jerry/OpenBB
1
0
Fork 0
mirror of https://github.com/OpenBB-finance/OpenBB.git synced 2026-10-27 04:31:13 +00:00
Code Issues Packages Projects Releases Wiki Activity

Refactor Economy menu (#652)

Browse Source 
* Allow to quit when DEFAULT_CONTEXT selected

* terminal imports inside context selection

* rework economy/events command

* Refactor fear greed CNN command

* refactor WSJ in economy

* import fred

* refactor fred commands in economy

* refactor disc commands into economy

* refactor disc commands into economy 2

* fix fred test

* fix fred test

* av pylint

* update quit from direct context

* fix av lint

* Add industry simply wallst to economy

* improve events display

* improv after review

* add mypy types

* tabulate raw series

* remove simply wallst
This commit is contained in:
DidierRLopes
2021-08-08 21:36:24 +01:00
committed by GitHub
parent 5f4be25ed2
commit ec07686aed
23 changed files with 1433 additions and 1027 deletions
Download Patch File Download Diff File Expand all files Collapse all files

0
exports/economy/.gitkeep vendored Normal file
View File

22
gamestonk_terminal/economy/alphavantage_model.py Normal file
View File

@@ -0,0 +1,22 @@
""" Alpha Vantage Model """
__docformat__ = "numpy"
import pandas as pd
from alpha_vantage.sectorperformance import SectorPerformances
from gamestonk_terminal import config_terminal as cfg
def get_sector_data() -> pd.DataFrame:
"""Get real-time performance sector data
Returns
----------
df_sectors : pd.Dataframe
Real-time performance data
"""
sector_perf = SectorPerformances(
key=cfg.API_KEY_ALPHAVANTAGE, output_format="pandas"
)
# pylint: disable=unbalanced-tuple-unpacking
df_sectors, _ = sector_perf.get_sector()
return df_sectors

44
gamestonk_terminal/economy/alphavantage_view.py Normal file
View File

@@ -0,0 +1,44 @@
""" Alpha Vantage View """
__docformat__ = "numpy"
import os
import matplotlib.pyplot as plt
from gamestonk_terminal.helper_funcs import export_data
from gamestonk_terminal.economy import alphavantage_model
from gamestonk_terminal import feature_flags as gtff
def realtime_performance_sector(raw: bool, export: str):
"""Display Real-Time Performance sector. [Source: AlphaVantage]
Parameters
----------
raw : bool
Output only raw data
export : str
Export dataframe data to csv,json,xlsx file
"""
df_sectors = alphavantage_model.get_sector_data()
# pylint: disable=invalid-sequence-index
df_rtp = df_sectors["Rank A: Real-Time Performance"]
if raw:
print(df_rtp.to_string())
else:
df_rtp.plot(kind="bar")
plt.title("Real Time Performance (%) per Sector")
plt.tight_layout()
plt.grid()
if gtff.USE_ION:
plt.ion()
plt.show()
print("")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"rtps",
df_sectors,
)

54
gamestonk_terminal/economy/cnn_model.py Normal file
View File

@@ -0,0 +1,54 @@
""" CNN Model """
__docformat__ = "numpy"
from typing import Tuple
from fear_greed_index.CNNFearAndGreedIndex import CNNFearAndGreedIndex
from pandas.plotting import register_matplotlib_converters
import matplotlib.pyplot as plt
register_matplotlib_converters()
def get_feargreed_report(indicator: str, fig: plt.figure) -> Tuple[str, plt.figure]:
"""Display CNN Fear And Greed Index.
Parameters
----------
indicator : str
CNN Fear And Greed indicator or index. From Junk Bond Demand, Market Volatility,
Put and Call Options, Market Momentum Stock Price Strength, Stock Price Breadth,
Safe Heaven Demand, and Index.
plt.figure
matplotlib figure initialized if indicator 'all' is selected
Returns
----------
str
String output with respect to indicator chosen
plt.figure
matplotlib figure with indicator
"""
cnn_fg = CNNFearAndGreedIndex()
if indicator:
if indicator == "index":
return cnn_fg.index_summary, cnn_fg.index_chart
d_indicator_match = {
"jbd": "Junk Bond Demand",
"mv": "Market Volatility",
"pco": "Put and Call Options",
"mm": "Market Momentum",
"sps": "Stock Price Strength",
"spb": "Stock Price Breadth",
"shd": "Safe Heaven Demand",
}
indicator_name = d_indicator_match[indicator]
for ind in cnn_fg.all_indicators:
if indicator_name == ind.type_indicator:
return ind.get_report(), ind.chart
return "", plt.figure()
return cnn_fg.get_complete_report(), cnn_fg.plot_all_charts(fig)

98
gamestonk_terminal/economy/cnn_view.py
View File

@@ -1,105 +1,37 @@
""" Fred View """
""" CNN View """
__docformat__ = "numpy"
import argparse
from typing import List
from fear_greed_index.CNNFearAndGreedIndex import CNNFearAndGreedIndex
from pandas.plotting import register_matplotlib_converters
import matplotlib.pyplot as plt
from gamestonk_terminal.helper_funcs import (
parse_known_args_and_warn,
plot_autoscale,
)
from gamestonk_terminal.config_plot import PLOT_DPI
from gamestonk_terminal import feature_flags as gtff
from gamestonk_terminal.economy import cnn_model
register_matplotlib_converters()
def fear_and_greed_index(other_args: List[str]):
def fear_and_greed_index(indicator: str):
"""Display CNN Fear And Greed Index.
Parameters
----------
other_args : List[str]
argparse other args
indicator : str
CNN Fear And Greed indicator or index. From Junk Bond Demand, Market Volatility,
Put and Call Options, Market Momentum Stock Price Strength, Stock Price Breadth,
Safe Heaven Demand, and Index.
"""
fig = plt.figure(figsize=plot_autoscale(), dpi=PLOT_DPI)
parser = argparse.ArgumentParser(
add_help=False,
prog="feargreed",
description="""
Display CNN Fear And Greed Index from https://money.cnn.com/data/fear-and-greed/.
""",
)
report, im = cnn_model.get_feargreed_report(indicator, fig)
parser.add_argument(
"-i",
"--indicator",
dest="indicator",
required=False,
type=str,
choices=["jbd", "mv", "pco", "mm", "sps", "spb", "shd", "index"],
help="""
CNN Fear And Greed indicator or index. From Junk Bond Demand, Market Volatility,
Put and Call Options, Market Momentum Stock Price Strength, Stock Price Breadth,
Safe Heaven Demand, and Index.
""",
)
print(report)
try:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-i")
if indicator:
plt.imshow(im)
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
cnn_fg = CNNFearAndGreedIndex()
fig = plt.figure(figsize=plot_autoscale(), dpi=PLOT_DPI)
if ns_parser.indicator:
if ns_parser.indicator == "index":
print(cnn_fg.index_summary)
im = cnn_fg.index_chart
plt.imshow(im)
else:
d_indicator_match = {
"jbd": "Junk Bond Demand",
"mv": "Market Volatility",
"pco": "Put and Call Options",
"mm": "Market Momentum",
"sps": "Stock Price Strength",
"spb": "Stock Price Breadth",
"shd": "Safe Heaven Demand",
}
indicator_name = d_indicator_match[ns_parser.indicator]
for indicator in cnn_fg.all_indicators:
if indicator_name == indicator.type_indicator:
print(indicator.get_report())
im = indicator.chart
plt.imshow(im)
else:
# print Fear and Greed complete report
print(cnn_fg.get_complete_report())
# plot Fear and Greed charts
cnn_fg.plot_all_charts(fig)
if gtff.USE_ION:
plt.ion()
plt.show()
print("")
except SystemExit:
print("")
except Exception as e:
print(e, "\n")
return
if gtff.USE_ION:
plt.ion()
plt.show()

