Add stocksera source to stocks/dps/ctb (#2896)

* Got stocksera source working

* Added fixes

* Removed prints

* Updated documentation

* Fixed pytest

* Added tests

Co-authored-by: James Maslek <jmaslek11@gmail.com>
This commit is contained in:
Colin Delahunty
2022-10-20 00:24:48 +02:00
committed by GitHub
parent 66f7d25edb
commit 52dd7a1f66
20 changed files with 1147 additions and 86 deletions

View File

@@ -181,3 +181,6 @@ API_EODHD_KEY = os.getenv("OPENBB_API_EODHD_KEY") or "REPLACE_ME"
# https://tokenterminal.com
API_TOKEN_TERMINAL_KEY = os.getenv("OPENBB_API_TOKEN_TERMINAL_KEY") or "REPLACE_ME"
# https://stocksera.pythonanywhere.com/accounts/developers
API_STOCKSERA_KEY = os.getenv("OPENBB_API_STOCKSERA_KEY") or "REPLACE_ME"

View File

@@ -81,6 +81,8 @@ class KeysController(BaseController): # pylint: disable=too-many-public-methods
elif status_msg == str(keys_model.KeyStatus.NOT_DEFINED):
c = "grey30"
if status_msg is None:
status_msg = str(keys_model.KeyStatus.NOT_DEFINED)
mt.add_raw(
f" [cmds]{cmd_name}[/cmds] {(20 - len(cmd_name)) * ' '}"
f" [{c}] {api_name} {(25 - len(api_name)) * ' '} {translate(status_msg)} [/{c}]\n"
@@ -1114,3 +1116,33 @@ class KeysController(BaseController): # pylint: disable=too-many-public-methods
self.status_dict["tokenterminal"] = keys_model.set_tokenterminal_key(
key=ns_parser.key, persist=True, show_output=True
)
@log_start_end(log=logger)
def call_stocksera(self, other_args: List[str]):
"""Process stocksera command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="stocksera",
description="Set Stocksera API key.",
)
parser.add_argument(
"-k",
"--key",
type=str,
dest="key",
help="key",
)
if not other_args:
console.print(
"For your API Key, https://stocksera.pythonanywhere.com/accounts/developers\n"
)
return
if other_args and "-" not in other_args[0][0]:
other_args.insert(0, "-k")
ns_parser = parse_simple_args(parser, other_args)
if ns_parser:
self.status_dict["stocksera"] = keys_model.set_stocksera_key(
key=ns_parser.key, persist=True, show_output=True
)

View File

@@ -15,6 +15,7 @@ import binance
import pandas as pd
import quandl
import requests
import stocksera
from prawcore.exceptions import ResponseException
import praw
import pyEX
@@ -80,6 +81,7 @@ API_DICT: Dict = {
"santiment": "SANTIMENT",
"tokenterminal": "TOKEN_TERMINAL",
"shroom": "SHROOM",
"stocksera": "STOCKSERA",
}
@@ -2106,3 +2108,57 @@ def check_tokenterminal_key(show_output: bool = False) -> str:
console.print(status.colorize() + "\n")
return str(status)
def set_stocksera_key(key: str, persist: bool = False, show_output: bool = False):
"""Set Stocksera key.
Parameters
----------
key: str
API key
persist: bool
If False, api key change will be contained to where it was changed. For example, Jupyter notebook.
If True, api key change will be global, i.e. it will affect terminal environment variables.
By default, False.
show_output: bool
Display status string or not. By default, False.
Returns
-------
status: str
"""
set_key("OPENBB_API_STOCKSERA_KEY", key, persist)
return check_stocksera_key(show_output)
def check_stocksera_key(show_output: bool = False):
"""Check Stocksera key
Parameters
----------
show_output: bool
Display status string or not. By default, False.
Returns
-------
status: str
"""
if cfg.API_STOCKSERA_KEY == "REPLACE_ME":
logger.info("Stocksera key not defined")
status = KeyStatus.NOT_DEFINED
else:
client = stocksera.Client(api_key=cfg.API_STOCKSERA_KEY)
try:
client.borrowed_shares(ticker="AAPL")
logger.info("Stocksera key defined, test passed")
status = KeyStatus.DEFINED_TEST_PASSED
except Exception as _: # noqa: F841
logger.warning("Stocksera key defined, test failed")
status = KeyStatus.DEFINED_TEST_FAILED
if show_output:
console.print(status.colorize() + "\n")
return str(status)

View File

@@ -102,7 +102,8 @@
"dpotc": ["FINRA"],
"ftd": ["SEC"],
"spos": ["Stockgrid"],
"psi": ["Stockgrid", "Quandl"]
"psi": ["Stockgrid", "Quandl"],
"ctb": ["ibkr", "stocksera"]
},
"scr": {
"view": [],

View File

@@ -226,7 +226,7 @@ en:
stocks/sia/ca: take these to comparison analysis menu
stocks/dps/load: load a specific stock ticker for analysis
stocks/dps/shorted: show most shorted stocks
stocks/dps/ctb: stocks with highest cost to borrow
stocks/dps/ctb: cost to borrow of stocks
stocks/dps/hsi: show top high short interest stocks of over 20% ratio
stocks/dps/prom: promising tickers based on dark pool shares regression
stocks/dps/pos: dark pool short position

View File

@@ -2,6 +2,7 @@ stocks
dps
shorted
ctb
ctb -source stocksera
hsi
pos
sidtc

View File

@@ -30,6 +30,7 @@ from openbb_terminal.stocks.dark_pool_shorts import (
stockgrid_view,
yahoofinance_view,
ibkr_view,
stocksera_view,
)
logger = logging.getLogger(__name__)
@@ -213,7 +214,7 @@ class DarkPoolShortsController(StockBaseController):
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="ctb",
description="Print stocks with highest cost to borrow. [Source: Interactive Broker]",
description="Show cost to borrow of stocks. [Source: Stocksera/Interactive Broker]",
)
parser.add_argument(
"-n",
@@ -222,18 +223,28 @@ class DarkPoolShortsController(StockBaseController):
dest="number",
type=check_int_range(1, 10000),
default=20,
help="Number of stocks with high cost to borrow to retrieve.",
help="Number of records to retrieve.",
)
parser.add_argument(
"--raw",
action="store_true",
default=False,
dest="raw",
help="Print raw data.",
)
if other_args and "-" not in other_args[0][0]:
other_args.insert(0, "-l")
ns_parser = self.parse_known_args_and_warn(
parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED
)
if ns_parser:
ibkr_view.display_cost_to_borrow(
limit=ns_parser.number,
export=ns_parser.export,
)
if ns_parser.source == "ibkr":
ibkr_view.display_cost_to_borrow(
limit=ns_parser.number,
export=ns_parser.export,
)
else:
stocksera_view.cost_to_borrow(
self.ticker, limit=ns_parser.number, raw=ns_parser.raw
)
@log_start_end(log=logger)
def call_hsi(self, other_args: List[str]):

