Merge pull request #15 from KIC/feature/0.2.1

Feature/0.2.1

Author: KIC

.en-custom.txt

@@ -0,0 +1,95 @@
+1ntegration
+DataFrame
+Dolthub
+FeaturesAndLabels
+FittingParameter
+MultiIndex
+PyCharm
+PyMC
+Quant
+Readme
+Utils
+adx
+apache
+apo
+args
+arma
+atr
+bband
+bbands
+cci
+coeff
+covariance
+covariances
+csv
+culb
+dolthub
+dulthubs
+ema
+empyrical
+ewma
+fibbonaci
+gaf
+garch
+gasf
+geodata
+gif
+github
+gld
+gramian
+inotify
+investpy
+keras
+kic
+kwargs
+macd
+mgarch
+modelling
+ncdf
+normalizer
+nox
+ntegration
+numpy
+ohl
+osc
+png
+ppo
+pytorch
+pytrends
+quant
+quantdb
+quantile
+readme
+realative
+regressors
+reparameterization
+resample
+rescale
+ret
+retracement
+rl
+rnn
+roc
+rsi
+sarimax
+scalers
+scalings
+scikit
+sharpe
+shiller
+sma
+sortino
+stddev
+submodules
+tensorflow
+timeseries
+tox
+trix
+txt
+unnesting
+unreproducible
+utils
+wilders
+williams
+yfinance
+zscore

.github/workflows/spellcheck.yml

@@ -0,0 +1,30 @@
+name: spellcheck
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    branches: [ master ]
+
+jobs:
+  spelling:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v1
+    - name: Set up Python 3.7
+      uses: actions/setup-python@v1
+      with:
+        python-version: 3.7
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip setuptools
+        python -m pip install pyspelling pymdown-extensions
+        # Install any additional libraries required: additional plugins, documentation building libraries, etc.
+    - name: Install Aspell
+      run: |
+        sudo apt-get install aspell aspell-en
+    #- name: Build documents
+    #  run:  ... Perform any documentation building that might be required ..
+    - name: Spell check
+      run: |
+        python -m pyspelling

.gitignore

@@ -26,3 +26,4 @@ streamlit_apps/streamlit/models/
 *outnb
 /.run/fetch_optionable_stocks (dolt).run.xml
 /todo.md
+*.egg-info

.pyspelling.yml

@@ -0,0 +1,39 @@
+spellchecker: aspell
+
+matrix:
+- name: markdown
+  sources:
+  - ./**/*eadme.md
+  aspell:
+    lang: en
+    d: en_US
+  dictionary:
+    wordlists:
+    - .en-custom.txt
+    output: /tmp/build/dictionary/mkdocs.dic
+  pipeline:
+  - pyspelling.filters.markdown:
+      markdown_extensions:
+        - pymdownx.superfences:
+  - pyspelling.filters.html:
+      comments: false
+      attributes:
+        - title
+        - alt
+      ignores:
+        - code
+        - pre
+  - pyspelling.filters.context:
+      context_visible_first: true
+      escapes: '\\[\\`]'
+      delimiters:
+      # Ignore multiline content between fences (fences can have 3 or more back ticks)
+      # ```
+      # content
+      # ```
+      - open: '(?s)^(?P<open> *`{3,})(.*)$'
+        close: '^(?P=open)$'
+      # Ignore text between inline back ticks
+      - open: '(?P<open>`+)'
+        close: '(?P=open)'
+  - pyspelling.filters.url:

Readme.md

@@ -3,15 +3,16 @@
 [![Python
 3.8](https://img.shields.io/badge/python-3.8-blue.svg)](https://www.python.org/downloads/release/python-360/)
 [![NOX Tests Status](https://github.com/KIC/pandas-ml-quant/workflows/NOX-Tests/badge.svg)](https://github.com/KIC/pandas-ml-quant/actions)
+[![Spelling](https://github.com/KIC/pandas-ml-quant/workflows/spellcheck/badge.svg)](https://github.com/KIC/pandas-ml-quant/actions)
 
 Whether it is some statistical analysis or machine learning, most likely it all starts with a `DataFrame`.
 But soon enough you will find yourself converting your data frames to numpy, splitting arrays, applying min
 max scalers, lagging and concatenating columns etc. As a result your notebook looks messy and became and 
 unreadable beast. Yet the mess becomes only worse once you start to deploy your research into a productive
 application. Now the untested hard coded data pipelines need to be maintained at two places. 
 
-The aim of this library is to conveniently operate with data frames without and abstract away the ugly un-
-reproducible data pipelines. The only thing you need is the original unprocessed data frame where you started.
+The aim of this library is to conveniently operate with data frames without and abstract away the ugly unreproducible
+data pipelines. The only thing you need is the original unprocessed data frame where you started.
 
