Anson/Simple-Stock-Bot
1
0
Fork 0
mirror of https://gitlab.com/simple-stock-bots/simple-stock-bot.git synced 2025-06-16 07:16:40 +00:00
Code Releases Activity

formatting

Browse Source
This commit is contained in:
Anson 2023-11-30 21:53:06 -07:00
parent 1fe7fe8c9c
commit ec516db22f
23 changed files with 772 additions and 784 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
common/MarketData.py
View File

@ -45,13 +45,9 @@ class MarketData:
self.MARKETDATA_TOKEN = ""
except KeyError:
self.MARKETDATA_TOKEN = ""
log.warning(
"Starting without an MarketData.app Token will not allow you to get market data!"
)
log.warning("Starting without an MarketData.app Token will not allow you to get market data!")
log.warning("Use this affiliate link so that the bot can stay free:")
log.warning(
"https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=repo"
)
log.warning("https://dashboard.marketdata.app/marketdata/aff/go/misterbiggs?keyword=repo")
if self.MARKETDATA_TOKEN != "":
schedule.every().day.do(self.clear_charts)
@ -153,7 +149,9 @@ class MarketData:
statusJSON = status.json()
if statusJSON["status"] == "ok":
return f"CoinGecko API responded that it was OK with a {status.status_code} in {status.elapsed.total_seconds()} seconds."
return (
f"CoinGecko API responded that it was OK with a {status.status_code} in {status.elapsed.total_seconds()} seconds."
)
else:
return f"MarketData.app is currently reporting the following status: {statusJSON['status']}"
@ -323,9 +321,7 @@ class MarketData:
options_data["underlying"] = "$" + options_data["underlying"]
options_data["updated"] = humanize.naturaltime(
dt.datetime.now() - dt.datetime.fromtimestamp(options_data["updated"])
)
options_data["updated"] = humanize.naturaltime(dt.datetime.now() - dt.datetime.fromtimestamp(options_data["updated"]))
options_data["expiration"] = humanize.naturaltime(
dt.datetime.now() - dt.datetime.fromtimestamp(options_data["expiration"])

24
common/cg_Crypto.py
View File

@ -37,9 +37,7 @@ class cg_Crypto:
# Make sure API returned a proper status code
if resp.status_code == 429:
log.warning(
f"CoinGecko returned 429 - Too Many Requests for endpoint: {endpoint}. Sleeping and trying again."
)
log.warning(f"CoinGecko returned 429 - Too Many Requests for endpoint: {endpoint}. Sleeping and trying again.")
time.sleep(10)
return self.get(endpoint=endpoint, params=params, timeout=timeout)
@ -59,9 +57,7 @@ class cg_Crypto:
def symbol_id(self, symbol) -> str:
try:
return self.symbol_list[self.symbol_list["symbol"] == symbol]["id"].values[
0
]
return self.symbol_list[self.symbol_list["symbol"] == symbol]["id"].values[0]
except KeyError:
return ""
@ -72,9 +68,7 @@ class cg_Crypto:
# Removes all binance-peg symbols
symbols = symbols[~symbols["id"].str.contains("binance-peg")]
symbols["description"] = (
"$$" + symbols["symbol"].str.upper() + ": " + symbols["name"]
)
symbols["description"] = "$$" + symbols["symbol"].str.upper() + ": " + symbols["name"]
symbols = symbols[["id", "symbol", "name", "description"]]
symbols["type_id"] = "$$" + symbols["symbol"]
@ -95,7 +89,9 @@ class cg_Crypto:
try:
status.raise_for_status()
return f"CoinGecko API responded that it was OK with a {status.status_code} in {status.elapsed.total_seconds()} seconds."
return (
f"CoinGecko API responded that it was OK with a {status.status_code} in {status.elapsed.total_seconds()} seconds."
)
except r.HTTPError:
return f"CoinGecko API returned an error code {status.status_code} in {status.elapsed.total_seconds()} seconds."
@ -165,9 +161,7 @@ class cg_Crypto:
f"/coins/{symbol.id}/ohlc",
params={"vs_currency": self.vs_currency, "days": 1},
):
df = pd.DataFrame(
resp, columns=["Date", "Open", "High", "Low", "Close"]
).dropna()
df = pd.DataFrame(resp, columns=["Date", "Open", "High", "Low", "Close"]).dropna()
df["Date"] = pd.to_datetime(df["Date"], unit="ms")
df = df.set_index("Date")
return df
@ -193,9 +187,7 @@ class cg_Crypto:
f"/coins/{symbol.id}/ohlc",
params={"vs_currency": self.vs_currency, "days": 30},
):
df = pd.DataFrame(
resp, columns=["Date", "Open", "High", "Low", "Close"]
).dropna()
df = pd.DataFrame(resp, columns=["Date", "Open", "High", "Low", "Close"]).dropna()
df["Date"] = pd.to_datetime(df["Date"], unit="ms")
df = df.set_index("Date")
return df