This notebook loops through the list of functions that were extracted from the RecordSearch interface and saves basic details of the agencies responsible for each function. To keep down the file size and avoid too much duplication it doesn't include the full range of relationships that an agency might have. If you want the full agency data, use this notebook to harvest agencies associated with an indivividual function or hierarchy.
The JSON data file created has the following structure:
[
{
'term': FUNCTION NAME
'agencies': [
'agency_id': AGENCY IDENTIFIER,
'title': AGENCY NAME,
'dates': {
'date_str': AGENCY LIFE DATES AS A STRING,
'start_date': AGENCY START DATE (YYYY-MM-DD),
'end_date': AGENCY END DATE (YYYY-MM-DD),
},
'agency_status': TYPE/LEVEL OF AGENCY,
'location': AGENCY LOCATION,
'function_start_date': DATE AGENCY STARTED BEING RESPONSIBLE FOR THIS FUNCTION (YYYY-MM-DD),
'function_end_date': DATE AGENCY STOPPED BEING RESPONSIBLE FOR THIS FUNCTION (YYYY-MM-DD),
]
}
]
import json
import time
from IPython.display import FileLink, clear_output, display
from recordsearch_data_scraper.scrapers import RSAgencySearch
from tinydb import Query, TinyDB
from tqdm.auto import tqdm
def harvest_agencies(function):
agencies = []
search = RSAgencySearch(function=function, record_detail="full")
with tqdm(total=search.total_results) as pbar:
more = True
while more:
data = search.get_results()
if data["results"]:
agencies += data["results"]
pbar.update(len(data["results"]))
time.sleep(0.5)
else:
more = False
return agencies
def get_children(function):
"""
Gets child terms of a given function.
"""
f_list = []
if "narrower" in function:
for subf in function["narrower"]:
f_list.append(subf["term"])
f_list += get_children(subf)
return f_list
def load_functions():
"""
Loads a pre-harvested JSON file containing functions data.
Returns a flat list of functions.
"""
functions_list = []
with open("data/functions.json", "r") as json_file:
functions = json.load(json_file)
for function in functions:
functions_list.append(function["term"])
functions_list += get_children(function)
# Get rid of duplicates
functions_list = set(functions_list)
# Sort terms
functions_list = sorted(functions_list)
return functions_list
def get_function_dates(function, agency):
"""
Get the dates an agency was responsible for a given function.
"""
dates = {}
# Loop through the functions associated with an agency
for f in agency["functions"]:
# Find the current function
if f["identifier"].lower() == function:
# Get the dates this agency was responsible for the current function
dates["function_start_date"] = f["start_date"]
dates["function_end_date"] = f["end_date"]
break
return dates
def get_all_agencies():
"""
Sends function terms off to the harvester to get related agencies.
"""
clear_output()
Record = Query()
# Get a list of functions
functions = load_functions()
db = TinyDB("data/db_agencies_by_function")
# Loop through the list of functions
for function in functions:
clear_output()
print('\nHarvesting "{}"'.format(function))
# Fire up the harvester for this function
results = harvest_agencies(function)
agencies = []
# Create a subset of the agency data to limit the filesize
for a in results:
# Keep the fields we want
agency = {
k: a[k]
for k in [
"identifier",
"title",
"start_date",
"end_date",
"agency_status",
"location",
]
}
# Add extra fields to show when the agency was responsible for this function
agency.update(get_function_dates(function, a))
agencies.append(agency)
db.upsert({"term": function, "agencies": agencies}, Record.term == function)
get_all_agencies()
def save_json():
db = TinyDB("data/db_agencies_by_function")
functions = db.all()
filename = "data/agencies_by_function.json"
with open(filename, "w") as json_file:
json.dump(functions, json_file, indent=4)
display(FileLink(filename))
save_json()
Created by Tim Sherratt as part of the GLAM Workbench.