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government menu to have house and senate

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This commit is contained in:
didier
2021-05-16 02:29:29 +01:00
parent 516803dbd2
commit 29a9c3ef97
3 changed files with 194 additions and 108 deletions
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56
gamestonk_terminal/government/gov_controller.py
View File

@@ -23,6 +23,14 @@ class GovController:
"buy_congress",
"sell_congress",
"congress",
"last_senate",
"buy_senate",
"sell_senate",
"senate",
"last_house",
"buy_house",
"sell_house",
"house",
]
def __init__(
@@ -50,10 +58,18 @@ class GovController:
print(" last_congress last congress trading")
print(" buy_congress top buy congress tickers")
print(" sell_congress top sell congress tickers")
print(" last_senate last senate trading")
print(" buy_senate top buy senate tickers")
print(" sell_senate top sell senate tickers")
print(" last_house last house trading")
print(" buy_house top buy house tickers")
print(" sell_house top sell house tickers")
print("")
if self.ticker:
print(f"Ticker: {self.ticker}")
print(" congress congress trades on the ticker")
print(" senate senate trades on the ticker")
print(" house house trades on the ticker")
print("")
return
@@ -87,19 +103,51 @@ class GovController:
def call_last_congress(self, other_args: List[str]):
"""Process last_congress command"""
quiverquant_view.last_congress(other_args)
quiverquant_view.last_government(other_args, "congress")
def call_buy_congress(self, other_args: List[str]):
"""Process buy_congress command"""
quiverquant_view.buy_congress(other_args)
quiverquant_view.buy_government(other_args, "congress")
def call_sell_congress(self, other_args: List[str]):
"""Process sell_congress command"""
quiverquant_view.sell_congress(other_args)
quiverquant_view.sell_government(other_args, "congress")
def call_congress(self, other_args: List[str]):
"""Process congress command"""
quiverquant_view.congress(other_args, self.ticker)
quiverquant_view.government(other_args, self.ticker, "congress")
def call_last_senate(self, other_args: List[str]):
"""Process last_senate command"""
quiverquant_view.last_government(other_args, "senate")
def call_buy_senate(self, other_args: List[str]):
"""Process buy_senate command"""
quiverquant_view.buy_government(other_args, "senate")
def call_sell_senate(self, other_args: List[str]):
"""Process sell_senate command"""
quiverquant_view.sell_government(other_args, "senate")
def call_senate(self, other_args: List[str]):
"""Process senate command"""
quiverquant_view.government(other_args, self.ticker, "senate")
def call_last_house(self, other_args: List[str]):
"""Process last_house command"""
quiverquant_view.last_government(other_args, "house")
def call_buy_house(self, other_args: List[str]):
"""Process buy_house command"""
quiverquant_view.buy_government(other_args, "house")
def call_sell_house(self, other_args: List[str]):
"""Process sell_house command"""
quiverquant_view.sell_government(other_args, "house")
def call_house(self, other_args: List[str]):
"""Process house command"""
quiverquant_view.government(other_args, self.ticker, "house")
def menu(ticker: str):

34
gamestonk_terminal/government/quiverquant_model.py
View File

@@ -5,11 +5,13 @@ import pandas as pd
API_QUIVERQUANT_KEY = "5cd2a65e96d0486efbe926a7cdbc1e8d8ab6c7b3"
def get_congress_trading(ticker: str = "") -> pd.DataFrame:
"""Returns the most recent transactions by members of U.S. Congress
def get_government_trading(type: str, ticker: str = "") -> pd.DataFrame:
"""Returns the most recent transactions by members of government
Parameters
----------
type: str
Type of government data between: Congress, Senate and House
ticker : str
Ticker to get congress trading data from
@@ -19,10 +21,28 @@ def get_congress_trading(ticker: str = "") -> pd.DataFrame:
Most recent transactions by members of U.S. Congress
"""
if ticker:
url = f"https://api.quiverquant.com/beta/historical/congresstrading/{ticker}"
if type == "congress":
if ticker:
url = (
f"https://api.quiverquant.com/beta/historical/congresstrading/{ticker}"
)
else:
url = "https://api.quiverquant.com/beta/live/congresstrading"
elif type == "senate":
if ticker:
url = f"https://api.quiverquant.com/beta/historical/senatetrading/{ticker}"
else:
url = "https://api.quiverquant.com/beta/live/senatetrading"
