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"""Main Indicators"""
from datetime import datetime, timedelta
from typing import Dict, List, Literal, Union
from aiohttp_client_cache import SQLiteBackend
from aiohttp_client_cache.session import CachedSession
from numpy import arange
from openbb_core.app.utils import get_user_cache_directory
from openbb_core.provider.utils.helpers import amake_request
from openbb_econdb.utils.helpers import COUNTRY_MAP, THREE_LETTER_ISO_MAP
from pandas import Categorical, DataFrame, Series, concat, to_datetime
trends_transform_labels_dict = {
1: "Change from previous period.",
2: "Change from one year ago.",
3: "Level",
9: "Level (USD)",
}
trends_freq_dict = {
"annual": "Y",
"quarter": "Q",
"month": "M",
}
trends_transform_dict = {
"tpop": 1,
"toya": 2,
"level": 3,
"tusd": 9,
None: 3,
}
main_indicators_order = [
"RGDP",
"RPRC",
"RPUC",
"RGFCF",
"REXP",
"RIMP",
"GDP",
"PRC",
"PUC",
"GFCF",
"EXP",
"IMP",
"CPI",
"PPI",
"CORE",
"URATE",
"EMP",
"ACPOP",
"RETA",
"CONF",
"IP",
"CP",
"GBAL",
"GREV",
"GSPE",
"GDEBT",
"CA",
"TB",
"NIIP",
"IIPA",
"IIPL",
"Y10YD",
"M3YD",
"HOU",
"OILPROD",
"POP",
]
async def fetch_data(url, use_cache: bool = True):
"""Fetch the data with or without the cached session object."""
response: Union[dict, List[dict]] = {}
if use_cache is True:
cache_dir = f"{get_user_cache_directory()}/http/econdb_main_indicators"
async with CachedSession(
cache=SQLiteBackend(cache_dir, expire_after=3600 * 24)
) as session:
try:
response = await amake_request(url, session=session)
finally:
await session.close()
else:
response = await amake_request(url)
return response
async def get_main_indicators( # pylint: disable=R0913,R0914,R0915
country: str = "US",
start_date: str = (datetime.now() - timedelta(weeks=52 * 3)).strftime("%Y-%m-%d"),
end_date: str = datetime.now().strftime("%Y-%m-%d"),
frequency: Literal["annual", "quarter", "month"] = "quarter",
transform: Literal["tpop", "toya", "level", "tusd", None] = "toya",
use_cache: bool = True,
) -> List[Dict]:
"""Get the main indicators for a given country."""
freq = trends_freq_dict.get(frequency)
transform = trends_transform_dict.get(transform) # type: ignore
if len(country) == 3:
country = THREE_LETTER_ISO_MAP.get(country.upper())
if not country:
raise ValueError(f"Error: Invalid country code -> {country}")
if country in COUNTRY_MAP:
country = COUNTRY_MAP.get(country)
if len(country) != 2:
raise ValueError(
f"Error: Please supply a 2-Letter ISO Country Code -> {country}"
)
if country not in COUNTRY_MAP.values():
raise ValueError(f"Error: Invalid country code -> {country}")
parents_url = (
"https://www.econdb.com/trends/country_forecast/"
+ f"?country={country}&freq={freq}&transform={transform}"
+ f"&dateStart={start_date}&dateEnd={end_date}"
)
r = await fetch_data(parents_url, use_cache)
row_names = r.get("row_names")
row_symbols = []
row_is_parent = []
row_symbols = [d["code"] for d in row_names]
row_is_parent = [d["is_parent"] for d in row_names]
parent_map = {d["code"]: d["is_parent"] for d in row_names}
units_col = r.get("units_col")
metadata = r.get("footnote")
row_names = r.get("row_names")
row_name_map = {d["code"]: d["verbose"].title() for d in row_names}
row_units_dict = dict(zip(row_symbols, units_col))
units_df = concat([Series(units_col), Series(row_is_parent)], axis=1)
units_df.columns = ["units", "is_parent"]
df = DataFrame(r["data"]).set_index("indicator")
df = df.pivot(columns="obs_time", values="obs_value").filter(
items=row_symbols, axis=0
)
df["units"] = df.index.map(row_units_dict.get)
df["is_parent"] = df.index.map(parent_map.get)
df = df.set_index("is_parent", append=True)
async def get_children( # pylint: disable=R0913
parent, country, freq, transform, start_date, end_date, use_cache
) -> DataFrame:
"""Get the child elements for the main indicator symbols."""
children_url = (
"https://www.econdb.com/trends/get_topic_children/"
+ f"?country={country}&agency=3&freq={freq}&transform={transform}"
+ f"&parent_id={parent}&dateStart={start_date}&dateEnd={end_date}"
)
child_r = await fetch_data(children_url, use_cache)
row_names = child_r.get("row_names")
row_symbols = []
row_symbols = [d["code"] for d in row_names]
units_col = child_r.get("units_col")
metadata.extend(child_r.get("footnote"))
row_names = child_r.get("row_names")
row_name_map.update({d["code"]: d["verbose"].title() for d in row_names})
row_units_dict = dict(zip(row_symbols, units_col))
child_df = DataFrame(child_r["data"]).set_index("indicator")
child_df = child_df.pivot(columns="obs_time", values="obs_value").filter(
items=row_symbols, axis=0
)
child_df["units"] = child_df.index.map(row_units_dict.get)
# Set 'units' to 'Index' when the index is 'CONF'
if "CONF" in child_df.index and child_df.loc["CONF", "units"] == "..":
child_df.loc["CONF", "units"] = "Index"
child_df["is_parent"] = parent
child_df = child_df.reset_index()
child_df["name"] = child_df["indicator"].map(row_name_map)
return child_df
new_df = df.reset_index()
has_children = new_df[
new_df["is_parent"] == True # noqa pylint: disable=C0121
].indicator.to_list()
async def append_children( # pylint: disable=R0913
df, parent, country, freq, transform, start_date, end_date, use_cache
):
"""Get the child element and insert it below the parent row."""
temp = DataFrame()
try:
children = await get_children(
parent, country, freq, transform, start_date, end_date, use_cache
)
except Exception as _: # pylint: disable=W0718
return df
idx = df[df["indicator"] == parent].index[0]
df1 = df[df.index <= idx]
df2 = df[df.index > idx]
temp = concat([df1, children, df2])
return temp
# Get the child elements for each parent.
for parent in has_children:
new_df = await append_children(
new_df, parent, country, freq, transform, start_date, end_date, use_cache
)
# Cast the shape, specify the order and flatten for output.
new_df["name"] = new_df["indicator"].map(row_name_map)
new_df.set_index(["indicator", "is_parent", "name", "units"], inplace=True)
new_df.columns = new_df.columns
new_df.columns = [to_datetime(d).strftime("%Y-%m-%d") for d in new_df.columns]
for col in new_df.columns:
new_df[col] = new_df[col].astype(str)
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