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Updated installation instructions (#470)
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README.md

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You can install the library by running the following command,
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```python
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python -m pip install .
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python scripts/build/install.py
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```
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For development purposes, you can use the option `e` as shown below,
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For development purposes i.e., if you intend to be a contributor,
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```python
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python -m pip install -e .
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python scripts/build/develop.py
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```
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In the above commands, `.` in the end means the current directory. So, make sure you change your working directory

docs/source/index.rst

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Welcome to PyDataStructs's documentation!
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=========================================
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This project aims to be a Python package for various data
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structures in computer science. We are also working on the
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development of algorithms including their parallel implementations.
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To the best of our knowledge, a well-designed library/package which
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This project aims to be a Python package for various data
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structures in computer science. We are also working on the
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development of algorithms including their parallel implementations.
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To the best of our knowledge, a well-designed library/package which
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has covered most of the data structures and algorithms doesn't exist yet.
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Once the software design becomes more stable after a few releases of
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this package in the near future, we also aim to provide APIs for the
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Once the software design becomes more stable after a few releases of
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this package in the near future, we also aim to provide APIs for the
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code in C++ and Java as well.
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.. note::
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Installation
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============
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After changing your directory to project root, you can
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After changing your directory to project root, you can
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install the package by running the following command,
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``python -m pip install .``
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``python scripts/build/install.py``
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For development purposes, you can use the option `e` as shown below,
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For development purposes, i.e., if you intend to be a contributor,
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``python -m pip install -e .``
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``python scripts/build/develop.py``
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For building documentation execute the following commands one after
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the other,
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Why do we use Python?
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=====================
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As we know Python is an interpreted language and hence is
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slow compared to C++, the most popular language for competitive programming.
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We still decided to use Python because the software development can happen
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at a much faster pace and it is much easier to test various software designs
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and APIs as coding them out takes no time. However, keeping the need of the
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users in mind, we will shift to C++ backend, which will happen quickly as
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we would be required to just translate the tested code rather than writing it
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As we know Python is an interpreted language and hence is
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slow compared to C++, the most popular language for competitive programming.
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We still decided to use Python because the software development can happen
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at a much faster pace and it is much easier to test various software designs
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and APIs as coding them out takes no time. However, keeping the need of the
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users in mind, we will shift to C++ backend, which will happen quickly as
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we would be required to just translate the tested code rather than writing it
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from scratch, after a few releases with APIs available for all the languages.
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