View File

@@ -0,0 +1,43 @@
"""Stocksera model"""
__docformat__ = "numpy"
import logging
import stocksera
import pandas as pd
from stocksera.exceptions import StockseraRequestException
from openbb_terminal import config_terminal as cfg
from openbb_terminal.decorators import log_start_end
from openbb_terminal.rich_config import console
logger = logging.getLogger(__name__)
@log_start_end(log=logger)
def get_cost_to_borrow(symbol: str) -> pd.DataFrame:
"""Get cost to borrow of stocks [Source: Stocksera]
Parameters
----------
symbol : str
ticker to get cost to borrow from
Returns
-------
pd.DataFrame
Cost to borrow
"""
df = pd.DataFrame()
try:
client = stocksera.Client(api_key=cfg.API_STOCKSERA_KEY)
df = pd.DataFrame(client.borrowed_shares(ticker=symbol))
df.columns = ["Ticker", "Fees", "Available", "Date"]
df.set_index("Date", inplace=True)
except StockseraRequestException:
console.print("[red]Invalid API Key[/red]\n")
except Exception as e:
console.print(f"[red]{e}[/red]\n")
return df

View File

@@ -0,0 +1,135 @@
""" Stocksera View """
__docformat__ = "numpy"
import logging
import os
from typing import List, Optional
import matplotlib.ticker
import pandas as pd
from matplotlib import pyplot as plt
from openbb_terminal.decorators import check_api_key
from openbb_terminal.config_terminal import theme
from openbb_terminal.decorators import log_start_end
from openbb_terminal.config_plot import PLOT_DPI
from openbb_terminal.helper_funcs import (
export_data,
lambda_long_number_format,
print_rich_table,
plot_autoscale,
is_valid_axes_count,
)
from openbb_terminal.stocks.dark_pool_shorts import stocksera_model
from openbb_terminal.rich_config import console
logger = logging.getLogger(__name__)
@log_start_end(log=logger)
def plot_cost_to_borrow(
symbol: str,
data: pd.DataFrame,
external_axes: Optional[List[plt.Axes]] = None,
):
"""Plots the cost to borrow of a stock. [Source: Stocksera]
Parameters
----------
symbol : str
ticker to get cost to borrow from
data: pd.DataFrame
Cost to borrow dataframe
external_axes : Optional[List[plt.Axes]], optional
External axes (2 axes are expected in the list), by default None
"""
# This plot has 2 axes
if not external_axes:
_, ax1 = plt.subplots(figsize=plot_autoscale(), dpi=PLOT_DPI)
ax2 = ax1.twinx()
elif is_valid_axes_count(external_axes, 2):
(ax1, ax2) = external_axes
else:
return
if data.empty:
return
ax1.bar(
data.index,
data["Available"],
0.3,
color=theme.up_color,
)
ax1.set_title(f"Cost to Borrow of {symbol}")
ax1.legend(labels=["Number Shares"], loc="best")
ax1.yaxis.set_major_formatter(matplotlib.ticker.EngFormatter())
ax2.set_ylabel("Fees %")
ax2.plot(data.index, data["Fees"].values)
ax2.tick_params(axis="y", which="major")
theme.style_twin_axes(ax1, ax2)
ax1.xaxis.set_major_locator(matplotlib.ticker.MaxNLocator(6))
if not external_axes:
theme.visualize_output()
@log_start_end(log=logger)
@check_api_key(["API_STOCKSERA_KEY"])
def cost_to_borrow(
symbol: str,
limit: int = 100,
raw: bool = False,
export: str = "",
external_axes: Optional[List[plt.Axes]] = None,
):
"""Plots the short interest of a stock. This corresponds to the
number of shares that have been sold short but have not yet been
covered or closed out. Either NASDAQ or NYSE [Source: Quandl]
Parameters
----------
symbol : str
ticker to get cost to borrow from
limit: int
Number of historical cost to borrow data to show
raw : bool
Flag to print raw data instead
export : str
Export dataframe data to csv,json,xlsx file
external_axes : Optional[List[plt.Axes]], optional
External axes (2 axes are expected in the list), by default None
"""
# Note: if you send an empty string stocksera will search every ticker
if not symbol:
console.print("[red]No symbol provided[/red]\n")
return
df_cost_to_borrow = stocksera_model.get_cost_to_borrow(symbol)
df_cost_to_borrow = df_cost_to_borrow.head(limit)[::-1]
pd.options.mode.chained_assignment = None
plot_cost_to_borrow(symbol, df_cost_to_borrow, external_axes)
if raw:
df_cost_to_borrow["Available"] = df_cost_to_borrow["Available"].apply(
lambda x: lambda_long_number_format(x)
)
print_rich_table(
df_cost_to_borrow,
headers=list(df_cost_to_borrow.columns),
show_index=True,
title=f"Cost to Borrow of {symbol}",
)
export_data(
export,
os.path.dirname(os.path.abspath(__file__)),
"stocksera",
df_cost_to_borrow,
)

