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algovis-0.1.6
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مشاهده بیشترتوضیحات
A Python library for visualising algorithms
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | algovis-0.1.6 |
| نام | algovis |
| نسخه کتابخانه | 0.1.6 |
| نگهدارنده | ['hotshot07'] |
| ایمیل نگهدارنده | ['aroram@tcd.ie'] |
| نویسنده | hotshot07 |
| ایمیل نویسنده | aroram@tcd.ie |
| آدرس صفحه اصلی | https://github.com/hotshot07/algovis |
| آدرس اینترنتی | https://pypi.org/project/algovis/ |
| مجوز | AGPL-3.0 |
[](https://www.codefactor.io/repository/github/hotshot07/algovis/overview/master)   [](https://pepy.tech/project/algovis) <!--  -->    [](https://mackweb.in) [](https://twitter.com/elonmusk)
Algovis is a python library made for visualizing algorithms. Refer to the [documentation](https://algovisdocs.netlify.app/) for more info.
Currently the library has these algorithms
#### Sorting
- Bubble Sort
- Insertion Sort
- Selection Sort
- Merge Sort
- Quick Sort
#### Searching
- Linear Search
- Binary Search
## Getting Started
### Prerequisites
I would highly suggest making a virtual environment. The main purpose of a Python virtual environments is to create an isolated environment for Python projects. You can read more about them [here](https://realpython.com/python-virtual-environments-a-primer/).
```bash
# making a test folder
$mkdir test_algovis
# make it the current directory
$cd test_algovis
# making a virtual environment (you can replace envname with whatever name you like)
$python3 -m venv envname
# activating it
$source envname/bin/activate
```
You can only access algovis inside this virtual environment. To leave this virtual env when you're done trying out the library, type
```bash
$deactivate
```
### Installing
```bash
$pip3 install algovis
```
### Using the sorting package
#### Visualize method
```python
# import the sorting package from library
from algovis import sorting
# importing random module to shuffle the list
import random
# Making a list of 100 integers from 1-100
# using list comprehension
my_list = [i+1 for i in range(100)]
# shuffling the list
random.shuffle(my_list)
# making a BubbleSort class object by passing the shuffled list
bs_object = sorting.BubbleSort(my_list)
# calling the visualize method
bs_object.visualize(interval= 100)
```
##### Output
<img src="https://media.giphy.com/media/ieb13rrmvVWC02zmI8/giphy.gif" width="600">
#### sort method
```python
# lets work on a shorter example now
my_list = [i + 1 for i in range(10)]
# shuffling the list using random module
random.shuffle(my_list)
#making a quicksort object
qs_object = sorting.QuickSort(my_list)
#sorting in reverse with steps
qs_object.sort(pivot = "first", steps = True, reverse = True)
```
#### evaluate method
```python
# calling the evaluate method and passing the optional parameter 'iterations'
# the list is sorted 'iterations' number of times and the min, max and average time taken
#to sort the list is returned in form of a formatted table
bs_object.evaluate(iterations = 100)
```
#### info method
```python
# This method gives us information about the algorithm
bs_object.info()
```
#### code method
```python
# It prints out the function for the algorithm
bs_object.code()
```
>My terminal config is iTerm2 + ohmyzsh + powerlevel10k with dark backgroud. Colors may appear different in your terminal output. It's recommended to change the terminal color to something darker
### Using the searching package
>The searching package has the same methods as sorting, just instead of 'sort' you have 'search'
>Refer to the [documentation](https://algovisdocs.netlify.app/) for more info
#### search method
```python
#importing searching package
from algovis import searching
# making a list of integers from 1 to 100
# using list comprehension
my_list = [i+1 for i in range(100)]
#making binary search object
bin_search = searching.BinarySearch(my_list)
#calling the search method
bin_search.search(42, steps = True)
```
#### visualize method
```python
# calling the visualize method
# interval is the time between two different frames of the animation
bin_search.visualize(42, interval = 1000)
```
<img src ="https://media.giphy.com/media/l3Cktj8ULcjHK3c90E/giphy.gif" width ="600">
```python
# or if you want to linear search 42
lin_search = searching.LinearSearch(my_list)
# setting a less interval to make a much faster animation
lin_search.visualize(42, interval = 100)
```
### Doumentation
The documentation is built with [MKdocs](https://www.mkdocs.org/) using [material](https://squidfunk.github.io/mkdocs-material/) theme and is hosted on netlify. You can read it [here](https://algovisdocs.netlify.app/)
### Author
* **Mayank Arora** *(hotshot07)*
### License
This project is licensed under the GNU Affero General Public License v3 (AGPL-3.0) - see the [LICENSE](LICENSE) file for details
نیازمندی
| مقدار | نام |
|---|---|
| >=3.2.1,<4.0.0 | matplotlib |
| >=3.3.1,<4.0.0 | rich |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7.0,<4.0.0 | Python |
نحوه نصب
نصب پکیج whl algovis-0.1.6:
pip install algovis-0.1.6.whl
نصب پکیج tar.gz algovis-0.1.6:
pip install algovis-0.1.6.tar.gz