747
gamestonk_terminal/economy/economy_controller.py
View File

@@ -6,12 +6,21 @@ import os
from typing import List
from prompt_toolkit.completion import NestedCompleter
from gamestonk_terminal import feature_flags as gtff
from gamestonk_terminal.helper_funcs import get_flair
from gamestonk_terminal.helper_funcs import (
get_flair,
parse_known_args_and_warn,
check_positive,
valid_date,
)
from gamestonk_terminal.menu import session
from gamestonk_terminal.economy import fred_view
from gamestonk_terminal.economy import finnhub_view
from gamestonk_terminal.economy import cnn_view
from gamestonk_terminal.economy import wsj_view
from gamestonk_terminal.economy import (
fred_view,
finnhub_view,
cnn_view,
wsj_view,
finviz_view,
alphavantage_view,
)
from gamestonk_terminal.economy.report import report_controller
# pylint: disable=R1710
@@ -20,7 +29,24 @@ from gamestonk_terminal.economy.report import report_controller
class EconomyController:
"""Economy Controller"""
# Command choices
d_GROUPS = {
"sector": "Sector",
"industry": "Industry",
"basic materials": "Industry (Basic Materials)",
"communication services": "Industry (Communication Services)",
"consumer cyclical": "Industry (Consumer Cyclical)",
"consumer defensive": "Industry (Consumer Defensive)",
"energy": "Industry (Energy)",
"financial": "Industry (Financial)",
"healthcare": "Industry (Healthcare)",
"industrials": "Industry (Industrials)",
"real Estate": "Industry (Real Estate)",
"technology": "Industry (Technology)",
"utilities": "Industry (Utilities)",
"country": "Country (U.S. listed stocks only)",
"capitalization": "Capitalization",
}
CHOICES = [
"cls",
"?",
@@ -30,20 +56,8 @@ class EconomyController:
]
CHOICES_COMMANDS = [
"events",
"fred",
"vixcls",
"gdp",
"unrate",
"dgs1",
"dgs5",
"dgs10",
"dgs30",
"mortgage30us",
"fedfunds",
"aaa",
"dexcaus",
"feargreed",
"events",
"overview",
"indices",
"futures",
@@ -51,6 +65,14 @@ class EconomyController:
"glbonds",
"futures",
"currencies",
"search",
"series",
"valuation",
"performance",
"spectrum",
"map",
"rtps",
"industry",
]
CHOICES_MENUS = [
@@ -71,45 +93,41 @@ class EconomyController:
@staticmethod
def print_help():
"""Print help"""
print(
"https://github.com/GamestonkTerminal/GamestonkTerminal/tree/main/gamestonk_terminal/economy"
)
print("")
print(">> ECONOMY <<")
print("")
print("What do you want to do?")
print(" cls clear screen")
print(" ?/help show this menu again")
print(" q quit this menu, and shows back to main menu")
print(" quit quit to abandon program")
print(" ")
print(" feargreed CNN Fear and Greed Index")
print(" events economic impact events [Finnhub]")
print(
" fred display customized FRED data from https://fred.stlouisfed.org"
)
print(" vixcls Volatility Index")
print(" gdp Gross Domestic Product")
print(" unrate Unemployment Rate")
print(" dgs1 1-year Treasury Constant Maturity Rate")
print(" dgs5 5-year Treasury Constant Maturity Rate")
print(" dgs10 10-year Treasury Constant Maturity Rate")
print(" dgs30 30-year Treasury Constant Maturity Rate")
print(" mortgage30us 30-year Fixed Rate Mortgage Average")
print(" fedfunds Effective Federal Funds Rate")
print(" aaa Moody's Seasoned AAA Corporate Bond Yield")
print(" dexcaus Canada / U.S. Foreign Exchange Rate (CAD per 1 USD)")
print("")
print("Wall St. Journal:")
print(" overview market data overview")
print(" indices us indices overview")
print(" futures futures overview")
print(" usbonds us bond overview")
print(" glbonds global bonds overview")
print(" currencies currency overview")
print("")
print("> report generate automatic report")
print("")
help_text = """https://github.com/GamestonkTerminal/GamestonkTerminal/tree/main/gamestonk_terminal/economy
>> ECONOMY <<
What do you want to do?
cls clear screen
?/help show this menu again
q quit this menu, and shows back to main menu
quit quit to abandon program
CNN:
feargreed CNN Fear and Greed Index
Finnhub:
events economic impact events
Wall St. Journal:
overview market data overview
indices US indices overview
futures futures and commodities overview
usbonds US bonds overview
glbonds global bonds overview
currencies currencies overview
Finviz:
map S&P500 index stocks map
valuation valuation of sectors, industry, country
performance performance of sectors, industry, country
spectrum spectrum of sectors, industry, country
Alpha Vantage:
rtps real-time performance sectors
FRED:
search search FRED series notes
series plot series from https://fred.stlouisfed.org
> report generate automatic report
"""
print(help_text)
def switch(self, an_input: str):
"""Process and dispatch input
@@ -157,83 +175,588 @@ class EconomyController:
def call_events(self, other_args: List[str]):
"""Process events command"""
finnhub_view.economy_calendar_events(other_args)
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="events",
description="""
Output economy impact calendar impact events. [Source: Finnhub]
""",
)
parser.add_argument(
"-c",
"--country",
action="store",
dest="country",
type=str,
default="US",
choices=["NZ", "AU", "ERL", "CA", "EU", "US", "JP", "CN", "GB", "CH"],
help="Country from where to get economy calendar impact events",
)
parser.add_argument(
"-n",
"--num",
action="store",
dest="num",
type=check_positive,
default=10,
help="Number economy calendar impact events to display",
)
parser.add_argument(
"-i",
"--impact",
action="store",
dest="impact",
type=str,
default="all",
choices=["low", "medium", "high", "all"],
help="Impact of the economy event",
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-c")
def call_fred(self, other_args: List[str]):
"""Process fred command"""
fred_view.display_fred(other_args, "")
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
def call_vixcls(self, other_args: List[str]):
"""Process vixcls command"""
fred_view.display_fred(other_args, "VIXCLS")
finnhub_view.economy_calendar_events(
country=ns_parser.country,
num=ns_parser.num,
impact=ns_parser.impact,
export=ns_parser.export,
)
def call_gdp(self, other_args: List[str]):
"""Process gdp command"""
fred_view.display_fred(other_args, "GDP")
def call_unrate(self, other_args: List[str]):
"""Process unrate command"""
fred_view.display_fred(other_args, "UNRATE")
def call_dgs1(self, other_args: List[str]):
"""Process dgs1 command"""
fred_view.display_fred(other_args, "DGS1")
def call_dgs5(self, other_args: List[str]):
"""Process dgs5 command"""
fred_view.display_fred(other_args, "DGS5")
def call_dgs10(self, other_args: List[str]):
"""Process dgs10 command"""
fred_view.display_fred(other_args, "DGS10")
def call_dgs30(self, other_args: List[str]):
"""Process dgs30 command"""
fred_view.display_fred(other_args, "DGS30")
def call_mortgage30us(self, other_args: List[str]):
"""Process mortgage30us command"""
fred_view.display_fred(other_args, "MORTGAGE30US")
def call_fedfunds(self, other_args: List[str]):
"""Process fedfunds command"""
fred_view.display_fred(other_args, "FEDFUNDS")
def call_aaa(self, other_args: List[str]):
"""Process aaa command"""
fred_view.display_fred(other_args, "AAA")
def call_dexcaus(self, other_args: List[str]):
"""Process dexcaus command"""
fred_view.display_fred(other_args, "DEXCAUS")
except Exception as e:
print(e, "\n")
def call_feargreed(self, other_args: List[str]):
"""Process feargreed command"""
cnn_view.fear_and_greed_index(other_args)
parser = argparse.ArgumentParser(
add_help=False,
prog="feargreed",
description="""
Display CNN Fear And Greed Index from https://money.cnn.com/data/fear-and-greed/.
""",
)
parser.add_argument(
"-i",
"--indicator",
dest="indicator",
required=False,
type=str,
choices=["jbd", "mv", "pco", "mm", "sps", "spb", "shd", "index"],
help="""
CNN Fear And Greed indicator or index. From Junk Bond Demand, Market Volatility,
Put and Call Options, Market Momentum Stock Price Strength, Stock Price Breadth,
Safe Heaven Demand, and Index.
""",
)
try:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-i")
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
cnn_view.fear_and_greed_index(indicator=ns_parser.indicator)
except Exception as e:
print(e, "\n")
def call_overview(self, other_args: List[str]):
"""Process overview command"""
wsj_view.display_overview(other_args)
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="overview",
description="Market overview. [Source: Wall St. Journal]",
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
wsj_view.display_overview(
export=ns_parser.export,
)
except Exception as e:
print(e, "\n")
def call_indices(self, other_args: List[str]):
"""Process indices command"""
wsj_view.display_indices(other_args)
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="indices",
description="US indices. [Source: Wall St. Journal]",
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
wsj_view.display_indices(
export=ns_parser.export,
)
except Exception as e:
print(e, "\n")
def call_futures(self, other_args: List[str]):
"""Process futures command"""
wsj_view.display_futures(other_args)
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="futures",
description="Futures/Commodities. [Source: Wall St. Journal]",
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
wsj_view.display_futures(
export=ns_parser.export,
)
except Exception as e:
print(e, "\n")
def call_usbonds(self, other_args: List[str]):
"""Process usbonds command"""
wsj_view.display_usbonds(other_args)
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="usbonds",
description="US Bonds. [Source: Wall St. Journal]",
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
wsj_view.display_usbonds(
export=ns_parser.export,
)
except Exception as e:
print(e, "\n")
def call_glbonds(self, other_args: List[str]):
"""Process glbonds command"""
wsj_view.display_glbonds(other_args)
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="glbonds",
description="Global Bonds. [Source: Wall St. Journal]",
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
wsj_view.display_glbonds(
export=ns_parser.export,
)
except Exception as e:
print(e, "\n")
def call_currencies(self, other_args: List[str]):
"""Process curremcies command"""
wsj_view.display_currencies(other_args)
"""Process currencies command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="currencies",
description="Currencies. [Source: Wall St. Journal]",
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
wsj_view.display_currencies(
export=ns_parser.export,
)
except Exception as e:
print(e, "\n")
def call_map(self, other_args: List[str]):
"""Process map command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="map",
description="""
Performance index stocks map categorized by sectors and industries.
Size represents market cap. Opens web-browser. [Source: Finviz]
""",
)
parser.add_argument(
"-p",
"--period",
action="store",
dest="s_period",
type=str,
default="1d",
choices=["1d", "1w", "1m", "3m", "6m", "1y"],
help="Performance period.",
)
parser.add_argument(
"-t",
"--type",
action="store",
dest="s_type",
type=str,
default="sp500",
choices=["sp500", "world", "full", "etf"],
help="Map filter type.",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
finviz_view.map_sp500_view(
period=ns_parser.s_period,
map_type=ns_parser.s_type,
)
except Exception as e:
print(e, "\n")
def call_valuation(self, other_args: List[str]):
"""Process valuation command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="valuation",
description="""
View group (sectors, industry or country) valuation data. [Source: Finviz]
""",
)
parser.add_argument(
"-g",
"--group",
type=str,
default="Sector",
dest="group",
help="Data group (sector, industry or country)",
choices=list(self.d_GROUPS.keys()),
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-g")
other_args = [other_args[0], " ".join(other_args[1:])]
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
finviz_view.view_group_data(
s_group=self.d_GROUPS[ns_parser.group],
data_type="valuation",
export=ns_parser.export,
)
except Exception as e:
print(e, "\n")
def call_performance(self, other_args: List[str]):
"""Process performance command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="performance",
description="""
View group (sectors, industry or country) performance data. [Source: Finviz]
""",
)
parser.add_argument(
"-g",
"--group",
type=str,
default="Sector",
dest="group",
help="Data group (sector, industry or country)",
choices=list(self.d_GROUPS.keys()),
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-g")
other_args = [other_args[0], " ".join(other_args[1:])]
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
finviz_view.view_group_data(
s_group=self.d_GROUPS[ns_parser.group],
data_type="performance",
export=ns_parser.export,
)
except Exception as e:
print(e, "\n")
def call_spectrum(self, other_args: List[str]):
"""Process spectrum command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="spectrum",
description="""
View group (sectors, industry or country) spectrum data. [Source: Finviz]
""",
)
parser.add_argument(
"-g",
"--group",
type=str,
default="Sector",
dest="group",
help="Data group (sector, industry or country)",
choices=list(self.d_GROUPS.keys()),
)
try:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-g")
other_args = [other_args[0], " ".join(other_args[1:])]
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
finviz_view.view_group_data(
s_group=self.d_GROUPS[ns_parser.group],
data_type="spectrum",
export="",
)
# Due to Finviz implementation of Spectrum, we delete the generated spectrum figure
# after saving it and displaying it to the user
os.remove(ns_parser.group + ".jpg")
except Exception as e:
print(e, "\n")
def call_rtps(self, other_args: List[str]):
"""Process rtps command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="rtps",
description="""
Real-time and historical sector performances calculated from
S&P500 incumbents. Pops plot in terminal. [Source: Alpha Vantage]
""",
)
parser.add_argument(
"--raw",
action="store_true",
dest="raw",
help="Only output raw data",
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
alphavantage_view.realtime_performance_sector(
raw=ns_parser.raw,
export=ns_parser.export,
)
except Exception as e:
print(e, "\n")
def call_series(self, other_args: List[str]):
"""Process series command"""
parser = argparse.ArgumentParser(
add_help=False,
prog="series",
description="""
Display (multiple) series from https://fred.stlouisfed.org. [Source: FRED]
""",
)
parser.add_argument(
"-i",
"--id",
dest="series_id",
required="-h" not in other_args,
type=str,
help="FRED Series from https://fred.stlouisfed.org. For multiple series use: series1,series2,series3",
)
parser.add_argument(
"-s",
dest="start_date",
type=valid_date,
default="2019-01-01",
help="Starting date (YYYY-MM-DD) of data",
)
parser.add_argument(
"--raw",
action="store_true",
dest="raw",
help="Only output raw data",
)
parser.add_argument(
"--export",
choices=["csv", "json", "xlsx"],
default="",
type=str,
dest="export",
help="Export dataframe data to csv,json,xlsx file",
)
try:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-i")
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
fred_view.display_series(
series=ns_parser.series_id,
start_date=ns_parser.start_date,
raw=ns_parser.raw,
export=ns_parser.export,
)
except Exception as e:
print(e, "\n")
def call_search(self, other_args: List[str]):
"""Process search command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="search",
description="Print series notes when searching for series. [Source: FRED]",
)
parser.add_argument(
"-s",
"--series",
action="store",
dest="series_term",
type=str,
required="-h" not in other_args,
help="Search for this series term.",
)
parser.add_argument(
"-n",
"--num",
action="store",
dest="num",
type=check_positive,
default=5,
help="Maximum number of series notes to display.",
)
try:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-s")
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
fred_view.notes(
series_term=ns_parser.series_term,
num=ns_parser.num,
)
except Exception as e:
print(e, "\n")
def call_report(self, _):
"""Process report command"""

