cargo run -p twitar
| # | Endpoints | Limit (app) | Limit (user) | Plan |
|---|---|---|---|---|
| 1 | Delete Retweet | (a). 50 requests per 15 min (per user) (b). 300 requests per 3-hour window(per user, per app) (c). 1000 successful requests/24hrs |
* | |
| 2 | Delete Like | (a). 1000 successful requests/24hrs/window per user (this limit is shared by both like a tweet and delete like endpoints) | ||
| 3 | User Tweet Timeline | (a). 1500 requests per 15 minutes (per app) | (a). 900 requests/15 minutes/app | |
| 4 | Tweet counts | 300 requests/15m/app | ||
| 5 | Retweets lookup | 75r/15m/app | 75r/15m/app | |
| 6 | Undo a retweet | 50r/15m/app |
use best_sum for best approach towards deletion
Scenario: Assuming 2 users are selected
- The Goal is to delete 960 reqs/day | limit - 1000reqs/day
- 240 reqs/3hrs | limit - 300reqs/3hrs
- 80 reqs/15mins i.e 40reqs/user | limit - 50reqs/15mins
- i.e. (960/4)/3
Scenario: Assuming 1 user is selected
- 40r/15mins | 50/15mins
- Run 7 times in 3hrs - (40*7 = 280r/3hrs) | 300/3hrs
- Run 3 times a day to delete (900 reqs/day) | 1000/day
def basic_del(num_of_users):
times_to_run = []
if num_of_users = 2:
times_to_run = [0min, 15mins, 30mins]
else:
times_to_run = [0min, 15mins, 30mins, 45mins, 60mins, 75mins, 90mins]
for time in times_to_run:
run_at(time) --> 40 * num_of_users
App has a maximum of 300 deletes/3hrs and 1000 deletes/24hrs
t1 - 1:00hrs
basic_del() - 240reqs | total 240
t2 - 4:00hrs (rather than 3hrs, add 1 extra hr from the expected limit)
basic_del() - 240reqs | total 480
t3 - 8:00hrs
basic_del() - 240reqs | total 720
t4 - 12:00hrs
basic_del() - 70reqs | total 960
basic_del()