* Import 
#+begin_src python
import json  # to parse data
import requests # to get data
import pandas as pd # work with data
from mastodon import Mastodon # to get the user id
from datetime import date # to get the current date
import subprocess # for getting access token from pass
from bs4 import BeautifulSoup # to more easily read the html output
#+end_src
* Get/refresh data
- I used [[https://jrashford.com/2023/02/13/how-to-scrape-mastodon-timelines-using-python-and-pandas/][this]] setup.
- Only have to be refreshed (run) every now and then
#+begin_src python
# Get user id
instance = "https://social.edu.nl"
username = "mishavelthuis"
id = json.loads(requests.get("https://social.edu.nl/api/v1/accounts/lookup?acct=mishavelthuis").text)['id']

URL = f'{instance}/api/v1/accounts/{id}/statuses'
params = {
    'limit': 40
}

results = []

while True:
    r = requests.get(URL, params=params)
    toots = json.loads(r.text)

    if len(toots) == 0:
        break
    
    results.extend(toots)
    
    max_id = toots[-1]['id']
    params['max_id'] = max_id
    
df = pd.DataFrame(results)

current_date = date.today()
current_dir="/".join(inspect.getfile(inspect.currentframe()).split("/")[:-1])
file_name_save=f'{current_dir}/mydata_{current_date}.csv'
df.to_csv(file_name_save, index=False)

#+end_src

* Use/search data
- You don't have to load all data for every search.
#+begin_src python
df=pd.read_csv(file_name_save)

query="test"

# Search for words
for i in df['content']:
    if isinstance(i,str):
      if query in i:
          soup = BeautifulSoup(i, 'html.parser')
          readable_text = soup.get_text(separator=' ', strip=True)
          print(readable_text)
          print("----")
#+end_src