Add ability to run this project in Docker

Dockerfile

@@ -0,0 +1,17 @@
+FROM python:3
+
+RUN pip install --upgrade pip && \
+    pip install --no-cache-dir nibabel pydicom matplotlib pillow && \
+    pip install --no-cache-dir med2image
+
+# As per https://docs.docker.com/develop/develop-images/dockerfile_best-practices/
+
+COPY requirements.txt /tmp
+RUN pip install --requirement /tmp/requirements.txt
+COPY . /tmp/
+
+RUN mkdir /opt/wsb/
+COPY grapher.py market_scanner.py stocklist.py /opt/wsb/
+
+RUN mkdir /opt/wsb/data
+COPY data /opt/wsb/data

README.md

@@ -2,24 +2,50 @@
 
 This scans every ticker on the market, gets their last 5 months of volume history, and alerts you when a stock's volume exceeds 10 standard deviations from the mean within the last 3 days. (these numbers are all adjustable).  Helps find anomalies in the stock market
 
+## [Website Link!](http://165.22.228.6/ ):
 
-## How to run this:
+[credit!](https://www.reddit.com/r/wallstreetbets/comments/i10mif/i_made_a_website_for_that_scanner_made_by_that/)
 
--download your favorite Python IDE. (I use VSCode)
 
--get my script from GitHub
+## Requirements
 
--open the script in your IDE and install all required dependancies by typing pip install -r requirements.txt into the IDE's terminal. You can get to the the terminal on VSC by pressing CMD and ` at the same time.
+Docker - install Docker https://docs.docker.com/get-docker/
 
--run the market_scanner.py and it will print out results into the terminal
--you can also graph any ticker's volume in grapher.py
+Alternatively,
+
+1) download your favorite Python IDE. (For example, the project creator uses VSCode)
+
+2) Clone project from GitHub
+
+3) Open project in your IDE and install all required dependancies by typing pip install -r requirements.txt into the IDE's terminal. You can get to the the terminal on VSC by pressing CMD and ` at the same time.
+
+## How to run
+Build docker image by running commands below, from the same directory as Dockerfile.
+<pre>
+docker build --tag NAME:VERSION . ie docker build --tag wsb:1.0 .
+</pre>
+You will be presented with a message
+<pre>
+Successfully built ID
+Successfully tagged wsb:1.0
+</pre>
+Then run
+<pre>
+docker run  -ti ID bash
+Once inside
+python /opt/wsb/market_scanner.py
+</pre>
+
+Alternatively,
+1) run the market_scanner.py and it will print out results into the terminal
+2) you can also graph any ticker's volume in grapher.py
 
 ## Controlling the Script
--Line 17 controls the amount of months of historical volume the script gets
+Line 17 controls the amount of months of historical volume the script gets
 
--Line 75 controls the amount of days before today that it will alert you
+Line 75 controls the amount of days before today that it will alert you
 
--Line 84 controls the number of standard deviations away from the mean volume
+Line 84 controls the number of standard deviations away from the mean volume
 
 
 

market_scanner.py

@@ -9,9 +9,6 @@
 from stocklist import NasdaqController
 from tqdm import tqdm
 
-from joblib import Parallel, delayed
-import multiprocessing
-
 
 class mainObj:
     def getData(self, ticker):
@@ -65,21 +62,18 @@ def days_between(self, d1, d2):
         d2 = datetime.datetime.strptime(d2, "%Y-%m-%d")
         return abs((d2 - d1).days)
 
-    def parallel_wrapper(self,x, cutoff, currentDate):
-        d = (self.find_anomalies_two(self.getData(x), cutoff))
-        if d['Dates']:
-            for i in range(len(d['Dates'])):
-                if self.days_between(str(currentDate)[:-9], str(d['Dates'][i])) <= 3:
-                    self.customPrint(d, x)
-
     def main_func(self, cutoff):
         StocksController = NasdaqController(True)
         list_of_tickers = StocksController.getList()
         currentDate = datetime.datetime.strptime(
             date.today().strftime("%Y-%m-%d"), "%Y-%m-%d")
         start_time = time.time()
-
-        Parallel(n_jobs=multiprocessing.cpu_count())(delayed(self.parallel_wrapper)(x, cutoff, currentDate) for x in tqdm(list_of_tickers) )
+        for x in tqdm(list_of_tickers):
+            d = (self.find_anomalies_two(self.getData(x), cutoff))
+            if d['Dates']:
+                for i in range(len(d['Dates'])):
+                    if self.days_between(str(currentDate)[:-9], str(d['Dates'][i])) <= 3:
+                        self.customPrint(d, x)
 
         print("\n\n\n\n--- this took %s seconds to run ---" %
               (time.time() - start_time))

requirements.txt

@@ -5,4 +5,3 @@ numpy==1.18.4
 mplcursors==0.3
 python_dateutil==2.8.1
 tqdm==4.48.0
-joblib

stocklist.py

@@ -47,8 +47,7 @@ def __init__(self, update=True):
 
                     line = line.strip().split("|")
 
-                    #line[6] and line[4] is for ETFs. Let's skip those to make this faster.
-                    if line[0] == "" or line[1] == "" or (filename == 'nasdaqlisted' and line[6] == 'Y') or (filename == 'otherlisted' and line[4] == 'Y'):
+                    if line[0] == "" or line[1] == "":
                         continue
 
                     all_listed.write(line[0] + ",")