elif type == "house":
if ticker:
url = f"https://api.quiverquant.com/beta/historical/housetrading/{ticker}"
else:
url = "https://api.quiverquant.com/beta/live/housetrading"
else:
url = "https://api.quiverquant.com/beta/live/congresstrading"
return pd.DataFrame()
headers = {
"accept": "application/json",
@@ -31,6 +51,8 @@ def get_congress_trading(ticker: str = "") -> pd.DataFrame:
}
response = requests.get(url, headers=headers)
if response.status_code == 200:
return pd.DataFrame(response.json())
return pd.DataFrame(response.json()).rename(
columns={"Date": "TransactionDate", "Senator": "Representative"}
)
return pd.DataFrame()

212
gamestonk_terminal/government/quiverquant_view.py
View File

@@ -14,20 +14,20 @@ from gamestonk_terminal.config_plot import PLOT_DPI
from gamestonk_terminal import feature_flags as gtff
def last_congress(other_args: List[str]):
"""Last congress trading
def last_government(other_args: List[str], type: str):
"""Last government trading
Parameters
----------
other_args : List[str]
Command line arguments to be processed with argparse
type: str
Type of government data between: congress, senate and house
"""
parser = argparse.ArgumentParser(
add_help=False,
prog="last_congress",
description="""
Last congress trading. [Source: www.quiverquant.com]
""",
prog="last_" + type,
description=f"Last {type} trading. [Source: www.quiverquant.com]",
)
parser.add_argument(
"-p",
@@ -45,7 +45,7 @@ def last_congress(other_args: List[str]):
dest="representative",
type=str,
default="",
help="Congress representative",
help="Representative",
)
try:
@@ -57,72 +57,83 @@ def last_congress(other_args: List[str]):
if not ns_parser:
return
df_congress = quiverquant_model.get_congress_trading()
df_gov = quiverquant_model.get_government_trading(type)
if df_congress.empty:
print("No congress trading data found\n")
if df_gov.empty:
print(f"No {type} trading data found\n")
return
df_congress = df_congress.sort_values("TransactionDate", ascending=False)
df_gov = df_gov.sort_values("TransactionDate", ascending=False)
df_congress = df_congress[
df_congress["TransactionDate"].isin(
df_congress["TransactionDate"].unique()[
: ns_parser.past_transactions_days
]
df_gov = df_gov[
df_gov["TransactionDate"].isin(
df_gov["TransactionDate"].unique()[: ns_parser.past_transactions_days]
)
]
df_congress = df_congress[
[
"TransactionDate",
"Ticker",
"Representative",
"Transaction",
"House",
"Range",
"ReportDate",
]
].rename(
columns={"TransactionDate": "Transaction Date", "ReportDate": "Report Date"}
)
if type == "congress":
df_gov = df_gov[
[
"TransactionDate",
"Ticker",
"Representative",
"Transaction",
"Range",
"House",
"ReportDate",
]
].rename(
columns={
"TransactionDate": "Transaction Date",
"ReportDate": "Report Date",
}
)
else:
df_gov = df_gov[
[
"TransactionDate",
"Ticker",
"Representative",
"Transaction",
"Range",
]
].rename(columns={"TransactionDate": "Transaction Date"})
if ns_parser.representative:
df_congress_rep = df_congress[
df_congress["Representative"].str.split().str[0]
== ns_parser.representative
df_gov_rep = df_gov[
df_gov["Representative"].str.split().str[0] == ns_parser.representative
]
if df_congress_rep.empty:
if df_gov_rep.empty:
print(
f"No representative {ns_parser.representative} found in the past {ns_parser.past_transactions_days}"
f" days. The following are available: "
f"{', '.join(df_congress['Representative'].str.split().str[0].unique())}"
f"{', '.join(df_gov['Representative'].str.split().str[0].unique())}"
)
else:
print(df_congress_rep.to_string(index=False))
print(df_gov_rep.to_string(index=False))
else:
print(df_congress.to_string(index=False))
print(df_gov.to_string(index=False))
print("")
except Exception as e:
print(e, "\n")
def buy_congress(other_args: List[str]):
"""Top buy congress trading
def buy_government(other_args: List[str], type: str):
"""Top buy government trading
Parameters
----------
other_args : List[str]
Command line arguments to be processed with argparse
type: str
Type of government data between: congress, senate and house
"""
parser = argparse.ArgumentParser(
add_help=False,
prog="buy_congress",
description="""
Top buy congress trading. [Source: www.quiverquant.com]
""",
prog="buy_" + type,
description=f"Top buy {type} trading. [Source: www.quiverquant.com]",
)
parser.add_argument(
"-p",
@@ -148,49 +159,49 @@ def buy_congress(other_args: List[str]):