85
poetry.lock generated vendored
View File

@@ -1066,7 +1066,7 @@ gitdb = ">=4.0.1,<5"
[[package]]
name = "grpcio"
version = "1.49.1"
version = "1.50.0"
description = "HTTP/2-based RPC framework"
category = "main"
optional = false
@@ -1076,7 +1076,7 @@ python-versions = ">=3.7"
six = ">=1.5.2"
[package.extras]
protobuf = ["grpcio-tools (>=1.49.1)"]
protobuf = ["grpcio-tools (>=1.50.0)"]
[[package]]
name = "h11"
@@ -1879,11 +1879,11 @@ test = ["pytest (<5.4)", "pytest-cov"]
[[package]]
name = "more-itertools"
version = "8.14.0"
version = "9.0.0"
description = "More routines for operating on iterables, beyond itertools"
category = "main"
optional = false
python-versions = ">=3.5"
python-versions = ">=3.7"
[[package]]
name = "mplfinance"
@@ -2230,7 +2230,7 @@ pyparsing = ">=2.0.2,<3.0.5 || >3.0.5"
[[package]]
name = "pandas"
version = "1.5.0"
version = "1.5.1"
description = "Powerful data structures for data analysis, time series, and statistics"
category = "main"
optional = false
@@ -2540,7 +2540,7 @@ requests = "*"
[[package]]
name = "psutil"
version = "5.9.2"
version = "5.9.3"
description = "Cross-platform lib for process and system monitoring in Python."
category = "main"
optional = false
@@ -3084,7 +3084,7 @@ requests = ">=2.0"
[[package]]
name = "pytz"
version = "2022.4"
version = "2022.5"
description = "World timezone definitions, modern and historical"
category = "main"
optional = false
@@ -3726,6 +3726,18 @@ python-versions = ">=3.8"
[package.dependencies]
pbr = ">=2.0.0,<2.1.0 || >2.1.0"
[[package]]
name = "stocksera"
version = "0.1.21"
description = "Official Stocksera API"
category = "main"
optional = false
python-versions = ">=3.6"
[package.dependencies]
pandas = "*"
requests = "*"
[[package]]
name = "streamlit"
version = "1.13.0"
@@ -3944,13 +3956,14 @@ requests = "*"
[[package]]
name = "traitlets"
version = "5.4.0"
version = "5.5.0"
description = ""
category = "main"
optional = false
python-versions = ">=3.7"
[package.extras]
docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
test = ["pre-commit", "pytest"]
[[package]]
@@ -4346,7 +4359,7 @@ prediction = ["torch"]
[metadata]
lock-version = "1.1"
python-versions = "^3.8,<3.11, !=3.9.7"
content-hash = "e8f775dcd95fd3f54e30eee355252e33e01619e070847be661b4e95b20ef1936"
content-hash = "c221577c37f21f30c12f8ccf882c6ca0bfdfc2afe303ea803d33bb7622bdc8d2"
[metadata.files]
aiodns = []
@@ -4880,53 +4893,7 @@ gitdb = [
{file = "gitdb-4.0.9.tar.gz", hash = "sha256:bac2fd45c0a1c9cf619e63a90d62bdc63892ef92387424b855792a6cabe789aa"},
]
gitpython = []
grpcio = [
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{file = "grpcio-1.49.1-cp39-cp39-macosx_10_10_x86_64.whl", hash = "sha256:9b449e966ef518ce9c860d21f8afe0b0f055220d95bc710301752ac1db96dd6a"},
{file = "grpcio-1.49.1-cp39-cp39-manylinux_2_17_aarch64.whl", hash = "sha256:aa34d2ad9f24e47fa9a3172801c676e4037d862247e39030165fe83821a7aafd"},
{file = "grpcio-1.49.1-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5207f4eed1b775d264fcfe379d8541e1c43b878f2b63c0698f8f5c56c40f3d68"},
{file = "grpcio-1.49.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0b24a74651438d45619ac67004638856f76cc13d78b7478f2457754cbcb1c8ad"},
{file = "grpcio-1.49.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:fe763781669790dc8b9618e7e677c839c87eae6cf28b655ee1fa69ae04eea03f"},
{file = "grpcio-1.49.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:2f2ff7ba0f8f431f32d4b4bc3a3713426949d3533b08466c4ff1b2b475932ca8"},
{file = "grpcio-1.49.1-cp39-cp39-win32.whl", hash = "sha256:08ff74aec8ff457a89b97152d36cb811dcc1d17cd5a92a65933524e363327394"},
{file = "grpcio-1.49.1-cp39-cp39-win_amd64.whl", hash = "sha256:274ffbb39717918c514b35176510ae9be06e1d93121e84d50b350861dcb9a705"},
{file = "grpcio-1.49.1.tar.gz", hash = "sha256:d4725fc9ec8e8822906ae26bb26f5546891aa7fbc3443de970cc556d43a5c99f"},
]
grpcio = []
h11 = []
hijri-converter = [
{file = "hijri-converter-2.2.4.tar.gz", hash = "sha256:9e1d9fa4c220f6867da2abb1a96240675ae974abba951c686a781f4ef6ac218f"},
@@ -5714,10 +5681,7 @@ pytrends = [
{file = "pytrends-4.8.0-py2-none-any.whl", hash = "sha256:31a76cf560a23a9eb691a9a83a3306bbe555ed1665122a5756e789829f56a0ef"},
{file = "pytrends-4.8.0.tar.gz", hash = "sha256:04b7b33eb6dfc120aa89cb4640688a8b633337276b6ddcea44ff0c7f6b6243d2"},
]
pytz = [
{file = "pytz-2022.4-py2.py3-none-any.whl", hash = "sha256:2c0784747071402c6e99f0bafdb7da0fa22645f06554c7ae06bf6358897e9c91"},
{file = "pytz-2022.4.tar.gz", hash = "sha256:48ce799d83b6f8aab2020e369b627446696619e79645419610b9facd909b3174"},
]
pytz = []
pytz-deprecation-shim = [
{file = "pytz_deprecation_shim-0.1.0.post0-py2.py3-none-any.whl", hash = "sha256:8314c9692a636c8eb3bda879b9f119e350e93223ae83e70e80c31675a0fdc1a6"},
{file = "pytz_deprecation_shim-0.1.0.post0.tar.gz", hash = "sha256:af097bae1b616dde5c5744441e2ddc69e74dfdcb0c263129610d85b87445a59d"},
@@ -6184,6 +6148,7 @@ statsmodels = [
{file = "statsmodels-0.13.2.tar.gz", hash = "sha256:77dc292c9939c036a476f1770f9d08976b05437daa229928da73231147cde7d4"},
]
stevedore = []
stocksera = []
streamlit = []
tabulate = [
{file = "tabulate-0.9.0-py3-none-any.whl", hash = "sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"},

1
pyproject.toml vendored
View File

@@ -101,6 +101,7 @@ ipyflex = "^0.2.4"
setuptools = "^65.4.1"
investiny = "^0.5.0"
numpy = "1.21.6"
stocksera = "^0.1.21"
[tool.poetry.dev-dependencies]
pytest = "^6.2.2"

13
requirements-full.txt vendored
View File

@@ -83,7 +83,7 @@ fundamentalanalysis==0.2.14
future==0.18.2; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0"
gitdb==4.0.9; python_version >= "3.7" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.7"
gitpython==3.1.29; python_version >= "3.7"
grpcio==1.49.1; python_full_version >= "3.7.1" and python_full_version < "4.0.0" and python_version >= "3.7"
grpcio==1.50.0; python_full_version >= "3.7.1" and python_full_version < "4.0.0" and python_version >= "3.7"
h11==0.12.0; python_version >= "3.8" and python_version < "4.0"
hijri-converter==2.2.4; python_version >= "3.7"
holidays==0.14.2; python_version >= "3.7"
@@ -135,7 +135,7 @@ mccabe==0.6.1; python_full_version >= "3.7.2"
mdit-py-plugins==0.2.8; python_version >= "3.6" and python_version < "4.0"
mistune==0.8.4; python_version >= "3.7"
mock==4.0.3; python_version >= "3.6"
more-itertools==8.14.0; python_version >= "3.6"
more-itertools==9.0.0; python_version >= "3.7"
mplfinance==0.12.9b1
multidict==6.0.2; python_version >= "3.7" and python_full_version >= "3.7.0"
multitasking==0.0.11
@@ -162,7 +162,7 @@ packaging==21.3; python_version >= "3.8" and python_full_version < "3.9.7" and p
pandas-datareader==0.10.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.6"
pandas-market-calendars==3.2; python_full_version >= "3.7.0"
pandas-ta==0.3.14b
pandas==1.5.0; python_version >= "3.8"
pandas==1.5.1; python_version >= "3.8"
pandocfilters==1.5.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.7"
parso==0.8.3; python_version >= "3.8" and python_full_version >= "3.7.0" and python_full_version < "4.0.0"
pathspec==0.10.1; python_version >= "3.7"
@@ -183,7 +183,7 @@ prompt-toolkit==3.0.31; python_full_version >= "3.6.2"
property-cached==1.6.4; python_version >= "3.8"
protobuf==3.20.3; python_full_version >= "3.7.1" and python_full_version < "4.0.0" and python_version >= "3.7" and (python_version >= "3.7" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.7")
psaw==0.0.12; python_version >= "3"
psutil==5.9.2; python_full_version >= "3.7.0" and python_full_version < "4.0.0" and python_version >= "3.7"
psutil==5.9.3; python_full_version >= "3.7.0" and python_full_version < "4.0.0" and python_version >= "3.7"
ptyprocess==0.7.0; os_name != "nt" and python_version >= "3.8" and sys_platform != "win32" and python_full_version >= "3.7.0" and python_full_version < "4.0.0"
pure-eval==0.2.2; python_version >= "3.8" and python_full_version >= "3.7.0" and python_full_version < "4.0.0"
py==1.11.0; python_full_version >= "3.7.0" and python_version >= "3.7" and python_full_version < "4.0.0" and implementation_name == "pypy"
@@ -224,7 +224,7 @@ python-dotenv==0.19.2; python_version >= "3.5"
python-i18n==0.3.9
pytrends==4.8.0
pytz-deprecation-shim==0.1.0.post0; python_version >= "3.7" and python_full_version < "3.0.0" or python_version >= "3.7" and python_full_version < "3.9.7" and python_full_version >= "3.6.0" or python_full_version > "3.9.7" and python_version >= "3.6"
pytz==2022.4; python_full_version >= "3.7.1" and python_full_version < "4.0.0" and python_version >= "3.8" and (python_version >= "3.8" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.8") and python_version < "4.0"
pytz==2022.5; python_full_version >= "3.7.1" and python_full_version < "4.0.0" and python_version >= "3.8" and (python_version >= "3.8" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.8") and python_version < "4.0"
pyupgrade==2.38.4; python_version >= "3.7"
pywin32==304; sys_platform == "win32" and platform_python_implementation != "PyPy" and python_version >= "3.7"
pywinpty==2.0.8; os_name == "nt" and python_version >= "3.7"
@@ -273,6 +273,7 @@ sseclient==0.0.27
stack-data==0.5.1; python_version >= "3.8" and python_full_version >= "3.7.0" and python_full_version < "4.0.0"
statsmodels==0.13.2; python_version >= "3.7"
stevedore==4.0.1; python_version >= "3.8"
stocksera==0.1.21; python_version >= "3.6"
streamlit==1.13.0; (python_version >= "3.7" and python_full_version < "3.9.7") or (python_full_version > "3.9.7")
tabulate==0.9.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.7"
temporal-cache==0.1.4
@@ -291,7 +292,7 @@ torch==1.11.0; python_full_version >= "3.7.0"
tornado==6.2; python_version >= "3.7" and python_full_version < "3.9.7" and python_full_version >= "3.7.0" or python_full_version > "3.9.7" and python_version >= "3.7" and python_full_version < "4.0.0"
tqdm==4.64.1; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0"
tradingview-ta==3.3.0; python_version >= "3.6"
traitlets==5.4.0; python_full_version >= "3.7.0" and python_full_version < "4.0.0" and python_version >= "3.8"
traitlets==5.5.0; python_full_version >= "3.7.0" and python_full_version < "4.0.0" and python_version >= "3.8"
types-python-dateutil==2.8.19.2
types-pytz==2021.3.8
types-pyyaml==6.0.12

13
requirements.txt vendored
View File

@@ -72,7 +72,7 @@ fundamentalanalysis==0.2.14
future==0.18.2; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0"
gitdb==4.0.9; python_version >= "3.7" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.7"
gitpython==3.1.29; python_version >= "3.7"
grpcio==1.49.1; python_full_version >= "3.7.1" and python_full_version < "4.0.0" and python_version >= "3.7"
grpcio==1.50.0; python_full_version >= "3.7.1" and python_full_version < "4.0.0" and python_version >= "3.7"
h11==0.12.0; python_version >= "3.8" and python_version < "4.0"
hijri-converter==2.2.4; python_version >= "3.7"
holidays==0.14.2; python_version >= "3.7"
@@ -116,7 +116,7 @@ matplotlib-inline==0.1.6; python_version >= "3.8"
matplotlib==3.5.3; python_version >= "3.7"
mccabe==0.6.1; python_full_version >= "3.7.0"
mistune==0.8.4; python_version >= "3.7"
more-itertools==8.14.0; python_version >= "3.6"
more-itertools==9.0.0; python_version >= "3.7"
mplfinance==0.12.9b1
multidict==6.0.2; python_version >= "3.7" and python_full_version >= "3.7.0"
multitasking==0.0.11
@@ -140,7 +140,7 @@ packaging==21.3; python_version >= "3.8" and python_full_version < "3.9.7" or py
pandas-datareader==0.10.0; python_version >= "3.6" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.6"
pandas-market-calendars==3.2; python_full_version >= "3.7.0"
pandas-ta==0.3.14b
pandas==1.5.0; python_version >= "3.8"
pandas==1.5.1; python_version >= "3.8"
pandocfilters==1.5.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.7"
parso==0.8.3; python_version >= "3.8"
pathspec==0.10.1; python_version >= "3.7"
@@ -158,7 +158,7 @@ prompt-toolkit==3.0.31; python_full_version >= "3.6.2"
property-cached==1.6.4; python_version >= "3.8"
protobuf==3.20.3; python_full_version >= "3.7.1" and python_full_version < "4.0.0" and python_version >= "3.7" and (python_version >= "3.7" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.7")
psaw==0.0.12; python_version >= "3"
psutil==5.9.2; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.7"
psutil==5.9.3; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0" and python_version >= "3.7"
ptyprocess==0.7.0; os_name != "nt" and python_version >= "3.8" and sys_platform != "win32"
pure-eval==0.2.2; python_version >= "3.8"
py==1.11.0; python_version >= "3.7" and python_full_version < "3.0.0" and implementation_name == "pypy" or implementation_name == "pypy" and python_version >= "3.7" and python_full_version >= "3.5.0"
@@ -193,7 +193,7 @@ python-dotenv==0.19.2; python_version >= "3.5"
python-i18n==0.3.9
pytrends==4.8.0
pytz-deprecation-shim==0.1.0.post0; python_version >= "3.7" and python_full_version < "3.0.0" or python_version >= "3.7" and python_full_version < "3.9.7" and python_full_version >= "3.6.0" or python_full_version > "3.9.7" and python_version >= "3.6"
pytz==2022.4; python_full_version >= "3.7.1" and python_full_version < "4.0.0" and python_version >= "3.8" and (python_version >= "3.8" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.8") and python_version < "4.0"
pytz==2022.5; python_full_version >= "3.7.1" and python_full_version < "4.0.0" and python_version >= "3.8" and (python_version >= "3.8" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.8") and python_version < "4.0"
pywin32==304; sys_platform == "win32" and platform_python_implementation != "PyPy" and python_version >= "3.7"
pywinpty==2.0.8; os_name == "nt" and python_version >= "3.7"
pyyaml==6.0; python_version >= "3.8"
@@ -232,6 +232,7 @@ squarify==0.4.3
sseclient==0.0.27
stack-data==0.5.1; python_version >= "3.8"
statsmodels==0.13.2; python_version >= "3.7"
stocksera==0.1.21; python_version >= "3.6"
streamlit==1.13.0; (python_version >= "3.7" and python_full_version < "3.9.7") or (python_full_version > "3.9.7")
tabulate==0.9.0; python_version >= "3.7" and python_full_version < "3.0.0" or python_full_version >= "3.6.0" and python_version >= "3.7"
temporal-cache==0.1.4
@@ -247,7 +248,7 @@ toolz==0.12.0; python_version >= "3.8" and python_version < "4.0" and python_ful
tornado==6.2; python_version >= "3.7" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.7"
tqdm==4.64.1; python_version >= "2.7" and python_full_version < "3.0.0" or python_full_version >= "3.4.0"
tradingview-ta==3.3.0; python_version >= "3.6"
traitlets==5.4.0; python_version >= "3.8" and python_full_version >= "3.7.0"
traitlets==5.5.0; python_version >= "3.8" and python_full_version >= "3.7.0"
typing-extensions==4.4.0; python_full_version >= "3.7.0" and python_full_version < "4.0.0" and python_version < "3.9" and python_version >= "3.7" and (python_version >= "3.7" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.7") and (python_version >= "3.7" and python_full_version < "3.9.7" or python_full_version > "3.9.7")
tzdata==2022.5; python_version >= "3.7" and python_full_version < "3.0.0" and platform_system == "Windows" or python_version >= "3.7" and python_full_version < "3.9.7" and platform_system == "Windows" and python_full_version >= "3.6.0" or python_full_version > "3.9.7" and python_version >= "3.6" and platform_system == "Windows"
tzlocal==4.2; python_version >= "3.7" and python_full_version < "3.9.7" or python_full_version > "3.9.7" and python_version >= "3.6"

