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import requests | ||
import pandas as pd | ||
import time | ||
import ujson | ||
from datetime import datetime | ||
from tqdm import tqdm | ||
from collections import defaultdict | ||
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start_date = '2015-01-01' | ||
end_date = datetime.today().strftime("%Y-%m-%d") | ||
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# API endpoint for spending by award | ||
url = "https://api.usaspending.gov/api/v2/search/spending_by_award/" | ||
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# Headers | ||
headers = { | ||
"Content-Type": "application/json", | ||
} | ||
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def save_json(symbol, data): | ||
with open(f"json/government-contract/{symbol}.json", 'w') as file: | ||
ujson.dump(data, file) | ||
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# Define a function to remove duplicates based on a key | ||
def remove_duplicates(data, key): | ||
seen = set() | ||
new_data = [] | ||
for item in data: | ||
if item[key] not in seen: | ||
seen.add(item[key]) | ||
new_data.append(item) | ||
return new_data | ||
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def sum_contract(symbol, data): | ||
aggregated_data = {} | ||
for entry in data: | ||
year = entry['date'][:4] | ||
expenses = entry.get('amount') # Retrieve expenses or default to None | ||
if expenses is not None: # Check if expenses is not None | ||
if year not in aggregated_data: | ||
aggregated_data[year] = { | ||
'year': year, | ||
'amount': 0, | ||
'numOfContracts': 0, | ||
} | ||
aggregated_data[year]['amount'] += int(expenses) | ||
aggregated_data[year]['numOfContracts'] += 1 | ||
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data = list(aggregated_data.values()) | ||
save_json(symbol, data) | ||
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def get_data(symbol, name): | ||
res = [] | ||
for page in tqdm(range(1,2000)): | ||
try: | ||
data = { | ||
"filters": { | ||
"recipient_search_text": [name], | ||
"time_period": [{"start_date": start_date, "end_date": end_date}], | ||
"award_type_codes": ["A", "B", "C", "D"], # Contract award types | ||
}, | ||
"fields": ["Award ID", "Recipient Name", "Award Amount", "Last Modified Date"], | ||
"page": page, | ||
"limit": 100 # Adjust as needed | ||
} | ||
response = requests.post(url, json=data, headers=headers) | ||
response_data = (response.json())['results'] | ||
res += [{'id': item['Award ID'], 'amount': item['Award Amount'], 'date': item['Last Modified Date']} for item in response_data] | ||
time.sleep(1) | ||
except Exception as e: | ||
break | ||
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sorted_res = sorted(res, key=lambda x: datetime.strptime(x['date'], '%Y-%m-%d')) | ||
sorted_res = remove_duplicates(sorted_res, 'id') | ||
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if len(sorted_res) > 0: | ||
sum_contract(symbol, sorted_res) | ||
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try: | ||
company_data = [{'symbol': 'J', 'name': 'Jacobs Engineering'},{'symbol': 'CRWD', 'name': 'CrowdStrike'},{'symbol': 'FLR', 'name': 'Fluor'},{'symbol': 'GD', 'name': 'General Dynamics'},{'symbol': 'NOC', 'name': 'Northrop Grumman'},{'symbol': 'RTX', 'name': 'Raytheon Technologies'},{'symbol': 'LHX', 'name': 'L3Harris Technologies'},{'symbol': 'CAT', 'name': 'Caterpillar'},{'symbol': 'JNJ', 'name': 'Johnson & Johnson'},{'symbol': 'CVX', 'name': 'Chevron'},{'symbol': 'XOM', 'name': 'Exxon Mobil'},{'symbol': 'UNH', 'name': 'UnitedHealth'},{'symbol': 'PFE', 'name': 'Pfizer'},{'symbol': 'BAH', 'name': 'Booz Allen Hamilton'},{'symbol': 'NEE', 'name': 'NextEra'},{'symbol': 'LDOS', 'name': 'Leidos'},{'symbol': 'PLTR', 'name': 'Palantir'},{'symbol': 'HII', 'name': 'Huntington Ingalls'},{'symbol': 'CACI', 'name': 'CACI International'},{'symbol': 'SAIC', 'name': 'Science Applications'},{'symbol': 'BA', 'name': 'Boeing'},{'symbol': 'LMT', 'name': 'Lockheed Martin'}] | ||
for item in company_data: | ||
symbol = item['symbol'] | ||
name = item['name'] | ||
get_data(symbol, name) | ||
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except Exception as e: | ||
print(e) | ||
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