Random stock quotes generator based on real data distribution
Project description
rndqts
Random stock market quotes
Installation
as a standalone lib.
# Set up a virtualenv.
python3 -m venv venv
source venv/bin/activate
# Install from PyPI...
pip install --upgrade pip
pip install -U rndqts
# ...or, install from updated source code.
pip install git+https://github.com/davips/rndqts
as an editable lib inside your project.
cd your-project
source venv/bin/activate
git clone https://github.com/davips/rndqts ../rndqts
pip install --upgrade pip
pip install -e ../rndqts
Examples
Fetching from Yahoo
from rndqts import Real
print(Real("VALE3.sa").data)
"""
Fetching VALE3.sa ...
[*********************100%***********************] 1 of 1 completed
Open High Low Close Volume
Date
2020-12-01 79.830002 81.500000 79.250000 81.250000 61441200
2020-12-02 80.900002 81.250000 77.309998 79.839996 53703300
2020-12-03 81.000000 81.050003 78.610001 78.959999 35158600
2020-12-04 80.099998 82.680000 80.099998 82.269997 38441000
2020-12-07 82.419998 82.989998 81.669998 82.949997 27398500
2020-12-08 82.970001 83.300003 81.660004 82.900002 28598800
2020-12-09 83.099998 83.830002 82.220001 82.699997 26938500
2020-12-10 83.650002 85.220001 83.199997 85.000000 41230700
2020-12-11 84.620003 85.279999 84.400002 84.760002 17825100
2020-12-14 85.199997 85.220001 82.949997 83.550003 20931700
2020-12-15 83.550003 85.379997 83.550003 84.500000 18762800
2020-12-16 84.900002 86.230003 84.360001 86.220001 23038300
2020-12-17 86.500000 87.949997 86.169998 87.199997 21367800
2020-12-18 87.620003 88.349998 87.430000 88.190002 13534400
2020-12-21 86.150002 87.400002 84.779999 86.860001 31877300
2020-12-22 86.860001 86.989998 85.430000 86.940002 23157000
2020-12-23 86.529999 87.529999 86.400002 87.360001 17710200
2020-12-28 87.790001 88.580002 87.080002 87.309998 26001300
2020-12-29 87.970001 88.199997 86.510002 87.070000 19727500
2020-12-30 87.190002 87.589996 86.650002 87.449997 30102700
"""
Random stock quotes
from rndqts import Realistic
from rndqts import Real
# Real quotes to fetch from Yahoo.
r1 = Real("PETR4.sa")
r2 = Real("CSNA3.sa")
r3 = Real("VALE3.sa")
r4 = Real("USIM5.sa")
# Generating random quotes.
print(Realistic([r1, r2, r3, r4]).data)
"""
Fetching PETR4.sa ...
[*********************100%***********************] 1 of 1 completed
Fetching CSNA3.sa ...
[*********************100%***********************] 1 of 1 completed
Fetching USIM5.sa ...
[*********************100%***********************] 1 of 1 completed
Open High Low Close Volume
Date
0 99.82 100.73 99.13 99.18 12499
1 101.52 109.90 101.52 109.59 15623
2 109.51 112.20 105.65 111.46 11805
3 111.59 112.56 110.18 110.30 10416
4 110.80 111.08 109.94 110.61 13019
... ... ... ... ... ...
147 92.05 93.28 92.05 92.82 5
148 92.34 94.85 92.32 94.16 5
149 93.27 97.09 91.75 93.43 7
150 93.76 97.64 92.09 96.71 7
151 96.71 104.32 96.71 100.05 9
[152 rows x 5 columns]
"""
Saving as a CSV file
from rndqts import Real
Real("VALE3.sa").data.to_csv("/tmp/myfile.csv")
Plotting
from rndqts import Real
Real("VALE3.sa").plot()
"""
Fetching VALE3.sa ...
[*********************100%***********************] 1 of 1 completed
"""
Features / TODO
-
Fetch from yahoo
-
Automatic local caching
-
Slicing
-
Plot candle sticks
-
Realistic random quotes
- Ticker 'pseudo' generates (not so realistic) data without real quotes dependence (good for tests)
-
Distinct kinds of quotes: Real, Realistic random, Synthetic Random
-
Cacheable and identified by hash of args
-
Real (market quotes)
-
Realistic (realistic random quotes, .i.e, it is based on real quotes)
-
Synthetic (quotes based interily on Gaussian distributions from pseudo random number generator)
- Lazy/Infinite
-
-
News fetching
Project details
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