22
gamestonk_terminal/economy/finnhub_model.py Normal file
View File

@@ -0,0 +1,22 @@
import requests
import pandas as pd
from gamestonk_terminal import config_terminal as cfg
def get_economy_calendar_events() -> pd.DataFrame:
"""Get economic calendar events
Returns
-------
pd.DataFrame
Get dataframe with economic calendar events
"""
response = requests.get(
f"https://finnhub.io/api/v1/calendar/economic?token={cfg.API_FINNHUB_KEY}"
)
if response.status_code == 200:
d_data = response.json()
if "economicCalendar" in d_data:
return pd.DataFrame(d_data["economicCalendar"])
return pd.DataFrame()

175
gamestonk_terminal/economy/finnhub_view.py
View File

@@ -1,131 +1,80 @@
import argparse
from typing import List
import requests
import pandas as pd
from gamestonk_terminal import config_terminal as cfg
from gamestonk_terminal.helper_funcs import (
parse_known_args_and_warn,
check_positive,
)
import os
from tabulate import tabulate
from gamestonk_terminal.economy import finnhub_model
from gamestonk_terminal.helper_funcs import export_data
def get_economy_calendar_events() -> pd.DataFrame:
"""Get economic calendar events
Returns
-------
pd.DataFrame
Get dataframe with economic calendar events
"""
response = requests.get(
f"https://finnhub.io/api/v1/calendar/economic?token={cfg.API_FINNHUB_KEY}"
)
if response.status_code == 200:
d_data = response.json()
if "economicCalendar" in d_data:
return pd.DataFrame(d_data["economicCalendar"])
return pd.DataFrame()
def economy_calendar_events(other_args: List[str]):
"""Output economy calendar impact events
def economy_calendar_events(country: str, num: int, impact: str, export: str):
"""Output economy calendar impact events. [Source: Finnhub]
Parameters
----------
other_args : List[str]
Command line arguments to be processed with argparse
country : str
Country from where to get economy calendar impact events
num : int
Number economy calendar impact events to display
impact : str
Impact of the economy event
export : str
Export dataframe data to csv,json,xlsx file
"""
parser = argparse.ArgumentParser(
add_help=False,
prog="events",
description="""
Output economy impact calendar impact events. [Source: https://finnhub.io]
""",
)
parser.add_argument(
"-c",
"--country",
action="store",
dest="country",
type=str,
default="US",
choices=["NZ", "AU", "ERL", "CA", "EU", "US", "JP", "CN", "GB", "CH"],
help="Country from where to get economy calendar impact events",
)
parser.add_argument(
"-n",
"--num",
action="store",
dest="num",
type=check_positive,
default=10,
help="Number economy calendar impact events to display",
)
parser.add_argument(
"-i",
"--impact",
action="store",
dest="impact",
type=str,
default="all",
choices=["low", "medium", "high", "all"],
help="Impact of the economy event",
df_events = finnhub_model.get_economy_calendar_events()
if df_events.empty:
print("No latest economy calendar events found\n")
return
df_econ_calendar = df_events[df_events["country"] == country].sort_values(
"time", ascending=True
)
try:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-c")
if df_econ_calendar.empty:
print("No latest economy calendar events found in the specified country\n")
return
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
df_events = get_economy_calendar_events()
if df_events.empty:
print("No latest economy calendar events found\n")
return
df_econ_calendar = df_events[
df_events["country"] == ns_parser.country
].sort_values("time", ascending=True)
if impact != "all":
df_econ_calendar = df_econ_calendar[df_econ_calendar["impact"] == impact]
if df_econ_calendar.empty:
print("No latest economy calendar events found in the specified country\n")
print(
"No latet economy calendar events found in the specified country with this impact\n"
)
return
if ns_parser.impact != "all":
df_econ_calendar = df_econ_calendar[
df_econ_calendar["impact"] == ns_parser.impact
]
df_econ_calendar = df_econ_calendar.fillna("").head(n=num)
if df_econ_calendar.empty:
print(
"No latet economy calendar events found in the specified country with this impact\n"
)
return
d_econ_calendar_map = {
"actual": "Actual release",
"prev": "Previous release",
"country": "Country",
"unit": "Unit",
"estimate": "Estimate",
"event": "Event",
"impact": "Impact Level",
"time": "Release time",
}
df_econ_calendar = df_econ_calendar.fillna("---").head(n=ns_parser.num)
df_econ_calendar = df_econ_calendar[
["time", "event", "impact", "prev", "estimate", "actual", "unit"]
].rename(columns=d_econ_calendar_map)
d_econ_calendar_map = {
"actual": "Actual release",
"prev": "Previous release",
"country": "Country",
"unit": "Unit",
"estimate": "Estimate",
"event": "Event",
"impact": "Impact Level",
"time": "Release time",
}
df_econ_calendar.replace("", float("NaN"), inplace=True)
df_econ_calendar.dropna(how="all", axis=1, inplace=True)
df_econ_calendar = df_econ_calendar[
["time", "event", "impact", "prev", "estimate", "actual", "unit"]
].rename(columns=d_econ_calendar_map)
print(
tabulate(
df_econ_calendar,
headers=df_econ_calendar.columns,
showindex=False,
floatfmt=".2f",
tablefmt="fancy_grid",
)
)
print("")
print(df_econ_calendar.to_string(index=False))
print("")
except Exception as e:
print(e, "\n")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"events",
df_econ_calendar,
)

36
gamestonk_terminal/economy/finviz_model.py Normal file
View File

@@ -0,0 +1,36 @@
""" Finviz Model """
__docformat__ = "numpy"
import pandas as pd
from finvizfinance.group import valuation, performance, spectrum
def get_valuation_performance_data(group: str, data_type: str) -> pd.DataFrame:
"""Get group (sectors, industry or country) valuation/performance data
Parameters
----------
group : str
sectors, industry or country
data_type : str
valuation or performance
Returns
----------
pd.DataFrame
dataframe with valuation/performance data
"""
if data_type == "valuation":
return valuation.Valuation().ScreenerView(group=group)
return performance.Performance().ScreenerView(group=group)
def get_spectrum_data(group: str):
"""Get group (sectors, industry or country) valuation/performance data
Parameters
----------
group : str
sectors, industry or country
"""
spectrum.Spectrum().ScreenerView(group=group)

73
gamestonk_terminal/economy/finviz_view.py Normal file
View File

@@ -0,0 +1,73 @@
""" Finviz View """
__docformat__ = "numpy"
import os
import webbrowser
from tabulate import tabulate
from PIL import Image
from gamestonk_terminal.economy import finviz_model
from gamestonk_terminal.helper_funcs import export_data
def map_sp500_view(period: str, map_type: str):
"""Opens Finviz map website in a browser. [Source: Finviz]
Parameters
----------
period : str
Performance period
map_type : str
Map filter type
"""
# Conversion from period and type, to fit url requirements
d_period = {"1d": "", "1w": "w1", "1m": "w4", "3m": "w13", "6m": "w26", "1y": "w52"}
d_type = {"sp500": "sec", "world": "geo", "full": "sec_all", "etf": "etf"}
# TODO: Try to get this image and output it instead of opening browser
webbrowser.open(
f"https://finviz.com/map.ashx?t={d_type[map_type]}&st={d_period[period]}"
)
print("")
def view_group_data(s_group: str, data_type: str, export: str):
"""View group (sectors, industry or country) valuation/performance/spectrum data
Parameters
----------
s_group : str
group between sectors, industry or country
data_type : str
select data type to see data between valuation, performance and spectrum
export : str
Export dataframe data to csv,json,xlsx file
"""
if data_type in ("valuation", "performance"):
df_group = finviz_model.get_valuation_performance_data(s_group, data_type)
print(
tabulate(
df_group.fillna(""),
showindex=False,
floatfmt=".2f",
headers=df_group.columns,
tablefmt="fancy_grid",
),
"\n",
)
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
data_type,
df_group,
)
elif data_type == "spectrum":
finviz_model.get_spectrum_data(s_group)
img = Image.open(s_group + ".jpg")
img.show()
else:
print(
"Invalid data type. Choose between valuation, performance and spectrum.\n"
)

