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Adds old data sourcing to new clr script (#9514)
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gdixon authored Sep 22, 2021
1 parent 0f1f13c commit 4705b1d
Showing 1 changed file with 150 additions and 3 deletions.
153 changes: 150 additions & 3 deletions app/grants/clr.py
Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,147 @@
from django.utils import timezone

import numpy as np
from grants.clr_data_src import fetch_grants, fetch_summed_contributions
from grants.clr_data_src import fetch_contributions, fetch_grants


def populate_data_for_clr(grants, contributions, clr_round):
'''
Populate Data needed to calculate CLR
Args:
grants : grants list
contributions : contributions list for those grants
clr_round : GrantCLR
Returns:
contrib_data_list: {
'id': grant_id,
'contributions': summed_contributions
}
'''

contrib_data_list = []

if not clr_round:
print('Error: populate_data_for_clr - missing clr_round')
return contrib_data_list

clr_start_date = clr_round.start_date
clr_end_date = clr_round.end_date

mechanism="profile"

# 3-4s to get all the contributions
_contributions = list(contributions.filter(created_on__gte=clr_start_date, created_on__lte=clr_end_date).prefetch_related('profile_for_clr', 'subscription'))
_contributions_by_id = {}
for ele in _contributions:
key = ele.normalized_data.get('id')
if key not in _contributions_by_id.keys():
_contributions_by_id[key] = []
_contributions_by_id[key].append(ele)

# set up data to load contributions for each grant
for grant in grants:
grant_id = grant.defer_clr_to.pk if grant.defer_clr_to else grant.id

# contributions
contribs = _contributions_by_id.get(grant.id, [])

# create arrays
contributing_profile_ids = []
contributions_by_id = {}
for c in contribs:
prof = c.profile_for_clr
if prof:
key = prof.id
if key not in contributions_by_id.keys():
contributions_by_id[key] = []
contributions_by_id[key].append(c)
contributing_profile_ids.append((prof.id, prof.trust_bonus))

contributing_profile_ids = list(set(contributing_profile_ids))

summed_contributions = []

# contributions
if len(contributing_profile_ids) > 0:
for profile_id, trust_bonus in contributing_profile_ids:
sum_of_each_profiles_contributions = sum(ele.normalized_data.get('amount_per_period_usdt') for ele in contributions_by_id[profile_id]) * float(clr_round.contribution_multiplier)

summed_contributions.append({
'id': str(profile_id),
'sum_of_each_profiles_contributions': sum_of_each_profiles_contributions,
'profile_trust_bonus': trust_bonus
})

contrib_data_list.append({
'id': grant_id,
'contributions': summed_contributions
})

return contrib_data_list


def translate_data(grants_data):
'''
translates django grant data structure to a list of lists
args:
django grant data structure
{
'id': (string) ,
'contibutions' : [
{
contributor_profile (str) : summed_contributions
}
]
}
returns:
list of lists of grant data
[[grant_id (str), user_id (str), contribution_amount (float)]]
dictionary of profile_ids and trust scores
{user_id (str): trust_score (float)}
'''
trust_dict = {}
grants_list = []
for g in grants_data:
grant_id = g.get('id')
for c in g.get('contributions'):
profile_id = c.get('id')
trust_bonus = c.get('profile_trust_bonus')
if profile_id:
val = [grant_id] + [c.get('id')] + [c.get('sum_of_each_profiles_contributions')]
grants_list.append(val)
trust_dict[profile_id] = trust_bonus

return grants_list, trust_dict


def aggregate_contributions(grant_contributions):
'''
aggregates contributions by contributor, and calculates total contributions by unique pairs
args:
list of lists of grant data
[[grant_id (str), user_id (str), verification_status (str), trust_bonus (float), contribution_amount (float)]]
returns:
aggregated contributions by pair nested dict
{
grant_id (str): {
user_id (str): aggregated_amount (float)
}
}
'''
contrib_dict = {}
for proj, user, amount in grant_contributions:
if proj not in contrib_dict:
contrib_dict[proj] = {}
contrib_dict[proj][user] = contrib_dict[proj].get(user, 0) + amount

return contrib_dict


def get_totals_by_pair(contrib_dict):
Expand Down Expand Up @@ -235,8 +375,15 @@ def predict_clr(save_to_db=False, from_date=None, clr_round=None, network='mainn
print(f"- starting fetch_grants at {round(time.time(),1)}")
grants = fetch_grants(clr_round, network)

print(f"- starting get data and sum at {round(time.time(),1)}")
curr_agg, trust_dict = fetch_summed_contributions(grants, clr_round, network)
print(f"- starting fetch_contributions at {round(time.time(),1)}")
contributions = fetch_contributions(clr_round, network)

print(f"- starting sum (of {contributions.count()} contributions) at {round(time.time(),1)}")
grant_contributions_curr = populate_data_for_clr(grants, contributions, clr_round)
curr_round, trust_dict = translate_data(grant_contributions_curr)

# this aggregates the data into the expected format
curr_agg = aggregate_contributions(curr_round)

if len(curr_agg) == 0:
print(f'- done - no Contributions for CLR {clr_round.round_num}. Exiting')
Expand Down

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