From 78246d200e5bd2010ab0ed7ebcd753e3530fe2fc Mon Sep 17 00:00:00 2001
From: Urban Ottosson <urban@ottosson.org>
Date: Thu, 15 Jul 2021 14:43:29 +0200
Subject: [PATCH] Initial version

---
 pandas_ta/custom.py | 132 ++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 132 insertions(+)
 create mode 100644 pandas_ta/custom.py

diff --git a/pandas_ta/custom.py b/pandas_ta/custom.py
new file mode 100644
index 0000000..d3f0a09
--- /dev/null
+++ b/pandas_ta/custom.py
@@ -0,0 +1,132 @@
+# -*- coding: utf-8 -*-
+
+import os
+import sys
+from os.path import dirname, abspath, join
+from glob import glob
+import importlib
+import pandas_ta
+
+def import_dir(dir_path, create_categories=True, verbose=True):
+
+    # ensure that the passed directory exists / is readable
+    if not os.path.exists(dir_path):
+        print(f"[X] Unable to read the directory '{dir_path}'.")
+        return
+   
+    # list the contents of the directory
+    dirs = glob(abspath(join(dir_path, '*')))
+
+    # optionally add any missing category subdirectories
+    if create_categories:
+        for sd in [*pandas_ta.Category]:
+            d = abspath(join(dir_path, sd)
+            if not os.path.exists(d):
+                os.makedirs(directory
+
+    # traverse the directory, importing all modules found there
+    for d in dirs:
+        dirname = os.path.basename(d)
+
+        if dirname not in [*pandas_ta.Category]:
+            print(f"[i] Skipping the sub-directory '{dirname}' since it's not a pandas_ta category.")
+            continue
+
+        for module in glob(abspath(join(dir_path, dirname, '*.py'))):
+            module = os.path.splitext(os.path.basename(module))[0]
+
+            if module in pandas_ta.Category[dirname]:
+                print(f"[X] Skipping the custom module '{module}' since a function with that name already exists in pandas_ta.")
+                continue
+
+            # import the module and add it to the correct category
+            pandas_ta.Category[dirname].append(module)
+            if d not in sys.path:
+                sys.path.append(d) 
+            importlib.import_module(module, d)
+
+            if verbose:
+                print(f"[i] Successfully imported the module '{module}' into category '{dirname}'.")
+
+import_dir.__doc__ = \
+"""
+This method allows you to experiment and develop your own technical analysis
+indicators independantly in a separate local directory of your choice but
+still use them seamlessly together with the existing pandas_ta functions just 
+like if they were part of pandas_ta.
+
+If you at some late point would like to push them into the pandas_ta library
+you can do so very easily by following the step by step instruction here
+https://github.com/twopirllc/pandas-ta/issues/264.
+
+----------------------------------
+
+By default, the 'ta' extension uses lower case column names: open, high,
+low, close, and volume. You can override the defaults by providing the it's
+replacement name when calling the indicator. For example, to call the
+indicator hl2().
+
+With 'default' columns: open, high, low, close, and volume.
+>>> df.ta.hl2()
+>>> df.ta(kind="hl2")
+
+With DataFrame columns: Open, High, Low, Close, and Volume.
+>>> df.ta.hl2(high="High", low="Low")
+>>> df.ta(kind="hl2", high="High", low="Low")
+
+If you do not want to use a DataFrame Extension, just call it normally.
+>>> sma10 = ta.sma(df["Close"]) # Default length=10
+>>> sma50 = ta.sma(df["Close"], length=50)
+>>> ichimoku, span = ta.ichimoku(df["High"], df["Low"], df["Close"])
+
+Args:
+    kind (str, optional): Default: None. Kind is the 'name' of the indicator.
+        It converts kind to lowercase before calling.
+    timed (bool, optional): Default: False. Curious about the execution
+        speed?
+    kwargs: Extension specific modifiers.
+        append (bool, optional): Default: False. When True, it appends the
+        resultant column(s) to the DataFrame.
+
+Returns:
+    Most Indicators will return a Pandas Series. Others like MACD, BBANDS,
+    KC, et al will return a Pandas DataFrame. Ichimoku on the other hand
+    will return two DataFrames, the Ichimoku DataFrame for the known period
+    and a Span DataFrame for the future of the Span values.
+
+Let's get started!
+
+1. Loading the 'ta' module:
+>>> import pandas as pd
+>>> import ta as ta
+
+2. Load some data:
+>>> df = pd.read_csv("AAPL.csv", index_col="date", parse_dates=True)
+
+3. Help!
+3a. General Help:
+>>> help(df.ta)
+>>> df.ta()
+3b. Indicator Help:
+>>> help(ta.apo)
+3c. Indicator Extension Help:
+>>> help(df.ta.apo)
+
+4. Ways of calling an indicator.
+4a. Standard: Calling just the APO indicator without "ta" DataFrame extension.
+>>> ta.apo(df["close"])
+4b. DataFrame Extension: Calling just the APO indicator with "ta" DataFrame extension.
+>>> df.ta.apo()
+4c. DataFrame Extension (kind): Calling APO using 'kind'
+>>> df.ta(kind="apo")
+4d. Strategy:
+>>> df.ta.strategy("All") # Default
+>>> df.ta.strategy(ta.Strategy("My Strat", ta=[{"kind": "apo"}])) # Custom
+
+5. Working with kwargs
+5a. Append the result to the working df.
+>>> df.ta.apo(append=True)
+5b. Timing an indicator.
+>>> apo = df.ta(kind="apo", timed=True)
+>>> print(apo.timed)
+"""