98
gamestonk_terminal/economy/fred_model.py Normal file
View File

@@ -0,0 +1,98 @@
""" Fred View """
__docformat__ = "numpy"
from typing import List, Tuple
import pandas as pd
import fred
from fredapi import Fred
from gamestonk_terminal import config_terminal as cfg
def get_series_notes(series_term: str, num: int) -> str:
"""Get Series notes. [Source: FRED]
Parameters
----------
series_term : str
Search for this series term
num : int
Maximum number of series notes to display
Returns
----------
notes : str
Series notes output
"""
fred.key(cfg.API_FRED_KEY)
d_series = fred.search(series_term)
if "seriess" not in d_series:
return "No Series found using this term!\n"
df_fred = pd.DataFrame(d_series["seriess"])
if df_fred.empty:
return "No Series found using this term!\n"
df_fred = df_fred.sort_values(by=["popularity"], ascending=False).head(num)
notes = ""
for _, series in df_fred.iterrows():
if series["notes"]:
notes += series["id"] + "\n"
notes += "-" * len(series["id"]) + "\n"
notes += series["notes"] + "\n\n"
if not notes:
return "Series notes not found!\n"
return notes
def get_series_ids(series_term: str, num: int) -> Tuple[List[str], List[str]]:
"""Get Series IDs. [Source: FRED]
Parameters
----------
series_term : str
Search for this series term
num : int
Maximum number of series IDs to output
Returns
----------
List[str]
List of series IDs
List[str]
List of series Titles
"""
fred.key(cfg.API_FRED_KEY)
d_series = fred.search(series_term)
if "seriess" not in d_series:
return [], []
if not d_series["seriess"]:
return [], []
df_series = pd.DataFrame(d_series["seriess"])
df_series = df_series.sort_values(by=["popularity"], ascending=False).head(num)
return df_series["id"].values, df_series["title"].values
def get_series_data(series_id: str, start: str):
"""Get Series data. [Source: FRED]
Parameters
----------
series_id : str
Series ID to get data from
start : str
Start date to get data from, format yyyy-mm-dd
Returns
----------
pd.DataFrame
Series data
"""
fredapi_client = Fred(cfg.API_FRED_KEY)
return fredapi_client.get_series(series_id, start)

277
gamestonk_terminal/economy/fred_view.py
View File

@@ -1,194 +1,145 @@
""" Fred View """
__docformat__ = "numpy"
import argparse
from typing import List
import pandas as pd
import os
from tabulate import tabulate
from pandas.plotting import register_matplotlib_converters
import pandas as pd
import matplotlib.pyplot as plt
from fredapi import Fred
from gamestonk_terminal.helper_funcs import (
parse_known_args_and_warn,
valid_date,
plot_autoscale,
)
from gamestonk_terminal.economy import fred_model
from gamestonk_terminal.helper_funcs import plot_autoscale, export_data
from gamestonk_terminal.config_plot import PLOT_DPI
from gamestonk_terminal import config_terminal as cfg
from gamestonk_terminal import feature_flags as gtff
register_matplotlib_converters()
fred_series_description = {
"VIXCLS": "Volatility Index",
"GDP": "Gross Domestic Product",
"UNRATE": "Unemployment Rate",
"DGS1": "1-Year Treasury Constant Maturity Rate",
"DGS5": "5-Year Treasury Constant Maturity Rate",
"DGS10": "10-Year Treasury Constant Maturity Rate",
"DGS30": "30-Year Treasury Constant Maturity Rate",
"MORTGAGE30US": "30-Year Mortgage Rate",
"FEDFUNDS": "Effective Federal Funds Rate",
"AAA": "Moody's Seasoned AAA Corporate Bond Yield",
"DEXCAUS": "Canada / U.S. Foreign Exchange Rate",
}
def display_fred(other_args: List[str], choice: str):
"""Display customized Federal Reserve Economic Data (FRED) from https://fred.stlouisfed.org.
It is possible to display multiple series.
def notes(series_term: str, num: int):
"""Print Series notes. [Source: FRED]
Parameters
----------
other_args : List[str]
argparse other args
choice : str
Fred data series: "VIXCLS", "GDP", "DGS1", "DGS5", "DGS10", "DGS30", "MORTGAGE30US", "FEDFUNDS",
"AAA", "DEXCAUS", "UNRATE",
series_term : str
Search for these series_term
num : int
Maximum number of series notes to display
"""
print(fred_model.get_series_notes(series_term, num))
parser = argparse.ArgumentParser(
add_help=False,
prog=choice if choice else "fred",
description="""
Display customized Federal Reserve Economic Data (FRED) from https://fred.stlouisfed.org.
It is possible to display multiple series.
""",
)
parser.add_argument(
"-i",
"--id",
dest="series_id",
required=not bool(choice) and "-h" not in other_args,
type=str,
default=choice.upper(),
help="FRED Series ID from https://fred.stlouisfed.org. For multiple series use: series1,series2,series3",
)
def display_series(series: str, start_date: str, raw: bool, export: str):
"""Display (multiple) series from https://fred.stlouisfed.org. [Source: FRED]
parser.add_argument(
"-s",
dest="start_date",
type=valid_date,
default="2019-01-01",
help="Starting date (YYYY-MM-DD) of data",
)
Parameters
----------
series : str
FRED Series ID from https://fred.stlouisfed.org. For multiple series use: series1,series2,series3
start_date : str
Starting date (YYYY-MM-DD) of data
raw : bool
Output only raw data
export : str
Export dataframe data to csv,json,xlsx file
"""
if export:
l_series_fred = list()
parser.add_argument(
"-t",
"--text",
action="store_true",
dest="text",
help="Only output text data",
)
if not raw:
_, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
ax.axes.get_yaxis().set_visible(False)
plt.subplots_adjust(right=0.9 - series.count(",") * 0.1)
l_colors = [
"tab:blue",
"tab:orange",
"tab:green",
"tab:red",
"tab:purple",
"tab:brown",
"tab:pink",
"tab:gray",
"tab:olive",
"tab:cyan",
]
try:
if not choice:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-i")
ns_parser = parse_known_args_and_warn(parser, other_args)
l_ts_start = list()
l_ts_end = list()
p = {}
success = -1
success_series = list()
success_titles = list()
if not ns_parser:
return
for serie_term in series.split(","):
if serie_term:
l_series, l_title = fred_model.get_series_ids(serie_term, 5)
fred = Fred(api_key=cfg.API_FRED_KEY)
if len(l_series) == 0:
print(f"No series found for term '{serie_term}'\n")
continue
if "," in ns_parser.series_id:
if not ns_parser.text:
l_colors = [
"tab:blue",
"tab:orange",
"tab:green",
"tab:red",
"tab:purple",
"tab:brown",
"tab:pink",
"tab:gray",
"tab:olive",
"tab:cyan",
]
l_ts_start = list()
l_ts_end = list()
p = {}
_, ax = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
ax.axes.get_yaxis().set_visible(False)
plt.subplots_adjust(right=0.9 - ns_parser.series_id.count(",") * 0.1)
print(f"For '{serie_term}', series IDs found: {', '.join(l_series)}.\n")
series = ns_parser.series_id.split(",")
ser = l_series[0]
ser_title = l_title[0]
df_fred = fred_model.get_series_data(ser, start_date)
success = -1
success_series = list()
for series_id in series:
try:
d_data = fred.get_series(series_id, ns_parser.start_date)
success += 1
success_series.append(series_id.upper())
except Exception:
print(f"Series '{series_id}' doesn't exist!")
continue
if export:
l_series_fred.append(df_fred)
df_fred = pd.DataFrame(d_data, columns=[f"{series_id}"])
df_fred.index.name = "Date"
if ns_parser.text:
print(df_fred.dropna().to_string(), "\n")
else:
axes = ax.twinx()
axes.spines["right"].set_position(("axes", 1 + success * 0.15))
axes.spines["right"].set_color(l_colors[success])
(p[success],) = axes.plot(
df_fred.index,
df_fred.iloc[:, 0],
c=l_colors[success],
label=series_id.upper(),
)
axes.yaxis.label.set_color(l_colors[success])
l_ts_start.append(df_fred.index[0])
l_ts_end.append(df_fred.index[-1])
if not ns_parser.text and success:
plt.title("FRED: " + ", ".join(success_series))
plt.xlim(min(l_ts_start), max(l_ts_end))
plt.gcf().autofmt_xdate()
plt.xlabel("Time")
plt.legend([val for _, val in p.items()], success_series)
plt.gca().spines["left"].set_visible(False)
plt.show()
print("")
else:
d_data = fred.get_series(ns_parser.series_id, ns_parser.start_date)
df_fred = pd.DataFrame(d_data, columns=[f"{ns_parser.series_id}"])
df_fred.index.name = "Date"
if ns_parser.text:
print(df_fred.to_string())
if raw:
df_fred.index = df_fred.index.strftime("%d/%m/%Y")
print(
tabulate(
df_fred.dropna().to_frame(),
showindex=True,
headers=[f"{ser}: {ser_title}"],
tablefmt="fancy_grid",
floatfmt=".2f",
),
"\n",
)
else:
plt.figure(figsize=plot_autoscale(), dpi=PLOT_DPI)
plt.plot(df_fred.index, df_fred.iloc[:, 0])
plt.xlabel("Time")
plt.xlim(df_fred.index[0], df_fred.index[-1])
plt.ylabel(f"{ns_parser.series_id.upper()}")
plt.grid(b=True, which="major", color="#666666", linestyle="-")
plt.minorticks_on()
plt.grid(
b=True, which="minor", color="#999999", linestyle="-", alpha=0.2
)
if choice:
plt.title(fred_series_description[ns_parser.series_id])
if gtff.USE_ION:
plt.ion()
plt.show()
print("")
success += 1
success_series.append(ser.upper())
success_titles.append(ser_title)
except SystemExit:
print("")
except Exception as e:
print(e, "\n")
return
axes = ax.twinx()
axes.spines["right"].set_position(("axes", 1 + success * 0.15))
axes.spines["right"].set_color(l_colors[success])
(p[success],) = axes.plot(
df_fred.index,
df_fred.values,
c=l_colors[success],
label=ser.upper(),
)
axes.yaxis.label.set_color(l_colors[success])
l_ts_start.append(df_fred.index[0])
l_ts_end.append(df_fred.index[-1])
if not raw and success > -1:
plt.title("FRED: " + ", ".join(success_series))
plt.xlim(min(l_ts_start), max(l_ts_end))
plt.gcf().autofmt_xdate()
plt.xlabel("Time")
plt.legend(
[val for _, val in p.items()], success_titles, loc="best", prop={"size": 6}
)
plt.gca().spines["left"].set_visible(False)
if gtff.USE_ION:
plt.ion()
plt.show()
if export:
df_data = pd.concat(l_series_fred, axis=1)
df_data.columns = success_series
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"series",
df_data,
)

