tifft
Technical Indicators for Financial Trading
Installation
$ pip install -U tifft
Docker image
The image is available at Docker Hub.
$ docker image pull dceoy/tifft
Usage
Calculator Classes for Python
import numpy as np
from tifft.bollingerbands import BollingerBandsCalculator
from tifft.macd import MacdCalculator
from tifft.rsi import RsiCalculator
prices = np.random.randn(100) * 100
# MACD
macdc = MacdCalculator(fast_ema_span=12, slow_ema_span=26, macd_ema_span=9)
df_macd = macdc.calculate(values=prices)
print(df_macd)
# Bollinger Bands
bbc = BollingerBandsCalculator(window_size=20, sd_multiplier=2)
df_bb = bbc.calculate(values=prices)
print(df_bb)
# RSI
rsic = RsiCalculator(window_size=14, upper_line=70, lower_line=30)
df_rsi = rsic.calculate(values=prices)
print(df_rsi)
Command-line Tools
Fetch the historical data of DJIA, SP500, and NASDAQ100 from FRED (St. Louis Fed).
$ tifft history DJIA SP500 NASDAQ100
Fetch the data of SP500 from FRED and calculate the MACD.
$ tifft macd SP500
Fetch the data of SP500 from FRED and calculate the Bollinger Bands.
$ tifft bb SP500
Fetch the data of SP500 from FRED and calculate the RSI.
$ tifft rsi SP500
Run tifft --help for information.
Release files for tifft 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| tifft-0.1.2.tar.gz | 18.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| tifft-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 37.8 kB
Release files / tifft-0.1.2.tar.gz
| Download URL | tifft-0.1.2.tar.gz |
|---|---|
| Size | 18.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
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Release files / tifft-0.1.2-py3-none-any.whl
| Download URL | tifft-0.1.2-py3-none-any.whl |
|---|---|
| Size | 19.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.13
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