 ![Fitting Example](.readme/videos/probabilistic-model-fit.gif)
 You find this demo in the pytorch [examples](./pandas-ml-utils-torch/examles/)<br><br>
@@ -39,7 +40,7 @@ option to move the modules into their own repository in the future if there will
 
 The submodules are:
  * pandas-ml-1ntegration-test  more complex tests involving several modules and eventually external data
- * pandas-ml-airflow  very experimental module to integrate models within apache airflow 
+ * pandas-ml-airflow  a very experimental module to integrate models within apache airflow 
  * pandas-ml-common  functionalities around data access and preparation like train/test splitting, cross validation, ...   
  * pandas-ml-quant  enhancing pandas-ml-utils for modeling financial timeseries
  * pandas-ml-quant-rl  very experimental module for reinforcement learning
@@ -53,7 +54,7 @@ The submodules are:
 ### [pandas-ml-common](pandas-ml-common/Readme.md)
 This module contains helpers and utilities for the most common tasks like:
 * splitting data and generation of cross validation data sets
-* nesting and un-nesting of multi dimensional column data like images or geo data
+* nesting and unnesting of multi dimensional column data like images or geodata
 * helpers for pandas `MultiIndex`es 
 * dependency injection
 * data serialization 
@@ -95,7 +96,7 @@ with df.model('file_name') as m:
 fit  # finally just return fit as the `Fit` object implements `_repr_html_()` which renders a nice report
 ```
 
-But before a model can be developed features need to be selected. 
+Before a model can be developed, features need to be selected. 
 ```python
 df.model.feature_selection(
     FeaturesAndLabels(
@@ -105,11 +106,11 @@ df.model.feature_selection(
 )
 ```
 
-Check this demo from the [exmaples](./pandas-ml-utils/examles/):
+Check this demo from the [examples](./pandas-ml-utils/examles/):
 
 ![Classification Example](.readme/images/classification.png)
 
-### [pandas-ml-utils-toch](pandas-ml-utils-torch/Readme.md)
+### [pandas-ml-utils-torch](pandas-ml-utils-torch/Readme.md)
 Extends the pandas-ml-utils library for the use of pytorch models
 
 ### [pandas-ml-utils-keras](pandas-ml-utils-keras/Readme.md)
@@ -130,14 +131,14 @@ Charting library
 ![Ta Plot](./.readme/videos/ta_plot.gif)
 
 ### [pandas-ml-quant-data-provider](pandas-quant-data-provider/Readme.md) 
-This is maily a wrapper around data providing libraries [yfinance](https://github.com/ranaroussi/yfinance) 
+This is mainly a wrapper around data providing libraries [yfinance](https://github.com/ranaroussi/yfinance) 
 or [investing](https://github.com/alvarobartt/investpy)
 
 ### Testing and experiments
 There are some more not published libraries used for testing and experiments.
 
 ## Installation
-Currently all libraries are somewhat entangled and will hike parallel the releases cycles. This dependency will weaken up
+Currently, all libraries are somewhat entangled and will hike parallel the releases cycles. This dependency will weaken up
 as we reach more stable release. 
 
 ```bash

bump_version.sh

@@ -7,11 +7,11 @@ ABSOLUTE_PATH="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
 TOX_FILES=$(find "$ABSOLUTE_PATH" -name tox.ini)
 echo "$TOX_FILES"
 
-# replace __version__ = '0.2.0' in all setup.py files
+# replace __version__ = '0.2.1' in all setup.py files
 SETUP_FILES=$(find "$ABSOLUTE_PATH" -regex ".*/pandas-ml-[a-z\-]+/setup\.py")
 echo "$SETUP_FILES"
 
-# replace __version__ = '0.2.0' in all pandas_ml_*/__init__.py files
+# replace __version__ = '0.2.1' in all pandas_ml_*/__init__.py files
 INIT_FILES=$(find "$ABSOLUTE_PATH" -regex ".*/pandas-ml-[a-z\-]+/pandas_ml_[a-z_]+/__init__\.py")
 echo "$INIT_FILES"
 

nox_all.sh

@@ -31,6 +31,9 @@ run_tests "pandas-ml-quant"
 run_tests "pandas-quant-data-provider"
 run_tests "pandas-ml-1ntegration-test"
 
+# run spellchecker
+pyspelling
+
 # TODO run private integration tests as nox tests as well
 # TODO finalize remaining tox tests: pandas-quant-data-provider, pandas-ml-1ntegration-test, quant plot
 #   cd "$ABSOLUTE_PATH/pandas-quant-data-provider" && tox && echo "done $(pwd)" && cd - || exit

pandas-ml-1ntegration-test-private

@@ -1,4 +1,4 @@
-__version__ = '0.2.0'
+__version__ = '0.2.1'
 
 import os
 import shutil

pandas-ml-1ntegration-test/noxfile.py

@@ -1,5 +1,5 @@
 """Augment pandas DataFrame with methods to fetch time series data for quant finance"""
-__version__ = '0.2.0'
+__version__ = '0.2.1'
 
 import os