24
gamestonk_terminal/economy/wsj_model.py
View File

@@ -5,8 +5,8 @@ import pandas as pd
def us_indices() -> pd.DataFrame:
"""
Get the top US indices
"""Get the top US indices
Returns
-------
indices: pd.DataFrame
@@ -42,8 +42,8 @@ def us_indices() -> pd.DataFrame:
def market_overview() -> pd.DataFrame:
"""
Scrape data for market overview
"""Scrape data for market overview
Returns
-------
overview: pd.DataFrame
@@ -77,8 +77,8 @@ def market_overview() -> pd.DataFrame:
def top_commodities() -> pd.DataFrame:
"""
Scrape data for top commodities
"""Scrape data for top commodities
Returns
-------
commodities: pd.DataFrame
@@ -113,8 +113,8 @@ def top_commodities() -> pd.DataFrame:
def us_bonds() -> pd.DataFrame:
"""
Scrape data for us bonds
"""Scrape data for us bonds
Returns
-------
bonds: pd.DataFrame
@@ -150,8 +150,8 @@ def us_bonds() -> pd.DataFrame:
def global_bonds() -> pd.DataFrame:
"""
Scrape data for global bonds
"""Scrape data for global bonds
Returns
-------
bonds: pd.DataFrame
@@ -182,8 +182,8 @@ def global_bonds() -> pd.DataFrame:
def global_currencies() -> pd.DataFrame:
"""
Scrape data for global currencies
"""Scrape data for global currencies
Returns
-------
currencies: pd.DataFrame

311
gamestonk_terminal/economy/wsj_view.py
View File

@@ -1,224 +1,199 @@
"""WSJ view """
__docformat__ = "numpy"
import argparse
from typing import List
import os
from tabulate import tabulate
from gamestonk_terminal.economy.wsj_model import (
market_overview,
us_bonds,
us_indices,
global_bonds,
global_currencies,
top_commodities,
)
from gamestonk_terminal.helper_funcs import parse_known_args_and_warn
from gamestonk_terminal.economy import wsj_model
from gamestonk_terminal.helper_funcs import export_data
def display_overview(other_args: List[str]):
"""Display market overview
def display_overview(export: str):
"""Market overview. [Source: Wall St. Journal]
Parameters
----------
other_args: List[str]
Argparse arguments
export : str
Export dataframe data to csv,json,xlsx file
"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="overview",
description="WSJ market overview",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
data = market_overview()
print(
tabulate(
data,
showindex=False,
headers=data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
df_data = wsj_model.market_overview()
if df_data.empty:
print("No overview data available\n")
return
print(
tabulate(
df_data,
showindex=False,
headers=df_data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
print("")
)
print("")
except Exception as e:
print(e, "\n")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"overview",
df_data,
)
def display_indices(other_args: List[str]):
"""Display us indices
def display_indices(export: str):
"""US indices. [Source: Wall St. Journal]
Parameters
----------
other_args: List[str]
Argparse arguments
export : str
Export dataframe data to csv,json,xlsx file
"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="indices",
description="WSJ US Indices",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
df_data = wsj_model.us_indices()
if df_data.empty:
print("No indices data available\n")
return
data = us_indices()
print(
tabulate(
data,
showindex=False,
headers=data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
print(
tabulate(
df_data,
showindex=False,
headers=df_data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
print("")
)
print("")
except Exception as e:
print(e, "\n")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"indices",
df_data,
)
def display_futures(other_args: List[str]):
"""Display futures/commodities
def display_futures(export: str):
"""Futures/Commodities. [Source: Wall St. Journal]
Parameters
----------
other_args: List[str]
Argparse arguments
export : str
Export dataframe data to csv,json,xlsx file
"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="futures",
description="WSJ futures/commodities",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
data = top_commodities()
print(
tabulate(
data,
showindex=False,
headers=data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
df_data = wsj_model.top_commodities()
if df_data.empty:
print("No futures/commodities data available\n")
return
print(
tabulate(
df_data,
showindex=False,
headers=df_data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
print("")
)
print("")
except Exception as e:
print(e, "\n")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"futures",
df_data,
)
def display_usbonds(other_args: List[str]):
"""Display us bonds overview
def display_usbonds(export: str):
"""US bonds. [Source: Wall St. Journal]
Parameters
----------
other_args: List[str]
Argparse arguments
export : str
Export dataframe data to csv,json,xlsx file
"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="usbonds",
description="WSJ US Bonds overview",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
df_data = wsj_model.us_bonds()
if df_data.empty:
print("No US bonds data available\n")
return
data = us_bonds()
print(
tabulate(
data,
showindex=False,
headers=data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
print(
tabulate(
df_data,
showindex=False,
headers=df_data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
print("")
)
print("")
except Exception as e:
print(e, "\n")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"usbonds",
df_data,
)
def display_glbonds(other_args: List[str]):
"""Display global bond overview
def display_glbonds(export: str):
"""Global bonds. [Source: Wall St. Journal]
Parameters
----------
other_args: List[str]
Argparse arguments
export : str
Export dataframe data to csv,json,xlsx file
"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="glbond",
description="WSJ global bond overview",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
df_data = wsj_model.global_bonds()
if df_data.empty:
print("No global bonds data available\n")
return
data = global_bonds()
print(
tabulate(
data,
showindex=False,
headers=data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
print(
tabulate(
df_data,
showindex=False,
headers=df_data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
print("")
)
print("")
except Exception as e:
print(e, "\n")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"glbonds",
df_data,
)
def display_currencies(other_args: List[str]):
"""Display global currencies
def display_currencies(export: str):
"""Display currencies. [Source: Wall St. Journal]
Parameters
----------
other_args: List[str]
Argparse arguments
export : str
Export dataframe data to csv,json,xlsx file
"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="currencies",
description="WSJ currency overview",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
df_data = wsj_model.global_currencies()
if df_data.empty:
print("No currencies data available\n")
return
data = global_currencies()
print(
tabulate(
data,
showindex=False,
headers=data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
print(
tabulate(
df_data,
showindex=False,
headers=df_data.columns,
floatfmt=".2f",
tablefmt="fancy_grid",
)
print("")
)
print("")
except Exception as e:
print(e, "\n")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"currencies",
df_data,
)

54
gamestonk_terminal/stocks/discovery/alpha_vantage_view.py
View File

@@ -1,54 +0,0 @@
""" Alpha Vantage View """
__docformat__ = "numpy"
import argparse
from typing import List
import matplotlib.pyplot as plt
from alpha_vantage.sectorperformance import SectorPerformances
from gamestonk_terminal import config_terminal as cfg
from gamestonk_terminal.helper_funcs import parse_known_args_and_warn
from gamestonk_terminal import feature_flags as gtff
def sectors_view(other_args: List[str]):
"""Opens a bar chart with sector performance
Parameters
----------
other_args : List[str]
argparse other args
"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="sectors",
description="""
Real-time and historical sector performances calculated from
S&P500 incumbents. Pops plot in terminal. [Source: Alpha Vantage]
""",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
sector_perf = SectorPerformances(
key=cfg.API_KEY_ALPHAVANTAGE, output_format="pandas"
)
# pylint: disable=unbalanced-tuple-unpacking
df_sectors, _ = sector_perf.get_sector()
# pylint: disable=invalid-sequence-index
df_sectors["Rank A: Real-Time Performance"].plot(kind="bar")
plt.title("Real Time Performance (%) per Sector")
plt.tight_layout()
plt.grid()
if gtff.USE_ION:
plt.ion()
plt.show()
print("")
except Exception as e:
print(e, "\n")

43
gamestonk_terminal/stocks/discovery/disc_controller.py
View File

@@ -10,10 +10,8 @@ from gamestonk_terminal import feature_flags as gtff
from gamestonk_terminal.helper_funcs import get_flair
from gamestonk_terminal.menu import session
from gamestonk_terminal.stocks.discovery import (
alpha_vantage_view,
ark_view,
fidelity_view,
finviz_view,
seeking_alpha_view,
short_interest_view,
simply_wallst_view,
@@ -38,8 +36,6 @@ class DiscoveryController:
"q",
"quit",
"ipo",
"map",
"rtp_sectors",
"gainers",
"losers",
"orders",
@@ -50,9 +46,6 @@ class DiscoveryController:
"simply_wallst",
"spachero",
"uwhales",
"valuation",
"performance",
"spectrum",
"latest",
"trending",
"darkpool",
@@ -64,7 +57,6 @@ class DiscoveryController:
def __init__(self):
"""Constructor"""
self.spectrum_img_to_delete = ""
self.disc_parser = argparse.ArgumentParser(add_help=False, prog="disc")
self.disc_parser.add_argument(
"cmd",
@@ -84,8 +76,6 @@ class DiscoveryController:
print(" quit quit to abandon program")
print("")
print(" ipo past and future IPOs [Finnhub]")
print(" map S&P500 index stocks map [Finviz]")
print(" rtp_sectors real-time performance sectors [Alpha Vantage]")
print(" gainers show latest top gainers [Yahoo Finance]")
print(" losers show latest top losers [Yahoo Finance]")
print(" orders orders by Fidelity Customers [Fidelity]")
@@ -102,9 +92,6 @@ class DiscoveryController:
print(" simply_wallst Simply Wall St. research data [Simply Wall St.]")
print(" spachero great website for SPACs research [SpacHero]")
print(" uwhales good website for SPACs research [UnusualWhales]")
print(" valuation valuation of sectors, industry, country [Finviz]")
print(" performance performance of sectors, industry, country [Finviz]")
print(" spectrum spectrum of sectors, industry, country [Finviz]")
print(" latest latest news [Seeking Alpha]")
print(" trending trending news [Seeking Alpha]")
print(
@@ -137,14 +124,6 @@ class DiscoveryController:
(known_args, other_args) = self.disc_parser.parse_known_args(an_input.split())
# Due to Finviz implementation of Spectrum, we delete the generated spectrum figure
# after saving it and displaying it to the user
if self.spectrum_img_to_delete:
# Confirm that file exists
if os.path.isfile(self.spectrum_img_to_delete + ".jpg"):
os.remove(self.spectrum_img_to_delete + ".jpg")
self.spectrum_img_to_delete = ""
# Help menu again
if known_args.cmd == "?":
self.print_help()
@@ -175,14 +154,6 @@ class DiscoveryController:
"""Process ipo command"""
finnhub_view.ipo_calendar(other_args)
def call_map(self, other_args: List[str]):
"""Process map command"""
finviz_view.map_sp500_view(other_args)
def call_rtp_sectors(self, other_args: List[str]):
"""Process rtp_sectors command"""
alpha_vantage_view.sectors_view(other_args)
def call_gainers(self, other_args: List[str]):
"""Process gainers command"""
yahoo_finance_view.gainers_view(other_args)
@@ -223,20 +194,6 @@ class DiscoveryController:
"""Process uwhales command"""
unusual_whales_view.unusual_whales_view(other_args)
def call_valuation(self, other_args: List[str]):
"""Process valuation command"""
finviz_view.view_group_data(other_args, "valuation")
def call_performance(self, other_args: List[str]):
"""Process performance command"""
finviz_view.view_group_data(other_args, "performance")
def call_spectrum(self, other_args: List[str]):
"""Process spectrum command"""
self.spectrum_img_to_delete = finviz_view.view_group_data(
other_args, "spectrum"
)
def call_latest(self, other_args: List[str]):
"""Process latest command"""
seeking_alpha_view.latest_news_view(other_args)

182
gamestonk_terminal/stocks/discovery/finviz_view.py
View File

@@ -1,182 +0,0 @@
""" Finviz View """
__docformat__ = "numpy"
import argparse
from typing import List
import webbrowser
from finvizfinance.group import valuation, performance, spectrum
from PIL import Image
from gamestonk_terminal.helper_funcs import parse_known_args_and_warn
l_GROUPS = [
"Sector",
"Industry",
"Industry (Basic Materials)",
"Industry (Communication Services)",
"Industry (Consumer Cyclical)",
"Industry (Consumer Defensive)",
"Industry (Energy)",
"Industry (Financial)",
"Industry (Healthcare)",
"Industry (Industrials)",
"Industry (Real Estate)",
"Industry (Technology)",
"Industry (Utilities)",
"Country (U.S. listed stocks only)",
"Capitalization",
]
def map_sp500_view(other_args: List[str]):
"""Opens Finviz website in a browser
Parameters
----------
other_args : List[str]
argparse other args
"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="map",
description="""
Performance index stocks map categorized by sectors and industries.
Size represents market cap. Opens web-browser. [Source: Finviz]
""",
)
parser.add_argument(
"-p",
"--period",
action="store",
dest="s_period",
type=str,
default="1d",
choices=["1d", "1w", "1m", "3m", "6m", "1y"],
help="Performance period.",
)
parser.add_argument(
"-t",
"--type",
action="store",
dest="s_type",
type=str,
default="sp500",
choices=["sp500", "world", "full", "etf"],
help="Map filter type.",
)
# Conversion from period and type, to fit url requirements
d_period = {"1d": "", "1w": "w1", "1m": "w4", "3m": "w13", "6m": "w26", "1y": "w52"}
d_type = {"sp500": "sec", "world": "geo", "full": "sec_all", "etf": "etf"}
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
webbrowser.open(
f"https://finviz.com/map.ashx?t={d_type[ns_parser.s_type]}&st={d_period[ns_parser.s_period]}"
)
print("")
except Exception as e:
print(e, "\n")
def get_valuation_performance_data(group: str, data_type: str):
"""Get group (sectors, industry or country) valuation/performance data
Parameters
----------
group : str
sectors, industry or country
data_type : str
valuation or performance
Returns
----------
pd.DataFrame
dataframe with valuation/performance data
"""
if data_type == "valuation":
return valuation.Valuation().ScreenerView(group=group)
return performance.Performance().ScreenerView(group=group)
def get_spectrum_data(group: str):
"""Get group (sectors, industry or country) valuation/performance data
Parameters
----------
group : str
sectors, industry or country
"""
spectrum.Spectrum().ScreenerView(group=group)
def view_group_data(other_args: List[str], data_type: str):
"""View group (sectors, industry or country) valuation/performance/spectrum data
Parameters
----------
other_args : List[str]
argparse other args
data_type : str
select data type to see data between valuation, performance and spectrum
"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="group_data",
description="""
View group (sectors, industry or country) valuation/performance/spectrum data. [Source: Finviz]
""",
)
parser.add_argument(
"-g",
"--group",
nargs="+",
type=str,
default="Sector",
dest="group",
help="Data group (sector, industry or country)",
choices=l_GROUPS,
)
try:
if other_args:
if "-" not in other_args[0]:
other_args.insert(0, "-g")
other_args = [other_args[0], " ".join(other_args[1:])]
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return ""
if isinstance(ns_parser.group, List):
ns_parser.group = ns_parser.group[0]
if data_type in ("valuation", "performance"):
df_group = get_valuation_performance_data(ns_parser.group, data_type)
print(df_group.to_string())
print("")
elif data_type == "spectrum":
get_spectrum_data(ns_parser.group)
img = Image.open(ns_parser.group + ".jpg")
img.show()
print("")
return ns_parser.group
else:
print(
"Invalid data type. Choose between valuation, performance and spectrum.\n"
)
return ""
except SystemExit:
print("")
return ""

46
poetry.lock generated vendored
View File

@@ -651,6 +651,17 @@ category = "main"
optional = true
python-versions = "*"
[[package]]
name = "fred"
version = "3.1"
description = "St. Louis Federal Reserve FRED API"
category = "main"
optional = false
python-versions = "*"
[package.dependencies]
requests = "*"
[[package]]
name = "fredapi"
version = "0.4.3"
@@ -3052,7 +3063,7 @@ prediction = ["tensorflow", "pmdarima"]
[metadata]
lock-version = "1.1"
python-versions = "^3.6.8"
content-hash = "90b9e9207f1a4680fc23f634392afb9c45bbc0227f36c6b6c1a1afde4dcdcb12"
content-hash = "152e3c597c933d00b15ee5c1ba97452112ae228c8995e0780303a378b5906a24"
[metadata.files]
absl-py = [
@@ -3141,10 +3152,6 @@ argon2-cffi = [
{file = "argon2_cffi-20.1.0-cp38-cp38-win_amd64.whl", hash = "sha256:9dfd5197852530294ecb5795c97a823839258dfd5eb9420233c7cfedec2058f2"},
{file = "argon2_cffi-20.1.0-cp39-cp39-win32.whl", hash = "sha256:e2db6e85c057c16d0bd3b4d2b04f270a7467c147381e8fd73cbbe5bc719832be"},
{file = "argon2_cffi-20.1.0-cp39-cp39-win_amd64.whl", hash = "sha256:8a84934bd818e14a17943de8099d41160da4a336bcc699bb4c394bbb9b94bd32"},
{file = "argon2_cffi-20.1.0-pp36-pypy36_pp73-macosx_10_7_x86_64.whl", hash = "sha256:b94042e5dcaa5d08cf104a54bfae614be502c6f44c9c89ad1535b2ebdaacbd4c"},
{file = "argon2_cffi-20.1.0-pp36-pypy36_pp73-win32.whl", hash = "sha256:8282b84ceb46b5b75c3a882b28856b8cd7e647ac71995e71b6705ec06fc232c3"},
{file = "argon2_cffi-20.1.0-pp37-pypy37_pp73-macosx_10_7_x86_64.whl", hash = "sha256:3aa804c0e52f208973845e8b10c70d8957c9e5a666f702793256242e9167c4e0"},
{file = "argon2_cffi-20.1.0-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:36320372133a003374ef4275fbfce78b7ab581440dfca9f9471be3dd9a522428"},
]
astroid = [
{file = "astroid-2.6.5-py3-none-any.whl", hash = "sha256:7b963d1c590d490f60d2973e57437115978d3a2529843f160b5003b721e1e925"},
@@ -3307,8 +3314,6 @@ cssselect = [
{file = "cssselect-1.1.0.tar.gz", hash = "sha256:f95f8dedd925fd8f54edb3d2dfb44c190d9d18512377d3c1e2388d16126879bc"},
]
cvxpy = [
{file = "cvxpy-1.1.12-cp35-cp35m-macosx_10_9_x86_64.whl", hash = "sha256:48e9bae36a43453659ca5d0c85e78f1eb0dfe629b8aa0f023f65aa59d0ac04d7"},
{file = "cvxpy-1.1.12-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:fe0bcb7f83b5d4deb760bf033cb72ab97c8e0770b116e08d96e9726cb1a52c01"},
{file = "cvxpy-1.1.12-cp36-cp36m-win_amd64.whl", hash = "sha256:86f8e4aa1a79482431b89aa526249d9fda04c74e04a3ec224d1175d281643d71"},
{file = "cvxpy-1.1.12-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:90b09a7361b9c614166fa673e1fe9321317df6939135330e1621b9a0bf10e3a8"},
{file = "cvxpy-1.1.12-cp37-cp37m-win_amd64.whl", hash = "sha256:084e5292f2a13133a1cd28d68f5af1df33a5119b0f1aec7cecf834eea3e2d11d"},
@@ -3316,8 +3321,6 @@ cvxpy = [
{file = "cvxpy-1.1.12-cp38-cp38-win_amd64.whl", hash = "sha256:76d04444cb50ad2840bbc72a625ac246b5eeeeb580ee20c71bec057822667738"},
{file = "cvxpy-1.1.12-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:2de5e0e75316839bc71b5df2c2db0131cee7ef06dac566c6c44dc852c091502b"},
{file = "cvxpy-1.1.12-cp39-cp39-win_amd64.whl", hash = "sha256:9fa4d033ab31855aea090e4b358017b36880390a7d0e6e97ecc5226c77eab489"},
{file = "cvxpy-1.1.12-py3.5-macosx-10.9-x86_64.egg", hash = "sha256:27ff263c80700b097d3714ba34161bd284f736f3029dfa89a95bf4c4a2801cb9"},
{file = "cvxpy-1.1.12-py3.6-macosx-10.7-x86_64.egg", hash = "sha256:7c1c5371dda78580f0892fba6776abb6e43bdb45589311c3179a057f1a984110"},
{file = "cvxpy-1.1.12-py3.6-win-amd64.egg", hash = "sha256:d2c28e0eea1b6dc70262c9ed8b63c5c1747d85c28b3ec24cbaab07583b3ad729"},
{file = "cvxpy-1.1.12-py3.7-win-amd64.egg", hash = "sha256:44d0e3d60693831ac70bdc9b2e23faf84401347bfcdef4eb5da5ae22ac57f5ff"},
{file = "cvxpy-1.1.12-py3.8-win-amd64.egg", hash = "sha256:c86f8de9a63ccbd45844a4482df8099824688b5329060f089aad1c3beb939190"},
@@ -3427,10 +3430,6 @@ entrypoints = [
{file = "entrypoints-0.3-py2.py3-none-any.whl", hash = "sha256:589f874b313739ad35be6e0cd7efde2a4e9b6fea91edcc34e58ecbb8dbe56d19"},
{file = "entrypoints-0.3.tar.gz", hash = "sha256:c70dd71abe5a8c85e55e12c19bd91ccfeec11a6e99044204511f9ed547d48451"},
]
et-xmlfile = [
{file = "et_xmlfile-1.1.0-py3-none-any.whl", hash = "sha256:a2ba85d1d6a74ef63837eed693bcb89c3f752169b0e3e7ae5b16ca5e1b3deada"},
{file = "et_xmlfile-1.1.0.tar.gz", hash = "sha256:8eb9e2bc2f8c97e37a2dc85a09ecdcdec9d8a396530a6d5a33b30b9a92da0c5c"},
]
fear-greed-index = [
{file = "fear-greed-index-0.1.3.tar.gz", hash = "sha256:5ba5286ee29b2b35147a93da353899e30abf1715decf943183399e4f057a2d87"},
{file = "fear_greed_index-0.1.3-py3-none-any.whl", hash = "sha256:0bdccdce61a408172187254dced6e1033c6126620d4694aaccc5ce09f4001921"},
@@ -3454,6 +3453,9 @@ flatbuffers = [
{file = "flatbuffers-1.12-py2.py3-none-any.whl", hash = "sha256:9e9ef47fa92625c4721036e7c4124182668dc6021d9e7c73704edd395648deb9"},
{file = "flatbuffers-1.12.tar.gz", hash = "sha256:63bb9a722d5e373701913e226135b28a6f6ac200d5cc7b4d919fa38d73b44610"},
]
fred = [
{file = "fred-3.1.tar.gz", hash = "sha256:f31327d648917694b8d15d66ca4e82a082dbb88ca027bdcc9d56738cbc836a6a"},
]
fredapi = [
{file = "fredapi-0.4.3-py3-none-any.whl", hash = "sha256:e06075592eabddadfe0635f3c59e9072c9f48647430328b4582171ea10f7df2f"},
{file = "fredapi-0.4.3.tar.gz", hash = "sha256:d9b3194fb60541991bd33f019c710d4a9580ecfb5e47efbf2d2571888a2aac02"},
@@ -3734,40 +3736,30 @@ lxml = [
{file = "lxml-4.6.3-cp27-cp27mu-manylinux1_x86_64.whl", hash = "sha256:4bff24dfeea62f2e56f5bab929b4428ae6caba2d1eea0c2d6eb618e30a71e6d4"},
{file = "lxml-4.6.3-cp35-cp35m-manylinux1_i686.whl", hash = "sha256:74f7d8d439b18fa4c385f3f5dfd11144bb87c1da034a466c5b5577d23a1d9b51"},
{file = "lxml-4.6.3-cp35-cp35m-manylinux1_x86_64.whl", hash = "sha256:f90ba11136bfdd25cae3951af8da2e95121c9b9b93727b1b896e3fa105b2f586"},
{file = "lxml-4.6.3-cp35-cp35m-manylinux2010_i686.whl", hash = "sha256:4c61b3a0db43a1607d6264166b230438f85bfed02e8cff20c22e564d0faff354"},
{file = "lxml-4.6.3-cp35-cp35m-manylinux2014_x86_64.whl", hash = "sha256:5c8c163396cc0df3fd151b927e74f6e4acd67160d6c33304e805b84293351d16"},
{file = "lxml-4.6.3-cp35-cp35m-win32.whl", hash = "sha256:f2380a6376dfa090227b663f9678150ef27543483055cc327555fb592c5967e2"},
{file = "lxml-4.6.3-cp35-cp35m-win_amd64.whl", hash = "sha256:c4f05c5a7c49d2fb70223d0d5bcfbe474cf928310ac9fa6a7c6dddc831d0b1d4"},
{file = "lxml-4.6.3-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:d2e35d7bf1c1ac8c538f88d26b396e73dd81440d59c1ef8522e1ea77b345ede4"},
{file = "lxml-4.6.3-cp36-cp36m-manylinux1_i686.whl", hash = "sha256:289e9ca1a9287f08daaf796d96e06cb2bc2958891d7911ac7cae1c5f9e1e0ee3"},
{file = "lxml-4.6.3-cp36-cp36m-manylinux1_x86_64.whl", hash = "sha256:bccbfc27563652de7dc9bdc595cb25e90b59c5f8e23e806ed0fd623755b6565d"},
{file = "lxml-4.6.3-cp36-cp36m-manylinux2010_i686.whl", hash = "sha256:d916d31fd85b2f78c76400d625076d9124de3e4bda8b016d25a050cc7d603f24"},
{file = "lxml-4.6.3-cp36-cp36m-manylinux2014_aarch64.whl", hash = "sha256:820628b7b3135403540202e60551e741f9b6d3304371712521be939470b454ec"},
{file = "lxml-4.6.3-cp36-cp36m-manylinux2014_x86_64.whl", hash = "sha256:c47ff7e0a36d4efac9fd692cfa33fbd0636674c102e9e8d9b26e1b93a94e7617"},
{file = "lxml-4.6.3-cp36-cp36m-win32.whl", hash = "sha256:5a0a14e264069c03e46f926be0d8919f4105c1623d620e7ec0e612a2e9bf1c04"},
{file = "lxml-4.6.3-cp36-cp36m-win_amd64.whl", hash = "sha256:92e821e43ad382332eade6812e298dc9701c75fe289f2a2d39c7960b43d1e92a"},
{file = "lxml-4.6.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:efd7a09678fd8b53117f6bae4fa3825e0a22b03ef0a932e070c0bdbb3a35e654"},
{file = "lxml-4.6.3-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:efac139c3f0bf4f0939f9375af4b02c5ad83a622de52d6dfa8e438e8e01d0eb0"},
{file = "lxml-4.6.3-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:0fbcf5565ac01dff87cbfc0ff323515c823081c5777a9fc7703ff58388c258c3"},
{file = "lxml-4.6.3-cp37-cp37m-manylinux2010_i686.whl", hash = "sha256:36108c73739985979bf302006527cf8a20515ce444ba916281d1c43938b8bb96"},
{file = "lxml-4.6.3-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:122fba10466c7bd4178b07dba427aa516286b846b2cbd6f6169141917283aae2"},
{file = "lxml-4.6.3-cp37-cp37m-manylinux2014_x86_64.whl", hash = "sha256:cdaf11d2bd275bf391b5308f86731e5194a21af45fbaaaf1d9e8147b9160ea92"},
{file = "lxml-4.6.3-cp37-cp37m-win32.whl", hash = "sha256:3439c71103ef0e904ea0a1901611863e51f50b5cd5e8654a151740fde5e1cade"},
{file = "lxml-4.6.3-cp37-cp37m-win_amd64.whl", hash = "sha256:4289728b5e2000a4ad4ab8da6e1db2e093c63c08bdc0414799ee776a3f78da4b"},
{file = "lxml-4.6.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:b007cbb845b28db4fb8b6a5cdcbf65bacb16a8bd328b53cbc0698688a68e1caa"},
{file = "lxml-4.6.3-cp38-cp38-manylinux1_i686.whl", hash = "sha256:76fa7b1362d19f8fbd3e75fe2fb7c79359b0af8747e6f7141c338f0bee2f871a"},
{file = "lxml-4.6.3-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:26e761ab5b07adf5f555ee82fb4bfc35bf93750499c6c7614bd64d12aaa67927"},
{file = "lxml-4.6.3-cp38-cp38-manylinux2010_i686.whl", hash = "sha256:e1cbd3f19a61e27e011e02f9600837b921ac661f0c40560eefb366e4e4fb275e"},
{file = "lxml-4.6.3-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:66e575c62792c3f9ca47cb8b6fab9e35bab91360c783d1606f758761810c9791"},
{file = "lxml-4.6.3-cp38-cp38-manylinux2014_x86_64.whl", hash = "sha256:1b38116b6e628118dea5b2186ee6820ab138dbb1e24a13e478490c7db2f326ae"},
{file = "lxml-4.6.3-cp38-cp38-win32.whl", hash = "sha256:89b8b22a5ff72d89d48d0e62abb14340d9e99fd637d046c27b8b257a01ffbe28"},
{file = "lxml-4.6.3-cp38-cp38-win_amd64.whl", hash = "sha256:2a9d50e69aac3ebee695424f7dbd7b8c6d6eb7de2a2eb6b0f6c7db6aa41e02b7"},
{file = "lxml-4.6.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:ce256aaa50f6cc9a649c51be3cd4ff142d67295bfc4f490c9134d0f9f6d58ef0"},
{file = "lxml-4.6.3-cp39-cp39-manylinux1_i686.whl", hash = "sha256:7610b8c31688f0b1be0ef882889817939490a36d0ee880ea562a4e1399c447a1"},
{file = "lxml-4.6.3-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:f8380c03e45cf09f8557bdaa41e1fa7c81f3ae22828e1db470ab2a6c96d8bc23"},
{file = "lxml-4.6.3-cp39-cp39-manylinux2010_i686.whl", hash = "sha256:3082c518be8e97324390614dacd041bb1358c882d77108ca1957ba47738d9d59"},
{file = "lxml-4.6.3-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:884ab9b29feaca361f7f88d811b1eea9bfca36cf3da27768d28ad45c3ee6f969"},
{file = "lxml-4.6.3-cp39-cp39-manylinux2014_x86_64.whl", hash = "sha256:6f12e1427285008fd32a6025e38e977d44d6382cf28e7201ed10d6c1698d2a9a"},
{file = "lxml-4.6.3-cp39-cp39-win32.whl", hash = "sha256:33bb934a044cf32157c12bfcfbb6649807da20aa92c062ef51903415c704704f"},
{file = "lxml-4.6.3-cp39-cp39-win_amd64.whl", hash = "sha256:542d454665a3e277f76954418124d67516c5f88e51a900365ed54a9806122b83"},
{file = "lxml-4.6.3.tar.gz", hash = "sha256:39b78571b3b30645ac77b95f7c69d1bffc4cf8c3b157c435a34da72e78c82468"},
@@ -4030,10 +4022,6 @@ oauthlib = [
onetimepass = [
{file = "onetimepass-1.0.1.tar.gz", hash = "sha256:a569dac076d6e3761cbc55e36952144a637ca1b075c6d509de1c1dbc5e7f6a27"},
]
openpyxl = [
{file = "openpyxl-3.0.7-py2.py3-none-any.whl", hash = "sha256:46af4eaf201a89b610fcca177eed957635f88770a5462fb6aae4a2a52b0ff516"},
{file = "openpyxl-3.0.7.tar.gz", hash = "sha256:6456a3b472e1ef0facb1129f3c6ef00713cebf62e736cd7a75bcc3247432f251"},
]
opt-einsum = [
{file = "opt_einsum-3.3.0-py3-none-any.whl", hash = "sha256:2455e59e3947d3c275477df7f5205b30635e266fe6dc300e3d9f9646bfcea147"},
{file = "opt_einsum-3.3.0.tar.gz", hash = "sha256:59f6475f77bbc37dcf7cd748519c0ec60722e91e63ca114e68821c0c54a46549"},
@@ -4254,13 +4242,9 @@ protobuf = [
{file = "protobuf-3.17.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:2ae692bb6d1992afb6b74348e7bb648a75bb0d3565a3f5eea5bec8f62bd06d87"},
{file = "protobuf-3.17.3-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:99938f2a2d7ca6563c0ade0c5ca8982264c484fdecf418bd68e880a7ab5730b1"},
{file = "protobuf-3.17.3-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:6902a1e4b7a319ec611a7345ff81b6b004b36b0d2196ce7a748b3493da3d226d"},
{file = "protobuf-3.17.3-cp38-cp38-win32.whl", hash = "sha256:59e5cf6b737c3a376932fbfb869043415f7c16a0cf176ab30a5bbc419cd709c1"},
{file = "protobuf-3.17.3-cp38-cp38-win_amd64.whl", hash = "sha256:ebcb546f10069b56dc2e3da35e003a02076aaa377caf8530fe9789570984a8d2"},
{file = "protobuf-3.17.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:4ffbd23640bb7403574f7aff8368e2aeb2ec9a5c6306580be48ac59a6bac8bde"},
{file = "protobuf-3.17.3-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:26010f693b675ff5a1d0e1bdb17689b8b716a18709113288fead438703d45539"},
{file = "protobuf-3.17.3-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:e76d9686e088fece2450dbc7ee905f9be904e427341d289acbe9ad00b78ebd47"},
{file = "protobuf-3.17.3-cp39-cp39-win32.whl", hash = "sha256:a38bac25f51c93e4be4092c88b2568b9f407c27217d3dd23c7a57fa522a17554"},
{file = "protobuf-3.17.3-cp39-cp39-win_amd64.whl", hash = "sha256:85d6303e4adade2827e43c2b54114d9a6ea547b671cb63fafd5011dc47d0e13d"},
{file = "protobuf-3.17.3-py2.py3-none-any.whl", hash = "sha256:2bfb815216a9cd9faec52b16fd2bfa68437a44b67c56bee59bc3926522ecb04e"},
{file = "protobuf-3.17.3.tar.gz", hash = "sha256:72804ea5eaa9c22a090d2803813e280fb273b62d5ae497aaf3553d141c4fdd7b"},
]

1
pyproject.toml vendored
View File

@@ -77,6 +77,7 @@ fear-greed-index = "^0.1.3"
pyEX = "^0.5.0"
charset-normalizer = "2.0.1"
sentiment-investor = "^2.0.0"
fred = "^3.1"
[tool.poetry.dev-dependencies]
pytest = "^6.2.2"

1
requirements-full.txt vendored
View File

@@ -48,6 +48,7 @@ ffn==0.3.6; python_version >= "2.7" and python_full_version < "3.0.0" or python_
finviz==1.4.2
finvizfinance==0.9.9; python_version >= "3.5"
flatbuffers==1.12
fred==3.1
fredapi==0.4.3
frozendict==2.0.3; python_version >= "3.6"
fundamentalanalysis==0.2.11

1
requirements.txt vendored
View File

@@ -44,6 +44,7 @@ fear-greed-index==0.1.3; python_full_version >= "3.6.8" and python_full_version
ffn==0.3.6; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0"
finviz==1.4.2
finvizfinance==0.9.9; python_version >= "3.5"
fred==3.1
fredapi==0.4.3
frozendict==2.0.3; python_version >= "3.6"
fundamentalanalysis==0.2.11

115
terminal.py
View File

@@ -20,18 +20,10 @@ from gamestonk_terminal.menu import session
from gamestonk_terminal import feature_flags as gtff
from gamestonk_terminal import config_terminal
from gamestonk_terminal.stocks import stocks_controller
from gamestonk_terminal.cryptocurrency import crypto_controller
from gamestonk_terminal.economy import economy_controller
from gamestonk_terminal.options import options_controller
# from gamestonk_terminal.etf import etf_controller
from gamestonk_terminal.forex import forex_controller
from gamestonk_terminal.resources import resources_controller
from gamestonk_terminal.portfolio import portfolio_controller
# pylint: disable=too-many-public-methods
# pylint: disable=too-many-public-methods,import-outside-toplevel
class TerminalController:
@@ -166,18 +158,26 @@ What do you want to do?
# MENUS
def call_stocks(self, _):
"""Process stocks command"""
from gamestonk_terminal.stocks import stocks_controller
return stocks_controller.menu()
def call_crypto(self, _):
"""Process crypto command"""
from gamestonk_terminal.cryptocurrency import crypto_controller
return crypto_controller.menu()
def call_economy(self, _):
"""Process econ command"""
from gamestonk_terminal.economy import economy_controller
return economy_controller.menu()
def call_options(self, _):
"""Process op command"""
from gamestonk_terminal.options import options_controller
return options_controller.menu()
def call_etf(self, _):
@@ -187,14 +187,20 @@ What do you want to do?
def call_forex(self, _):
"""Process fx command"""
from gamestonk_terminal.forex import forex_controller
return forex_controller.menu()
def call_resources(self, _):
"""Process resources command"""
from gamestonk_terminal.resources import resources_controller
return resources_controller.menu()
def call_portfolio(self, _):
"""Process portfolio command"""
from gamestonk_terminal.portfolio import portfolio_controller
return portfolio_controller.menu()
@@ -202,72 +208,75 @@ def terminal():
"""Terminal Menu"""
bootup()
process_input = False
t_controller = TerminalController()
if config_terminal.DEFAULT_CONTEXT:
if config_terminal.DEFAULT_CONTEXT in t_controller.CHOICES_MENUS:
try:
print("")
t_controller.switch(config_terminal.DEFAULT_CONTEXT.lower())
process_input = t_controller.switch(
config_terminal.DEFAULT_CONTEXT.lower()
)
except SystemExit:
print("")
else:
print("\nInvalid DEFAULT_CONTEXT config selected!", "\n")
t_controller.print_help()
parsed_stdin = False
if not process_input:
t_controller.print_help()
parsed_stdin = False
while True:
if gtff.ENABLE_QUICK_EXIT:
print("Quick exit enabled")
break
while True:
if gtff.ENABLE_QUICK_EXIT:
print("Quick exit enabled")
break
# Get input command from stdin or user
if not parsed_stdin and len(sys.argv) > 1:
an_input = " ".join(sys.argv[1:])
print(f"{get_flair()}> {an_input}")
parsed_stdin = True
# Get input command from stdin or user
if not parsed_stdin and len(sys.argv) > 1:
an_input = " ".join(sys.argv[1:])
print(f"{get_flair()}> {an_input}")
parsed_stdin = True
elif session and gtff.USE_PROMPT_TOOLKIT:
an_input = session.prompt(
f"{get_flair()}> ", completer=t_controller.completer
)
elif session and gtff.USE_PROMPT_TOOLKIT:
an_input = session.prompt(
f"{get_flair()}> ", completer=t_controller.completer
)
else:
an_input = input(f"{get_flair()}> ")
else:
an_input = input(f"{get_flair()}> ")
# Is command empty
if not an_input:
print("")
continue
# Is command empty
if not an_input:
print("")
continue
# Process list of commands selected by user
try:
process_input = t_controller.switch(an_input)
# None - Keep loop
# True - Quit or Reset based on flag
# False - Keep loop and show help menu
# Process list of commands selected by user
try:
process_input = t_controller.switch(an_input)
# None - Keep loop
# True - Quit or Reset based on flag
# False - Keep loop and show help menu
if process_input is not None:
# Quit terminal
if process_input:
break
if process_input is not None:
# Quit terminal
if process_input:
break
t_controller.print_help()
t_controller.print_help()
except SystemExit:
print("The command selected doesn't exist\n")
continue
except SystemExit:
print("The command selected doesn't exist\n")
continue
if not gtff.ENABLE_QUICK_EXIT:
# Check if the user wants to reset application
if an_input == "reset" or t_controller.update_succcess:
ret_code = reset()
if ret_code != 0:
if not gtff.ENABLE_QUICK_EXIT:
# Check if the user wants to reset application
if an_input == "reset" or t_controller.update_succcess:
ret_code = reset()
if ret_code != 0:
print_goodbye()
else:
print_goodbye()
else:
print_goodbye()
if __name__ == "__main__":

36
tests/test_fred_fred_view.py
View File

@@ -5,27 +5,37 @@ from io import StringIO
import pandas as pd
# pylint: disable=unused-import
from gamestonk_terminal.economy.fred_view import display_fred # noqa: F401
from gamestonk_terminal.economy.fred_view import display_series # noqa: F401
fred_data_mock = """
,GDP
2019-01-01,21115.309
2019-04-01,21329.877
2019-07-01,21540.325
2019-10-01,21747.394
2020-01-01,21561.139
2020-04-01,19520.114
2020-07-01,21170.252
2020-10-01,21494.731
2021-01-01,22048.894
For 'gdp', series IDs found: GDP, GDPC1, M2V, GFDEGDQ188S, PAYEMS.
GDP
---
Date
2019-01-01 21001.591
2019-04-01 21289.268
2019-07-01 21505.012
2019-10-01 21694.458
2020-01-01 21481.367
2020-04-01 19477.444
2020-07-01 21138.574
2020-10-01 21477.597
2021-01-01 22038.226
2021-04-01 22722.581
"""
class TestFredFredView(unittest.TestCase):
@mock.patch("gamestonk_terminal.economy.fred_view.Fred.get_series")
@mock.patch("gamestonk_terminal.economy.fred_model.get_series_data")
def test_display_fred(self, mock_get_series):
fred_data = pd.read_csv(StringIO(fred_data_mock), header=0, index_col=0)
mock_get_series.return_value = fred_data
display_fred(["-t"], "gdp")
display_series(
series="gdp",
start_date="2019-01-01",
raw=True,
export="",
)