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2022-10-14 07:40,TSLA,0.25,10000000
2022-10-14 07:30,TSLA,0.25,10000000
2022-10-14 07:20,TSLA,0.25,10000000
2022-10-14 07:10,TSLA,0.25,10000000
2022-10-14 07:02,TSLA,0.25,10000000
2022-10-13 16:50,TSLA,0.25,10000000
2022-10-13 16:41,TSLA,0.25,10000000
2022-10-13 16:30,TSLA,0.25,10000000
2022-10-13 16:20,TSLA,0.25,10000000
2022-10-13 16:10,TSLA,0.25,10000000
2022-10-13 16:02,TSLA,0.25,10000000
2022-10-13 15:50,TSLA,0.25,10000000
2022-10-13 15:40,TSLA,0.25,10000000
2022-10-13 15:31,TSLA,0.25,10000000
2022-10-13 15:20,TSLA,0.25,10000000
2022-10-13 15:10,TSLA,0.25,10000000
2022-10-13 15:01,TSLA,0.25,10000000
2022-10-13 14:50,TSLA,0.25,10000000
2022-10-13 14:40,TSLA,0.25,10000000
2022-10-13 14:30,TSLA,0.25,10000000
2022-10-13 14:20,TSLA,0.25,10000000
2022-10-13 14:10,TSLA,0.25,10000000
2022-10-13 14:01,TSLA,0.25,10000000
2022-10-13 13:50,TSLA,0.25,10000000
2022-10-13 13:41,TSLA,0.25,10000000
2022-10-13 13:30,TSLA,0.25,10000000
2022-10-13 13:20,TSLA,0.25,10000000
2022-10-13 13:10,TSLA,0.25,10000000
2022-10-13 13:02,TSLA,0.25,10000000
2022-10-13 12:51,TSLA,0.25,10000000
2022-10-13 12:41,TSLA,0.25,10000000
2022-10-13 12:30,TSLA,0.25,10000000
2022-10-13 12:20,TSLA,0.25,10000000
2022-10-13 12:10,TSLA,0.25,10000000
2022-10-13 12:01,TSLA,0.25,10000000
2022-10-13 11:50,TSLA,0.25,10000000
2022-10-13 11:40,TSLA,0.25,10000000
2022-10-13 11:30,TSLA,0.25,10000000
2022-10-13 11:20,TSLA,0.25,10000000
2022-10-13 11:10,TSLA,0.25,10000000
2022-10-13 11:01,TSLA,0.25,10000000
2022-10-13 10:50,TSLA,0.25,10000000
2022-10-13 10:40,TSLA,0.25,10000000
2022-10-13 10:31,TSLA,0.25,10000000
2022-10-13 10:20,TSLA,0.25,10000000
2022-10-13 10:10,TSLA,0.25,10000000
2022-10-13 10:02,TSLA,0.25,10000000
2022-10-13 09:50,TSLA,0.25,10000000
2022-10-13 09:40,TSLA,0.25,10000000
2022-10-13 09:30,TSLA,0.25,10000000
2022-10-13 09:20,TSLA,0.25,10000000
2022-10-13 09:10,TSLA,0.25,10000000
2022-10-13 08:50,TSLA,0.25,10000000
2022-10-13 08:41,TSLA,0.25,10000000
2022-10-13 08:30,TSLA,0.25,10000000
2022-10-13 08:20,TSLA,0.25,10000000
2022-10-13 08:10,TSLA,0.2596,10000000
2022-10-13 08:01,TSLA,0.2596,10000000
2022-10-13 07:51,TSLA,0.2596,10000000
2022-10-13 07:40,TSLA,0.2596,10000000
2022-10-13 07:30,TSLA,0.2596,10000000
2022-10-13 07:20,TSLA,0.2596,10000000
2022-10-13 07:10,TSLA,0.2596,10000000
2022-10-13 07:01,TSLA,0.2596,10000000
2022-10-12 16:50,TSLA,0.2596,10000000
2022-10-12 16:40,TSLA,0.2596,10000000
2022-10-12 16:31,TSLA,0.2596,10000000
2022-10-12 16:20,TSLA,0.2596,10000000
2022-10-12 16:10,TSLA,0.2603,10000000
2022-10-12 16:02,TSLA,0.2603,10000000
2022-10-12 15:50,TSLA,0.2603,10000000
2022-10-12 15:40,TSLA,0.2603,10000000
2022-10-12 15:31,TSLA,0.2603,10000000
2022-10-12 15:20,TSLA,0.2603,10000000
2022-10-12 15:10,TSLA,0.2661,10000000
2022-10-12 15:01,TSLA,0.2661,10000000
2022-10-12 14:50,TSLA,0.2661,10000000
2022-10-12 14:40,TSLA,0.2661,10000000
2022-10-12 14:30,TSLA,0.2661,10000000
2022-10-12 14:20,TSLA,0.2661,10000000
2022-10-12 14:10,TSLA,0.2661,10000000
2022-10-12 14:01,TSLA,0.2661,10000000
2022-10-12 13:50,TSLA,0.2661,10000000
2022-10-12 13:40,TSLA,0.2661,10000000
2022-10-12 13:31,TSLA,0.2661,10000000
2022-10-12 13:20,TSLA,0.2661,10000000
2022-10-12 13:10,TSLA,0.2769,10000000
2022-10-12 13:02,TSLA,0.2769,10000000
2022-10-12 12:50,TSLA,0.2769,10000000
2022-10-12 12:40,TSLA,0.2769,10000000
2022-10-12 12:31,TSLA,0.2769,10000000
2022-10-12 12:20,TSLA,0.2769,10000000
2022-10-12 12:10,TSLA,0.2769,10000000
2022-10-12 12:01,TSLA,0.2769,10000000
2022-10-12 11:50,TSLA,0.2769,10000000
2022-10-12 11:40,TSLA,0.2769,10000000
2022-10-12 11:30,TSLA,0.2769,10000000
2022-10-12 11:20,TSLA,0.2769,10000000
2022-10-12 11:10,TSLA,0.2771,10000000
2022-10-12 11:01,TSLA,0.2771,10000000
2022-10-12 10:50,TSLA,0.2771,10000000
2022-10-12 10:40,TSLA,0.2771,10000000
2022-10-12 10:31,TSLA,0.2771,10000000
2022-10-12 10:20,TSLA,0.2771,10000000
2022-10-12 10:10,TSLA,0.2771,10000000
2022-10-12 10:01,TSLA,0.2771,10000000
2022-10-12 09:50,TSLA,0.2771,10000000
2022-10-12 09:40,TSLA,0.2771,10000000
2022-10-12 09:30,TSLA,0.2771,10000000
2022-10-12 09:20,TSLA,0.2771,10000000
2022-10-12 09:10,TSLA,0.2771,10000000
2022-10-12 09:02,TSLA,0.2771,10000000
2022-10-12 08:50,TSLA,0.2771,10000000
2022-10-12 08:41,TSLA,0.2771,10000000
2022-10-12 08:31,TSLA,0.2771,10000000
2022-10-12 08:20,TSLA,0.2771,10000000
2022-10-12 08:10,TSLA,0.2539,10000000
2022-10-12 08:01,TSLA,0.2539,10000000
2022-10-12 07:50,TSLA,0.2539,10000000
2022-10-12 07:40,TSLA,0.2539,10000000
2022-10-12 07:30,TSLA,0.2539,10000000
2022-10-12 07:20,TSLA,0.2539,10000000
2022-10-12 07:11,TSLA,0.2539,10000000
2022-10-12 07:02,TSLA,0.2539,10000000
2022-10-11 16:50,TSLA,0.2539,10000000
2022-10-11 16:40,TSLA,0.2539,10000000
2022-10-11 16:31,TSLA,0.2539,10000000
2022-10-11 16:21,TSLA,0.2539,10000000
2022-10-11 16:10,TSLA,0.25,10000000
2022-10-11 16:02,TSLA,0.25,10000000
2022-10-11 15:50,TSLA,0.25,10000000
2022-10-11 15:41,TSLA,0.25,10000000
2022-10-11 15:31,TSLA,0.25,10000000
2022-10-11 15:20,TSLA,0.25,10000000
2022-10-11 15:10,TSLA,0.25,10000000
2022-10-11 15:02,TSLA,0.25,10000000
2022-10-11 14:50,TSLA,0.25,10000000
2022-10-11 14:41,TSLA,0.25,10000000
2022-10-11 14:31,TSLA,0.25,10000000
2022-10-11 14:20,TSLA,0.25,10000000
2022-10-11 14:10,TSLA,0.25,10000000
2022-10-11 14:01,TSLA,0.25,10000000
2022-10-11 13:50,TSLA,0.25,10000000
2022-10-11 13:41,TSLA,0.25,10000000
2022-10-11 13:31,TSLA,0.25,10000000
2022-10-11 13:20,TSLA,0.25,10000000
2022-10-11 13:10,TSLA,0.25,10000000
2022-10-11 13:02,TSLA,0.25,10000000
2022-10-11 12:50,TSLA,0.25,10000000
2022-10-11 12:41,TSLA,0.25,10000000
2022-10-11 12:31,TSLA,0.25,10000000
2022-10-11 12:20,TSLA,0.25,10000000
2022-10-11 12:10,TSLA,0.25,10000000
2022-10-11 12:01,TSLA,0.25,10000000
2022-10-11 11:50,TSLA,0.25,10000000
2022-10-11 11:41,TSLA,0.25,10000000
2022-10-11 11:31,TSLA,0.25,10000000
2022-10-11 11:20,TSLA,0.25,10000000
2022-10-11 11:10,TSLA,0.25,10000000
2022-10-11 11:01,TSLA,0.25,10000000
2022-10-11 10:50,TSLA,0.25,10000000
2022-10-11 10:40,TSLA,0.25,10000000
2022-10-11 10:31,TSLA,0.25,10000000
2022-10-11 10:20,TSLA,0.25,10000000
2022-10-11 10:10,TSLA,0.25,10000000
2022-10-11 10:01,TSLA,0.25,10000000
2022-10-11 09:50,TSLA,0.25,10000000
2022-10-11 09:40,TSLA,0.25,10000000
2022-10-11 09:31,TSLA,0.25,10000000
2022-10-11 09:20,TSLA,0.25,10000000
2022-10-11 09:10,TSLA,0.25,10000000
2022-10-11 09:02,TSLA,0.25,10000000
2022-10-11 08:50,TSLA,0.25,10000000
2022-10-11 08:40,TSLA,0.25,10000000
2022-10-11 08:31,TSLA,0.25,10000000
2022-10-11 08:20,TSLA,0.25,10000000
2022-10-11 08:10,TSLA,0.25,10000000
2022-10-11 08:01,TSLA,0.25,10000000
2022-10-11 07:50,TSLA,0.25,10000000
2022-10-11 07:40,TSLA,0.25,10000000
2022-10-11 07:30,TSLA,0.25,10000000
2022-10-11 07:20,TSLA,0.25,10000000
2022-10-11 07:10,TSLA,0.25,10000000
2022-10-11 07:01,TSLA,0.25,10000000
2022-10-10 16:50,TSLA,0.25,10000000
2022-10-10 16:40,TSLA,0.25,10000000
2022-10-10 16:31,TSLA,0.25,10000000
2022-10-10 16:20,TSLA,0.25,10000000
2022-10-10 16:10,TSLA,0.25,10000000
2022-10-10 16:02,TSLA,0.25,10000000
2022-10-10 15:50,TSLA,0.25,10000000
2022-10-10 15:40,TSLA,0.25,10000000
2022-10-10 15:31,TSLA,0.25,10000000
2022-10-10 15:20,TSLA,0.25,10000000
2022-10-10 15:10,TSLA,0.25,10000000
2022-10-10 15:01,TSLA,0.25,10000000
2022-10-10 14:50,TSLA,0.25,10000000
2022-10-10 14:40,TSLA,0.25,10000000
2022-10-10 14:30,TSLA,0.25,10000000
2022-10-10 14:20,TSLA,0.25,10000000
2022-10-10 14:10,TSLA,0.25,10000000
2022-10-10 14:01,TSLA,0.25,10000000
2022-10-10 13:50,TSLA,0.25,10000000
2022-10-10 13:40,TSLA,0.25,10000000
2022-10-10 13:31,TSLA,0.25,10000000
2022-10-10 13:20,TSLA,0.25,10000000
2022-10-10 13:10,TSLA,0.25,10000000
2022-10-10 13:01,TSLA,0.25,10000000
2022-10-10 12:50,TSLA,0.25,10000000
2022-10-10 12:40,TSLA,0.25,10000000
2022-10-10 12:30,TSLA,0.25,10000000
2022-10-10 12:20,TSLA,0.25,10000000
2022-10-10 12:10,TSLA,0.25,10000000
2022-10-10 12:01,TSLA,0.25,10000000
2022-10-10 11:50,TSLA,0.25,10000000
2022-10-10 11:40,TSLA,0.25,10000000
2022-10-10 11:30,TSLA,0.25,10000000
2022-10-10 11:20,TSLA,0.25,10000000
2022-10-10 11:10,TSLA,0.25,10000000
2022-10-10 11:01,TSLA,0.25,10000000
2022-10-10 10:50,TSLA,0.25,10000000
2022-10-10 10:40,TSLA,0.25,10000000
2022-10-10 10:31,TSLA,0.25,10000000
2022-10-10 10:20,TSLA,0.25,10000000
2022-10-10 10:10,TSLA,0.25,10000000
2022-10-10 10:01,TSLA,0.25,10000000
2022-10-10 09:50,TSLA,0.25,10000000
2022-10-10 09:40,TSLA,0.25,10000000
2022-10-10 09:30,TSLA,0.25,10000000
2022-10-10 09:20,TSLA,0.25,10000000
2022-10-10 09:10,TSLA,0.25,10000000
2022-10-10 09:02,TSLA,0.25,10000000
2022-10-10 08:50,TSLA,0.25,10000000
2022-10-10 08:40,TSLA,0.25,10000000
2022-10-10 08:30,TSLA,0.25,10000000
2022-10-10 08:20,TSLA,0.25,10000000
2022-10-10 08:10,TSLA,0.25,10000000
2022-10-10 08:01,TSLA,0.25,10000000
2022-10-10 07:50,TSLA,0.25,10000000
2022-10-10 07:40,TSLA,0.25,10000000
2022-10-10 07:30,TSLA,0.25,10000000
2022-10-10 07:20,TSLA,0.25,10000000
2022-10-10 07:10,TSLA,0.25,10000000
2022-10-10 07:01,TSLA,0.25,10000000
2022-10-07 16:50,TSLA,0.25,10000000
2022-10-07 16:40,TSLA,0.25,10000000
2022-10-07 16:31,TSLA,0.25,10000000
2022-10-07 16:20,TSLA,0.25,10000000
2022-10-07 16:10,TSLA,0.25,10000000
2022-10-07 16:02,TSLA,0.25,10000000
2022-10-07 15:50,TSLA,0.25,10000000
2022-10-07 15:40,TSLA,0.25,10000000
2022-10-07 15:31,TSLA,0.25,10000000
2022-10-07 15:20,TSLA,0.25,10000000
2022-10-07 15:11,TSLA,0.25,10000000
2022-10-07 14:50,TSLA,0.25,10000000
2022-10-07 14:40,TSLA,0.25,10000000
2022-10-07 14:31,TSLA,0.25,10000000
2022-10-07 14:20,TSLA,0.25,10000000
2022-10-07 14:10,TSLA,0.25,10000000
2022-10-07 14:01,TSLA,0.25,10000000
2022-10-07 13:50,TSLA,0.25,10000000
2022-10-07 13:40,TSLA,0.25,10000000
2022-10-07 13:31,TSLA,0.25,10000000
2022-10-07 13:20,TSLA,0.25,10000000
2022-10-07 13:10,TSLA,0.25,10000000
2022-10-07 13:01,TSLA,0.25,10000000
2022-10-07 12:50,TSLA,0.25,10000000
2022-10-07 12:40,TSLA,0.25,10000000
2022-10-07 12:31,TSLA,0.25,10000000
2022-10-07 12:20,TSLA,0.25,10000000
2022-10-07 12:10,TSLA,0.25,10000000
2022-10-07 12:01,TSLA,0.25,10000000
2022-10-07 11:50,TSLA,0.25,10000000
2022-10-07 11:40,TSLA,0.25,10000000
2022-10-07 11:31,TSLA,0.25,10000000
2022-10-07 11:20,TSLA,0.25,10000000
2022-10-07 11:10,TSLA,0.25,10000000
2022-10-07 11:01,TSLA,0.25,10000000
2022-10-07 10:50,TSLA,0.25,10000000
2022-10-07 10:40,TSLA,0.25,10000000
2022-10-07 10:31,TSLA,0.25,10000000
2022-10-07 10:20,TSLA,0.25,10000000
2022-10-07 10:10,TSLA,0.25,10000000
2022-10-07 10:01,TSLA,0.25,10000000
2022-10-07 09:50,TSLA,0.25,10000000
2022-10-07 09:40,TSLA,0.25,10000000
2022-10-07 09:31,TSLA,0.25,10000000
2022-10-07 09:20,TSLA,0.25,10000000
2022-10-07 09:10,TSLA,0.25,10000000
2022-10-07 09:02,TSLA,0.25,10000000
2022-10-07 08:50,TSLA,0.25,10000000
2022-10-07 08:40,TSLA,0.25,10000000
2022-10-07 08:31,TSLA,0.25,10000000
2022-10-07 08:20,TSLA,0.25,10000000
2022-10-07 08:10,TSLA,0.25,10000000
2022-10-07 08:01,TSLA,0.25,10000000
2022-10-07 07:50,TSLA,0.25,10000000
2022-10-07 07:40,TSLA,0.25,10000000
2022-10-07 07:30,TSLA,0.25,10000000
2022-10-07 07:20,TSLA,0.25,10000000
2022-10-07 07:10,TSLA,0.25,10000000
2022-10-07 07:01,TSLA,0.25,10000000
2022-10-06 16:50,TSLA,0.25,10000000
2022-10-06 16:40,TSLA,0.25,10000000
2022-10-06 16:30,TSLA,0.25,10000000
2022-10-06 16:20,TSLA,0.25,10000000
2022-10-06 16:10,TSLA,0.25,10000000
2022-10-06 16:01,TSLA,0.25,10000000
2022-10-06 15:50,TSLA,0.25,10000000
2022-10-06 15:40,TSLA,0.25,10000000
