following columns: Id, Name, DOB, College, Years_experience, Nationality , while the same table on page 2 has the same columns expect for College. So it is:

Id, Name, DOB, College, Years_experience, Nationality

vs

Id, Name, DOB, Years_experience, Nationality

As I would like to store the data to single CSV, my question is how I can define all the columns, and if table is missing some columns, that it fills null values to CSV.

So something like: check for column names, if not found then fill null values to all rows.

Is there any simple solution for this, or I need to create dict and do everything manually?

Btw; if there is general better solution for this problem it doesn't have to be done with Pandas, just I got used to it as it is super easy to read HTML table

I am doing something like:

So I am doing something like:

This is such a weird problem I don't even know how to ask, but I'll try. I have some json files that have web scrape data in them, multiple entries per file and they look like this: