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ee34a1f278
* Fixed isort * Fixed issues * FIxed linters --------- Co-authored-by: James Maslek <jmaslek11@gmail.com>
344 lines
11 KiB
Python
344 lines
11 KiB
Python
""" Seeking Alpha Model """
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__docformat__ = "numpy"
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import logging
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import pandas as pd
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import requests
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.helper_funcs import lambda_long_number_format
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logger = logging.getLogger(__name__)
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@log_start_end(log=logger)
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def get_estimates_eps(ticker: str) -> pd.DataFrame:
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"""Takes the ticker, asks for seekingalphaID and gets eps estimates
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Parameters
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----------
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ticker: str
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ticker of company
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Returns
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-------
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pd.DataFrame
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eps estimates for the next 10yrs
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Examples
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--------
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>>> from openbb_terminal.sdk import openbb
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>>> openbb.stocks.fa.epsfc("AAPL")
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"""
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url = "https://seekingalpha.com/api/v3/symbol_data/estimates"
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querystring = {
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"estimates_data_items": "eps_normalized_actual,eps_normalized_consensus_low,eps_normalized_consensus_mean,"
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"eps_normalized_consensus_high,eps_normalized_num_of_estimates",
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"period_type": "annual",
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"relative_periods": "-3,-2,-1,0,1,2,3,4,5,6,7,8,9,10,11",
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}
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# add ticker_ids for the ticker
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seek_id = get_seekingalpha_id(ticker)
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querystring["ticker_ids"] = seek_id
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payload = ""
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Linux x86_64; rv:106.0) Gecko/20100101 Firefox/106.0",
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"Accept": "*/*",
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"Accept-Language": "de,en-US;q=0.7,en;q=0.3",
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"Accept-Encoding": "gzip, deflate, br",
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"Sec-Fetch-Dest": "empty",
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"Sec-Fetch-Mode": "cors",
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"Sec-Fetch-Site": "same-origin",
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"Connection": "keep-alive",
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}
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# semi random user agent -- disabled and static user agent because it might be the reason for 403
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# headers["User-Agent"] = get_user_agent()
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response = requests.request(
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"GET", url, data=payload, headers=headers, params=querystring
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)
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# init
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output = pd.DataFrame(
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columns=[
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"fiscalyear",
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"consensus_mean",
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"change %",
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"analysts",
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"actual",
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"consensus_low",
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"consensus_high",
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]
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)
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# if no estimations exist, response is empty "reviews" and "reviews"
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# {"revisions":{},"estimates":{}}
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try:
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seek_object = response.json()["estimates"][str(seek_id)]
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items = len(seek_object["eps_normalized_num_of_estimates"].keys())
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for i in range(0, items - 3):
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# python_dict
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eps_estimates = {}
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eps_estimates["fiscalyear"] = seek_object[
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"eps_normalized_num_of_estimates"
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][str(i)][0]["period"]["fiscalyear"]
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eps_estimates["analysts"] = seek_object["eps_normalized_num_of_estimates"][
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str(i)
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][0]["dataitemvalue"]
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try:
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eps_estimates["actual"] = seek_object["eps_normalized_actual"][str(i)][
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0
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]["dataitemvalue"]
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except Exception:
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eps_estimates["actual"] = 0
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eps_estimates["consensus_low"] = seek_object[
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"eps_normalized_consensus_low"
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][str(i)][0]["dataitemvalue"]
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eps_estimates["consensus_high"] = seek_object[
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"eps_normalized_consensus_high"
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][str(i)][0]["dataitemvalue"]
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eps_estimates["consensus_mean"] = seek_object[
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"eps_normalized_consensus_mean"
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][str(i)][0]["dataitemvalue"]
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try:
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this = float(eps_estimates["consensus_mean"])
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try:
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prev = float(
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seek_object["eps_normalized_actual"][str(i - 1)][0][
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"dataitemvalue"
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]
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)
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except Exception:
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prev = float(
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seek_object["eps_normalized_consensus_mean"][str(i - 1)][0][
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"dataitemvalue"
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]
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)
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percent = ((this / prev) - 1) * 100
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except Exception:
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percent = 0
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eps_estimates["change %"] = percent
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# format correction (before return, so calculation still works)
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eps_estimates["consensus_mean"] = lambda_long_number_format(
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float(eps_estimates["consensus_mean"])
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)
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eps_estimates["consensus_low"] = lambda_long_number_format(
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float(eps_estimates["consensus_low"])
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)
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eps_estimates["consensus_high"] = lambda_long_number_format(
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float(eps_estimates["consensus_high"])
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)
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eps_estimates["actual"] = lambda_long_number_format(
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float(eps_estimates["actual"])
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)
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# df append replacement
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new_row = pd.DataFrame(eps_estimates, index=[0])
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output = pd.concat([output, new_row])
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except Exception:
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return pd.DataFrame()
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return output
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@log_start_end(log=logger)
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def get_estimates_rev(ticker: str) -> pd.DataFrame:
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"""Takes the ticker, asks for seekingalphaID and gets rev estimates
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Parameters
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----------
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ticker: str
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ticker of company
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Returns
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-------
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pd.DataFrame
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rev estimates for the next 10yrs
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Examples
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--------
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>>> from openbb_terminal.sdk import openbb
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>>> openbb.stocks.fa.revfc("AAPL")
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"""
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url = "https://seekingalpha.com/api/v3/symbol_data/estimates"
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querystring = {
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"estimates_data_items": "revenue_actual,revenue_consensus_low,revenue_consensus_mean,"
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"revenue_consensus_high,revenue_num_of_estimates",
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"period_type": "annual",
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"relative_periods": "-3,-2,-1,0,1,2,3,4,5,6,7,8,9,10,11",
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}
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# add ticker_ids for the ticker
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seek_id = get_seekingalpha_id(ticker)
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querystring["ticker_ids"] = seek_id
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payload = ""
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Linux x86_64; rv:106.0) Gecko/20100101 Firefox/106.0",
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"Accept": "*/*",
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"Accept-Language": "de,en-US;q=0.7,en;q=0.3",
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"Accept-Encoding": "gzip, deflate, br",
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"Sec-Fetch-Dest": "empty",
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"Sec-Fetch-Mode": "cors",
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"Sec-Fetch-Site": "same-origin",
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"Connection": "keep-alive",
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"TE": "trailers",
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}
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# semi random user agent -- disabled and static user agent because it might be the reason for 403
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# headers["User-Agent"] = get_user_agent()
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response = requests.request(
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"GET", url, data=payload, headers=headers, params=querystring
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)
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# init
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# pd.empty should deliver true if no data-rows are added
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output = pd.DataFrame(
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columns=[
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"fiscalyear",
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"consensus_mean",
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"change %",
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"analysts",
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"actual",
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"consensus_low",
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"consensus_high",
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]
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)
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# if no estimations exist, response is empty "reviews" and "reviews"
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# {"revisions":{},"estimates":{}}
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try:
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seek_object = response.json()["estimates"][seek_id]
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items = len(seek_object["revenue_num_of_estimates"].keys())
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for i in range(0, items - 3):
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# python_dict
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revenue_estimates = {}
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revenue_estimates["fiscalyear"] = seek_object["revenue_num_of_estimates"][
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str(i)
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][0]["period"]["fiscalyear"]
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revenue_estimates["consensus_mean"] = seek_object["revenue_consensus_mean"][
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str(i)
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][0]["dataitemvalue"]
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revenue_estimates["analysts"] = seek_object["revenue_num_of_estimates"][
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str(i)
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][0]["dataitemvalue"]
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if i < 1:
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revenue_estimates["actual"] = seek_object["revenue_actual"][str(i)][0][
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"dataitemvalue"
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]
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else:
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revenue_estimates["actual"] = 0
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revenue_estimates["consensus_low"] = seek_object["revenue_consensus_low"][
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str(i)
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][0]["dataitemvalue"]
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revenue_estimates["consensus_high"] = seek_object["revenue_consensus_high"][
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str(i)
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][0]["dataitemvalue"]
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try:
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this = float(revenue_estimates["consensus_mean"])
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# if actual revenue is available, take it for the calc
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try:
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prev = float(
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seek_object["revenue_actual"][str(i - 1)][0]["dataitemvalue"]
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)
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except Exception:
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prev = float(
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seek_object["revenue_consensus_mean"][str(i - 1)][0][
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"dataitemvalue"
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]
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)
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percent = ((this / prev) - 1) * 100
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except Exception:
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percent = float(0)
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revenue_estimates["change %"] = percent
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# format correction (before return, so calculation still works)
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revenue_estimates["consensus_mean"] = lambda_long_number_format(
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float(revenue_estimates["consensus_mean"])
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)
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revenue_estimates["consensus_low"] = lambda_long_number_format(
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float(revenue_estimates["consensus_low"])
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)
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revenue_estimates["consensus_high"] = lambda_long_number_format(
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float(revenue_estimates["consensus_high"])
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)
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revenue_estimates["actual"] = lambda_long_number_format(
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float(revenue_estimates["actual"])
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)
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# df append replacement
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new_row = pd.DataFrame(revenue_estimates, index=[0])
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output = pd.concat([output, new_row])
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except Exception:
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return pd.DataFrame()
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return output
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@log_start_end(log=logger)
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def get_seekingalpha_id(ticker: str) -> str:
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"""Takes the ticker, asks for seekingalphaID and returns it
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Parameters
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----------
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ticker: str
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ticker of company
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Returns
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-------
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str:
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seekingalphaID - to be used for further API calls
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"""
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url = "https://seekingalpha.com/api/v3/searches"
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querystring = {
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"filter[type]": "symbols",
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"filter[list]": "all",
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"page[size]": "1",
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}
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querystring["filter[query]"] = ticker
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payload = ""
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headers = {
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"User-Agent": "Mozilla/5.0 (X11; Linux x86_64; rv:106.0) Gecko/20100101 Firefox/106.0",
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"Accept": "*/*",
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"Accept-Language": "de,en-US;q=0.7,en;q=0.3",
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"Accept-Encoding": "gzip, deflate, br",
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"Sec-Fetch-Dest": "empty",
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"Sec-Fetch-Mode": "cors",
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"Sec-Fetch-Site": "same-origin",
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"Referer": "https://seekingalpha.com/",
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"Connection": "keep-alive",
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# "TE": "trailers",
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}
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response = requests.request(
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"GET", url, data=payload, headers=headers, params=querystring
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)
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try:
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seekingalphaID = str(response.json()["symbols"][0]["id"])
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except Exception:
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# for some reason no mapping possible
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seekingalphaID = "0"
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return seekingalphaID
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