130 lines
3.9 KiB
Python
130 lines
3.9 KiB
Python
# convert demographic-manager data to google sheets data
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# to be interpreted by gas-demoman
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# for information on gas-demoman, see
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# https://git.beepboop.systems/stupidcomputer/gas-demoman
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# and https://github.com/stupidcomputer/gas-demoman
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# because the majority of the code that is in this repo
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# is crap, we'll just be reimplementing the existing
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# datastructures
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import json
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from typing import Any
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def get_json_for_filename(filename: str) -> Any:
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with open(filename, "r") as file:
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return json.loads(file.read())
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def replace_manifest_filename_references(manifest: dict) -> Any:
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for site in manifest["sites"]:
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to_replace = site["usedrecord"]
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site["usedrecord"] = get_json_for_filename("data/" + site["usedrecord"])["payload"]
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return manifest
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json_data = get_json_for_filename("data/manifest.json")
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json_data = replace_manifest_filename_references(json_data)
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intern_data = get_json_for_filename("data/staffrecord.json")["payload"]
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def translate_shortcodes_to_human_readable(shortcode: Any) -> str:
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mapping = {
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"a": "Adult",
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"c": "Child",
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"wh": "White",
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"as": "Asian",
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"f": "Female",
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"m": "Male",
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"1+": "More than one race",
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"nh": "Not Hispanic",
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"h": "Hispanic",
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"b/aa": "Black/African American",
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"unk": "Unknown",
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"u/o": "Unknown/Other",
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"ai/an": "American Indian/Alaskan Native",
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"nh/opi": "Native Hawaiian/Other Pacific Islander",
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"i": "Intern",
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"None": "Unknown",
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}
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return mapping[str(shortcode)]
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def generate_intern_data_table(intern_data: dict) -> Any:
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output = [["First Name", "Last Name", "Gender", "Ethnicity", "Race"]]
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for intern in intern_data:
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result = []
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name = intern["name"].split(' ')
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result.append(name[0])
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result.append(name[1])
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result.append(translate_shortcodes_to_human_readable(intern["innerpayload"]["gender"]))
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result.append(translate_shortcodes_to_human_readable(intern["innerpayload"]["ethnicity"]))
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result.append(translate_shortcodes_to_human_readable(intern["innerpayload"]["race"]))
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output.append(result)
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return output
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def generate_site_name_data_table(manifest: dict) -> Any:
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output = [["Site name", "Date", "Those Present", "Data leads", "On-site lead(s)", "Who collected?"]]
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for site in manifest["sites"]:
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result = []
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result.append(site["name"])
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result.append("{} {}".format(
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site["date"],
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site["time"],
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))
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result.append(', '.join(site["present"]))
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result.append(', '.join(site["commleads"]))
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result.append(', '.join(site["onsiteleads"]))
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result.append(site["records"][0]["submitter"])
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output.append(result)
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return output
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def generate_demographic_data_table(manifest: dict) -> Any:
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output = [["Site name", "Count", "Age", "Gender", "Ethnicity", "Race"]]
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for site in manifest["sites"]:
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for datum in site["usedrecord"]:
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fields = [
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"age",
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"gender",
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"ethnicity",
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"race"
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]
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def mapper(x) -> Any:
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return translate_shortcodes_to_human_readable(datum[x])
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fields = map(mapper, fields)
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final = [site["name"], "1", *fields]
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output.append(final)
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return output
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def convert_table_to_tsv(table: list[list[str]]) -> str:
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output = ""
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for row in table:
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output += "\t".join(row)
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output += "\n"
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return output
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def write_file(filename: str, data: str) -> None:
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with open(filename, "w") as file:
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file.write(data)
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write_file("demographic_data.tsv", convert_table_to_tsv(
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generate_demographic_data_table(json_data)
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))
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write_file("sites.tsv", convert_table_to_tsv(
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generate_site_name_data_table(json_data)
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))
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write_file("interns.tsv", convert_table_to_tsv(
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generate_intern_data_table(intern_data)
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)) |