1 USING PYCHARM, PYLINT, PYTEST, AND VCS TO DESIGN A ...
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USING PYCHARM, PYLINT, PYTEST, AND VCS TO DESIGN A PROJECT PIPELINE
Antonio Luca Alfeo
2
OVERVIEW
1.
Installation
2.
Work with Pycharm projects
I.
Configure the interpreter
II.
Requirements management
III.
Project navigation and run
3.
Code quality checking
I.
Pylint
II.
Plugin installation and usage
8.
Python basics to design a structured project pipeline
I.
Tabular data with pandas.dataframes
II.
Dataframe manipulation
III.
Data segregation with Sklearn
IV.
Model hyperarametrization
V.
From JSON to Object
VI.
Performance evaluation
VII.
Model deployment
VIII. Project profiling
4.
Code correctness checking
9.
Recap and more resources
I.
Enabling and configuring Pytest in Pycharm
II.
Testing methods and usage
10. Exercise
5.
Version Control on Pycharm
I.
Local history
II.
Connect to GitHub
III.
Github: share a project
IV.
Github: commit and push
V.
Github: clone a project
6.
Recap and more resources
7.
Exercise
3
INSTALLATION
4
INSTALLATION 1/3
1. Install Git using only the default settings in the installation process
?
2. Install PyCharm
? Linux ->
? Windows ->
? MacOs ->
5
INSTALLATION 2/3
During PyCharm installation enable "open folder as project"
6
INSTALLATION 3/3
? Accept the JetBrains Privacy Policy
? Choose the UI theme you prefer
? Do not install any featured plugin
? Install Miniconda: includes the conda environment manager, Python, the packages they depend on, and a small number of other useful packages (e.g. pip).
? Start using PyCharm
7
WORK WITH PYCHARM PROJECTS
8
OPEN A PROJECT
1. Unzip "simpleClassifier.rar" 2. Open the resulting folder "as a
PyCharm project"
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