2022-10-06 15:31,TSLA,0.25,10000000
2022-10-06 15:20,TSLA,0.25,10000000
2022-10-06 15:10,TSLA,0.25,10000000
2022-10-06 15:01,TSLA,0.25,10000000
2022-10-06 14:50,TSLA,0.25,10000000
2022-10-06 14:40,TSLA,0.25,10000000
2022-10-06 14:30,TSLA,0.25,10000000
2022-10-06 14:20,TSLA,0.25,10000000
2022-10-06 14:10,TSLA,0.25,10000000
2022-10-06 14:01,TSLA,0.25,10000000
2022-10-06 13:50,TSLA,0.25,10000000
2022-10-06 13:40,TSLA,0.25,10000000
2022-10-06 13:30,TSLA,0.25,10000000
2022-10-06 13:20,TSLA,0.25,10000000
2022-10-06 13:10,TSLA,0.25,10000000
2022-10-06 13:01,TSLA,0.25,10000000
2022-10-06 12:50,TSLA,0.25,10000000
2022-10-06 12:40,TSLA,0.25,10000000
2022-10-06 12:30,TSLA,0.25,10000000
2022-10-06 12:20,TSLA,0.25,10000000
2022-10-06 12:10,TSLA,0.25,10000000
2022-10-06 12:01,TSLA,0.25,10000000
2022-10-06 11:50,TSLA,0.25,10000000
2022-10-06 11:40,TSLA,0.25,10000000
2022-10-06 11:30,TSLA,0.25,10000000
2022-10-06 11:20,TSLA,0.25,10000000
2022-10-06 11:10,TSLA,0.25,10000000
2022-10-06 11:01,TSLA,0.25,10000000
2022-10-06 10:50,TSLA,0.25,10000000
2022-10-06 10:40,TSLA,0.25,10000000
2022-10-06 10:39,TSLA,0.25,10000000
1 Date Ticker Fees Available
2 2022-10-19 10:21 TSLA 0.25 10000000
3 2022-10-19 10:01 TSLA 0.25 10000000
4 2022-10-19 09:51 TSLA 0.25 10000000
5 2022-10-19 09:40 TSLA 0.25 10000000
6 2022-10-19 09:30 TSLA 0.25 10000000
7 2022-10-19 09:20 TSLA 0.25 10000000
8 2022-10-19 09:10 TSLA 0.25 10000000
9 2022-10-19 09:02 TSLA 0.25 10000000
10 2022-10-19 08:51 TSLA 0.25 10000000
11 2022-10-19 08:40 TSLA 0.25 10000000
12 2022-10-19 08:30 TSLA 0.25 10000000
13 2022-10-19 08:20 TSLA 0.25 10000000
14 2022-10-19 08:10 TSLA 0.25 10000000
15 2022-10-19 08:02 TSLA 0.25 10000000
16 2022-10-19 07:50 TSLA 0.25 10000000
17 2022-10-19 07:40 TSLA 0.25 10000000
18 2022-10-19 07:30 TSLA 0.25 10000000
19 2022-10-19 07:20 TSLA 0.25 10000000
20 2022-10-19 07:10 TSLA 0.25 10000000
21 2022-10-19 07:02 TSLA 0.25 10000000
22 2022-10-18 16:50 TSLA 0.25 10000000
23 2022-10-18 16:40 TSLA 0.25 10000000
24 2022-10-18 16:30 TSLA 0.25 10000000
25 2022-10-18 16:20 TSLA 0.25 10000000
26 2022-10-18 16:10 TSLA 0.25 10000000
27 2022-10-18 16:02 TSLA 0.25 10000000
28 2022-10-18 15:50 TSLA 0.25 10000000
29 2022-10-18 15:40 TSLA 0.25 10000000
30 2022-10-18 15:31 TSLA 0.25 10000000
31 2022-10-18 15:20 TSLA 0.25 10000000
32 2022-10-18 15:10 TSLA 0.2652 10000000
33 2022-10-18 14:50 TSLA 0.2652 10000000
34 2022-10-18 14:40 TSLA 0.2652 10000000
35 2022-10-18 14:30 TSLA 0.2652 10000000
36 2022-10-18 14:20 TSLA 0.2652 10000000
37 2022-10-18 14:10 TSLA 0.2652 10000000
38 2022-10-18 14:01 TSLA 0.2652 10000000
39 2022-10-18 13:51 TSLA 0.2652 10000000
40 2022-10-18 13:40 TSLA 0.2652 10000000
41 2022-10-18 13:30 TSLA 0.2652 10000000
42 2022-10-18 13:20 TSLA 0.2652 10000000
43 2022-10-18 13:10 TSLA 0.3057 10000000
44 2022-10-18 13:01 TSLA 0.3057 10000000
45 2022-10-18 12:51 TSLA 0.3057 10000000
46 2022-10-18 12:40 TSLA 0.3057 10000000
47 2022-10-18 12:31 TSLA 0.3057 10000000
48 2022-10-18 12:20 TSLA 0.3057 10000000
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470 2022-10-07 11:20 TSLA 0.25 10000000
471 2022-10-07 11:10 TSLA 0.25 10000000
472 2022-10-07 11:01 TSLA 0.25 10000000
473 2022-10-07 10:50 TSLA 0.25 10000000
474 2022-10-07 10:40 TSLA 0.25 10000000
475 2022-10-07 10:31 TSLA 0.25 10000000
476 2022-10-07 10:20 TSLA 0.25 10000000
477 2022-10-07 10:10 TSLA 0.25 10000000
478 2022-10-07 10:01 TSLA 0.25 10000000
479 2022-10-07 09:50 TSLA 0.25 10000000
480 2022-10-07 09:40 TSLA 0.25 10000000
481 2022-10-07 09:31 TSLA 0.25 10000000
482 2022-10-07 09:20 TSLA 0.25 10000000
483 2022-10-07 09:10 TSLA 0.25 10000000
484 2022-10-07 09:02 TSLA 0.25 10000000
485 2022-10-07 08:50 TSLA 0.25 10000000
486 2022-10-07 08:40 TSLA 0.25 10000000
487 2022-10-07 08:31 TSLA 0.25 10000000
488 2022-10-07 08:20 TSLA 0.25 10000000
489 2022-10-07 08:10 TSLA 0.25 10000000
490 2022-10-07 08:01 TSLA 0.25 10000000
491 2022-10-07 07:50 TSLA 0.25 10000000
492 2022-10-07 07:40 TSLA 0.25 10000000
493 2022-10-07 07:30 TSLA 0.25 10000000
494 2022-10-07 07:20 TSLA 0.25 10000000
495 2022-10-07 07:10 TSLA 0.25 10000000
496 2022-10-07 07:01 TSLA 0.25 10000000
497 2022-10-06 16:50 TSLA 0.25 10000000
498 2022-10-06 16:40 TSLA 0.25 10000000
499 2022-10-06 16:30 TSLA 0.25 10000000
500 2022-10-06 16:20 TSLA 0.25 10000000
501 2022-10-06 16:10 TSLA 0.25 10000000
502 2022-10-06 16:01 TSLA 0.25 10000000
503 2022-10-06 15:50 TSLA 0.25 10000000
504 2022-10-06 15:40 TSLA 0.25 10000000
505 2022-10-06 15:31 TSLA 0.25 10000000
506 2022-10-06 15:20 TSLA 0.25 10000000
507 2022-10-06 15:10 TSLA 0.25 10000000
508 2022-10-06 15:01 TSLA 0.25 10000000
509 2022-10-06 14:50 TSLA 0.25 10000000
510 2022-10-06 14:40 TSLA 0.25 10000000
511 2022-10-06 14:30 TSLA 0.25 10000000
512 2022-10-06 14:20 TSLA 0.25 10000000
513 2022-10-06 14:10 TSLA 0.25 10000000
514 2022-10-06 14:01 TSLA 0.25 10000000
515 2022-10-06 13:50 TSLA 0.25 10000000
516 2022-10-06 13:40 TSLA 0.25 10000000
517 2022-10-06 13:30 TSLA 0.25 10000000
518 2022-10-06 13:20 TSLA 0.25 10000000
519 2022-10-06 13:10 TSLA 0.25 10000000
520 2022-10-06 13:01 TSLA 0.25 10000000
521 2022-10-06 12:50 TSLA 0.25 10000000
522 2022-10-06 12:40 TSLA 0.25 10000000
523 2022-10-06 12:30 TSLA 0.25 10000000
524 2022-10-06 12:20 TSLA 0.25 10000000
525 2022-10-06 12:10 TSLA 0.25 10000000
526 2022-10-06 12:01 TSLA 0.25 10000000
527 2022-10-06 11:50 TSLA 0.25 10000000
528 2022-10-06 11:40 TSLA 0.25 10000000
529 2022-10-06 11:30 TSLA 0.25 10000000
530 2022-10-06 11:20 TSLA 0.25 10000000
531 2022-10-06 11:10 TSLA 0.25 10000000
532 2022-10-06 11:01 TSLA 0.25 10000000
533 2022-10-06 10:50 TSLA 0.25 10000000
534 2022-10-06 10:40 TSLA 0.25 10000000
535 2022-10-06 10:39 TSLA 0.25 10000000