if not ns_parser:
return
df_congress = quiverquant_model.get_congress_trading()
df_gov = quiverquant_model.get_government_trading(type)
if df_congress.empty:
print("No congress trading data found\n")
if df_gov.empty:
print(f"No {type} trading data found\n")
return
df_congress = df_congress.sort_values("TransactionDate", ascending=False)
df_gov = df_gov.sort_values("TransactionDate", ascending=False)
start_date = datetime.now() - timedelta(
days=ns_parser.past_transactions_months * 30
)
df_congress["TransactionDate"] = pd.to_datetime(df_congress["TransactionDate"])
df_gov["TransactionDate"] = pd.to_datetime(df_gov["TransactionDate"])
df_congress = df_congress[df_congress["TransactionDate"] > start_date].dropna()
df_gov = df_gov[df_gov["TransactionDate"] > start_date].dropna()
df_congress["min"] = df_congress["Range"].apply(
df_gov["min"] = df_gov["Range"].apply(
lambda x: x.split("-")[0].strip("$").replace(",", "").strip()
)
df_congress["max"] = df_congress["Range"].apply(
df_gov["max"] = df_gov["Range"].apply(
lambda x: x.split("-")[1].replace(",", "").strip().strip("$")
if "-" in x
else x.strip("$").replace(",", "")
)
df_congress["lower"] = df_congress[["min", "max", "Transaction"]].apply(
df_gov["lower"] = df_gov[["min", "max", "Transaction"]].apply(
lambda x: float(x["min"])
if x["Transaction"] == "Purchase"
else -float(x["max"]),
axis=1,
)
df_congress["upper"] = df_congress[["min", "max", "Transaction"]].apply(
df_gov["upper"] = df_gov[["min", "max", "Transaction"]].apply(
lambda x: float(x["max"])
if x["Transaction"] == "Purchase"
else -float(x["min"]),
axis=1,
)
df_congress = df_congress.sort_values("TransactionDate", ascending=True)
df_gov = df_gov.sort_values("TransactionDate", ascending=True)
plt.figure(figsize=plot_autoscale(), dpi=PLOT_DPI)
df_congress.groupby("Ticker")["upper"].sum().sort_values(ascending=False).head(
df_gov.groupby("Ticker")["upper"].sum().sort_values(ascending=False).head(
n=ns_parser.top_num
).plot(kind="bar", rot=0)
plt.ylabel("Amount [$]")
@@ -209,20 +220,20 @@ def buy_congress(other_args: List[str]):
print(e, "\n")
def sell_congress(other_args: List[str]):
"""Top sell congress trading
def sell_government(other_args: List[str], type: str):
"""Top sell government trading
Parameters
----------
other_args : List[str]
Command line arguments to be processed with argparse
type: str
Type of government data between: congress, senate and house
"""
parser = argparse.ArgumentParser(
add_help=False,
prog="sell_congress",
description="""
Top sell congress trading. [Source: www.quiverquant.com]
""",
prog="sell_" + type,
description=f"Top sell {type} trading. [Source: www.quiverquant.com]",
)
parser.add_argument(
"-p",
@@ -248,49 +259,49 @@ def sell_congress(other_args: List[str]):
if not ns_parser:
return
df_congress = quiverquant_model.get_congress_trading()
df_gov = quiverquant_model.get_government_trading(type)
if df_congress.empty:
print("No congress trading data found\n")
if df_gov.empty:
print(f"No {type} trading data found\n")
return
df_congress = df_congress.sort_values("TransactionDate", ascending=False)
df_gov = df_gov.sort_values("TransactionDate", ascending=False)
start_date = datetime.now() - timedelta(
days=ns_parser.past_transactions_months * 30
)
df_congress["TransactionDate"] = pd.to_datetime(df_congress["TransactionDate"])
df_gov["TransactionDate"] = pd.to_datetime(df_gov["TransactionDate"])
df_congress = df_congress[df_congress["TransactionDate"] > start_date].dropna()
df_gov = df_gov[df_gov["TransactionDate"] > start_date].dropna()
df_congress["min"] = df_congress["Range"].apply(
df_gov["min"] = df_gov["Range"].apply(
lambda x: x.split("-")[0].strip("$").replace(",", "").strip()
)
df_congress["max"] = df_congress["Range"].apply(
df_gov["max"] = df_gov["Range"].apply(
lambda x: x.split("-")[1].replace(",", "").strip().strip("$")
if "-" in x
else x.strip("$").replace(",", "")
)
df_congress["lower"] = df_congress[["min", "max", "Transaction"]].apply(
df_gov["lower"] = df_gov[["min", "max", "Transaction"]].apply(
lambda x: float(x["min"])
if x["Transaction"] == "Purchase"
else -float(x["max"]),
axis=1,
)
df_congress["upper"] = df_congress[["min", "max", "Transaction"]].apply(
df_gov["upper"] = df_gov[["min", "max", "Transaction"]].apply(
lambda x: float(x["max"])
if x["Transaction"] == "Purchase"
else -float(x["min"]),
axis=1,
)
df_congress = df_congress.sort_values("TransactionDate", ascending=True)
df_gov = df_gov.sort_values("TransactionDate", ascending=True)
plt.figure(figsize=plot_autoscale(), dpi=PLOT_DPI)
df_congress.groupby("Ticker")["lower"].sum().sort_values().abs().head(
df_gov.groupby("Ticker")["lower"].sum().sort_values().abs().head(
n=ns_parser.top_num
).plot(kind="bar", rot=0)
plt.ylabel("Amount [$]")
@@ -310,29 +321,34 @@ def sell_congress(other_args: List[str]):
print(e, "\n")
def plot_congress(congress: pd.DataFrame, ticker: str):
"""Plot congress trading
def plot_government(government: pd.DataFrame, ticker: str, type: str):
"""Plot government trading
Parameters
----------
other_args : List[str]
Command line arguments to be processed with argparse
ticker: str
Ticker to plot congress trading
Ticker to plot government trading
type: str
Type of government data between: congress, senate and house
"""
plt.figure(figsize=plot_autoscale(), dpi=PLOT_DPI)
plt.gca().fill_between(
congress["TransactionDate"].unique(),
congress.groupby("TransactionDate")["lower"].sum().values / 1000,
congress.groupby("TransactionDate")["upper"].sum().values / 1000,
government["TransactionDate"].unique(),
government.groupby("TransactionDate")["lower"].sum().values / 1000,
government.groupby("TransactionDate")["upper"].sum().values / 1000,
)
plt.xlim(
[congress["TransactionDate"].values[0], congress["TransactionDate"].values[-1]]
[
government["TransactionDate"].values[0],
government["TransactionDate"].values[-1],
]
)
plt.grid()
plt.title(f"Congress trading on {ticker}")
plt.title(f"{type.capitalize()} trading on {ticker}")
plt.xlabel("Date")
plt.ylabel("Amount [1k $]")
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter("%Y/%m/%d"))
@@ -344,8 +360,8 @@ def plot_congress(congress: pd.DataFrame, ticker: str):
plt.show()
def congress(other_args: List[str], ticker: str):
"""Congress trading
def government(other_args: List[str], ticker: str, type: str):
"""Government trading
Parameters
----------
@@ -353,13 +369,13 @@ def congress(other_args: List[str], ticker: str):
Command line arguments to be processed with argparse
ticker: str
Ticker to get congress trading data from
type: str
Type of government data between: congress, senate and house
"""
parser = argparse.ArgumentParser(
add_help=False,
prog="congress",
description="""
Congress trading. [Source: www.quiverquant.com]
""",
prog=type,
description=f"{type} trading. [Source: www.quiverquant.com]",
)
parser.add_argument(
"-p",
@@ -381,47 +397,47 @@ def congress(other_args: List[str], ticker: str):
if not ns_parser:
return
df_congress = quiverquant_model.get_congress_trading(ticker)
df_gov = quiverquant_model.get_government_trading(type, ticker)
if df_congress.empty:
print("No congress trading data found\n")
if df_gov.empty:
print(f"No {type} trading data found\n")
return
df_congress = df_congress.sort_values("TransactionDate", ascending=False)
df_gov = df_gov.sort_values("TransactionDate", ascending=False)
start_date = datetime.now() - timedelta(
days=ns_parser.past_transactions_months * 30
)
df_congress["TransactionDate"] = pd.to_datetime(df_congress["TransactionDate"])
df_gov["TransactionDate"] = pd.to_datetime(df_gov["TransactionDate"])
df_congress = df_congress[df_congress["TransactionDate"] > start_date]
df_gov = df_gov[df_gov["TransactionDate"] > start_date]
df_congress["min"] = df_congress["Range"].apply(
df_gov["min"] = df_gov["Range"].apply(
lambda x: x.split("-")[0].strip("$").replace(",", "").strip()
)
df_congress["max"] = df_congress["Range"].apply(
df_gov["max"] = df_gov["Range"].apply(
lambda x: x.split("-")[1].replace(",", "").strip().strip("$")
if "-" in x
else x.strip("$").replace(",", "")
)
df_congress["lower"] = df_congress[["min", "max", "Transaction"]].apply(
df_gov["lower"] = df_gov[["min", "max", "Transaction"]].apply(
lambda x: int(x["min"])
if x["Transaction"] == "Purchase"
else -int(x["max"]),
axis=1,
)
df_congress["upper"] = df_congress[["min", "max", "Transaction"]].apply(
df_gov["upper"] = df_gov[["min", "max", "Transaction"]].apply(
lambda x: int(x["max"])
if x["Transaction"] == "Purchase"
else -int(x["min"]),
axis=1,
)
df_congress = df_congress.sort_values("TransactionDate", ascending=True)
df_gov = df_gov.sort_values("TransactionDate", ascending=True)
plot_congress(df_congress, ticker)
plot_government(df_gov, ticker, type)
print("")