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Fix for 0.1.1
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README.md

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</picture>
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</div>
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# pypredictor
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# pypredictor 0.1.1
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<p>
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<img src="https://img.shields.io/badge/Python-3.8 | 3.9 | 3.10 | 3.11 -blue.svg" alt="py versions">
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<img src="https://img.shields.io/badge/PyPi package-0.1.0-green.svg" alt="pypi version">

examples/example_numgraph.ipynb

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],
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"source": [
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"\"\"\"\n",
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"pypredictor 0.1.0\n",
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"pypredictor 0.1.1\n",
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"\n",
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"© Hamd Waseem under the Apache Licence 2.0\n",
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"\n",

examples/example_numpredict.py

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"""
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pypredictor 0.1.0
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pypredictor 0.1.1
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© Hamd Waseem under the Apache Licence 2.0
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pypredictor/__init__.py

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"""
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pypredictor 0.1.0
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pypredictor 0.1.1
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© Hamd Waseem under the Apache Licence 2.0
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__init__.py - initialisation
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The Python library that makes AI predictions simple.
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"""
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__version__ = "0.1.0"
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__version__ = "0.1.1"

pypredictor/_exceptions.py

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"""
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pypredictor 0.1.0
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pypredictor 0.1.1
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© Hamd Waseem under the Apache Licence 2.0
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pypredictor/numgraph.py

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"""
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pypredictor 0.1.0
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pypredictor 0.1.1
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© Hamd Waseem under the Apache Licence 2.0
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import pandas as pd
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import matplotlib.pyplot as plt
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import seaborn as sns
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import numpredict
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import _exceptions
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from . import numpredict
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from . import _exceptions
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class NumGraph:
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""" Base class for generating seaborn plots. """

pypredictor/numpredict.py

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"""
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pypredictor 0.1.1
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import logging
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import numpy as np
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import pandas as pd
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import _exceptions
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from . import _exceptions
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from tensorflow.keras.models import Sequential
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from tensorflow.keras.layers import Dense, LSTM
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pypredictor/tests/numpredict_tests.py

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"""
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pypredictor 0.1.0
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pypredictor 0.1.1
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© Hamd Waseem under the Apache Licence 2.0
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pypredictor/tests/pypredictor_test_setup.py

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"""
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pypredictor 0.1.0
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pypredictor 0.1.1
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© Hamd Waseem under the Apache Licence 2.0
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setup.py

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from setuptools import setup, find_packages
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VERSION = '0.1.0'
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DESCRIPTION = 'A Python library that can predict the next values in a list.'
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LONG_DESCRIPTION = 'A Python library that can predict the next values in a list. (long desc here)'
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VERSION = '0.1.1'
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DESCRIPTION = 'The Python library that makes AI predictions simple.'
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LONG_DESCRIPTION = """
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<div align="center">
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<picture>
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<source media="(prefers-color-scheme: dark)" srcset="https://github.com/hamdivazim/pypredictor/raw/main/logo_dark.png">
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<img src="https://github.com/hamdivazim/pypredictor/raw/main/logo.png" alt="pypredictor logo">
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</picture>
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</div>
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# pypredictor
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<p>
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<img src="https://img.shields.io/badge/Python-3.8 | 3.9 | 3.10 | 3.11 -blue.svg" alt="py versions">
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<img src="https://img.shields.io/badge/PyPi package-0.1.0-green.svg" alt="pypi version">
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<img src="https://img.shields.io/badge/License-Apache License 2.0-green.svg" alt="license">
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<img src="https://img.shields.io/badge/Libraries-tensorflow | numpy | seaborn | pandas-green.svg" alt="libs">
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</p>
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The Python library that makes AI predictions simple.
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### View the [GitHub Page](https://github.com/hamdivazim/pypredictor)
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## What can it do?
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pypredictor uses an RNN (Recurrent Neural Network) to predict the next n numbers in a sequence. As an example, using this code:
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```python
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pred = NumPredictor(500)
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print(pred.predict([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 5, 3))
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```
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pypredictor generated the following output, which is quite accurate:
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```
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[10.969043, 11.950292, 12.920968, 13.859894, 14.789316]
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```
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pypredictor also has the ability to generate a pandas DataFrame and a seaborn line graph, from an initial sequence/DataFrame which you provide.
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###
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Plus, there are examples in the `examples/` directory, so you can take a look for yourself :)
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## How to install
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Install via pip:
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```
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$ pip install pypredictor
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```
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To get examples, clone this repository and enter `pypredictor/examples`:
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```
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$ git clone https://github.com/hamdivazim/pypredictor.git
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$ cd pypredictor/examples
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```
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anaconda support hopefully coming soon!
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## License
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pypredictor is licensed by Hamd Waseem (codingboy_CW) under [the Apache License 2.0](https://github.com/hamdivazim/pypredictor/blob/main/LICENSE).
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"""
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setup(
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name="pypredictor",

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