View File

@@ -0,0 +1,14 @@
# IMPORTATION STANDARD
# IMPORTATION THIRDPARTY
import pytest
# IMPORTATION INTERNAL
from openbb_terminal.stocks.dark_pool_shorts import stocksera_model
@pytest.mark.vcr
def test_get_cost_to_borrow(recorder):
result_df = stocksera_model.get_cost_to_borrow("TSLA")
recorder.capture(result_df)

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@@ -0,0 +1,19 @@
# IMPORTATION STANDARD
# IMPORTATION THIRDPARTY
import pytest
import pandas as pd
# IMPORTATION INTERNAL
from openbb_terminal.stocks.dark_pool_shorts import stocksera_view
@pytest.mark.vcr
def test_plot_cost_to_borrow():
df = pd.DataFrame()
stocksera_view.plot_cost_to_borrow("TSLA", df)
@pytest.mark.vcr
def test_cost_to_borrow():
stocksera_view.cost_to_borrow("TSLA")

View File

@@ -1,7 +1,7 @@
load load a specific stock ticker for analysis [YahooFinance, IEXCloud, AlphaVantage, Polygon, EODHD]
shorted show most shorted stocks [YahooFinance]
ctb stocks with highest cost to borrow [InteractiveBrokers]
ctb cost to borrow of stocks [ibkr, stocksera]
hsi show top high short interest stocks of over 20% ratio [Shortinterest]
prom promising tickers based on dark pool shares regression [FINRA]
pos dark pool short position [Stockgrid]

View File

@@ -6,10 +6,13 @@ Request a list of stocks that have the highest cost to borrow [Source: Interacti
```
optional arguments:
-n NUM, --num NUM Number of the stocks with high cost to borrow to retrieve. (default: 20)
--export {csv,json,xlsx}
Export dataframe data to csv,json,xlsx file
-n NUMBER, --number NUMBER
Number of records to retrieve. (default: 20)
--raw Print raw data. (default: False)
-h, --help show this help message (default: False)
--export EXPORT Export raw data into csv, json, xlsx (default: )
--source {ibkr,stocksera}
Data source to select from (default: ibkr)
```
Example: