Python-100-Days

Python - 100天从新手到大师

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Quick Overview

Python-100-Days is a comprehensive learning resource for Python programming, designed as a 100-day course. It covers a wide range of topics from basic syntax to advanced concepts, including web development, data analysis, and machine learning, making it suitable for beginners and intermediate learners alike.

Pros

Extensive coverage of Python topics, from basics to advanced concepts
Structured learning path with daily lessons and exercises
Includes practical projects and real-world applications
Regularly updated with new content and improvements

Cons

May be overwhelming for absolute beginners due to the vast amount of information
Some topics might be covered too briefly for in-depth understanding
Primarily in Chinese, which may limit accessibility for non-Chinese speakers
The 100-day structure might not suit everyone's learning pace

Code Examples

This repository is not a code library but a learning resource, so code examples are not applicable in the context of using the repository as a library. However, the repository contains numerous code examples within its lessons and projects.

Getting Started

As this is not a code library but a learning resource, there's no specific installation or setup required. To get started:

Visit the repository: https://github.com/jackfrued/Python-100-Days
Clone or download the repository to your local machine
Follow the day-by-day structure, starting with Day 01
Read the lessons, complete the exercises, and work on the projects
Use the provided resources and links for additional learning materials

Note: Basic knowledge of Git and GitHub might be helpful for navigating and using the repository effectively.

Competitor Comparisons

ML-For-Beginners

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12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Pros of ML-For-Beginners

Comprehensive curriculum covering various ML topics
Hands-on approach with practical projects and quizzes
Well-structured lessons with clear learning objectives

Cons of ML-For-Beginners

Focuses solely on machine learning, not general Python programming
May be more challenging for absolute beginners
Requires some prior programming knowledge

Code Comparison

ML-For-Beginners:

from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
model = RandomForestClassifier(n_estimators=100, random_state=42)
model.fit(X_train, y_train)

Python-100-Days:

def bubble_sort(items):
    for i in range(len(items) - 1):
        for j in range(len(items) - 1 - i):
            if items[j] > items[j + 1]:
                items[j], items[j + 1] = items[j + 1], items[j]

The ML-For-Beginners repository provides a structured approach to learning machine learning concepts and techniques, while Python-100-Days offers a broader coverage of Python programming topics. ML-For-Beginners is more suitable for those specifically interested in machine learning, whereas Python-100-Days caters to a wider audience looking to learn Python from scratch and explore various applications.

javascript-algorithms

187,883

📝 Algorithms and data structures implemented in JavaScript with explanations and links to further readings

Pros of javascript-algorithms

Focuses specifically on algorithms and data structures, providing a deep dive into these topics
Includes implementations in multiple programming languages, not just JavaScript
Offers detailed explanations and complexity analysis for each algorithm

Cons of javascript-algorithms

Lacks a structured learning path or curriculum for beginners
Does not cover broader programming concepts or practical application development
May be overwhelming for those new to algorithms and data structures

Code Comparison

Python-100-Days (Day 7 example):

import random

word_list = ["ardvark", "baboon", "camel"]
chosen_word = random.choice(word_list)
display = ["_" for _ in chosen_word]

print(f"Pssst, the solution is {chosen_word}.")

javascript-algorithms (Binary Search example):

function binarySearch(sortedArray, seekElement) {
  let startIndex = 0;
  let endIndex = sortedArray.length - 1;

  while (startIndex <= endIndex) {
    const middleIndex = startIndex + Math.floor((endIndex - startIndex) / 2);
    // ... (implementation continues)
  }
}

Both repositories offer valuable resources for learning programming concepts, but they cater to different audiences and learning objectives. Python-100-Days provides a comprehensive curriculum for Python learners, while javascript-algorithms focuses on in-depth algorithm implementations and analysis across multiple languages.

system-design-primer

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Pros of System Design Primer

Focuses on system design and scalability concepts, providing a broader perspective on software engineering
Includes visual aids and diagrams to illustrate complex system architectures
Covers a wide range of topics relevant to modern software development and interviews

Cons of System Design Primer

Less hands-on coding practice compared to Python-100-Days
May be more challenging for beginners without prior programming experience
Doesn't provide a structured daily learning path like Python-100-Days

Code Comparison

While a direct code comparison isn't relevant due to the different focus of these repositories, here's an example of how they might approach a similar concept:

System Design Primer (describing a load balancer):

Load Balancer -> Web Server 1
               -> Web Server 2
               -> Web Server 3

Python-100-Days (implementing a simple load balancer):

import random

def load_balancer(servers):
    return random.choice(servers)

servers = ['Server1', 'Server2', 'Server3']
chosen_server = load_balancer(servers)

Both repositories offer valuable resources for developers, with System Design Primer focusing on high-level system architecture and Python-100-Days providing hands-on Python programming practice.

Python

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All Algorithms implemented in Python

Pros of Python

Focuses on algorithms and data structures, providing a comprehensive collection of implementations
Well-organized repository structure with clear categorization of algorithms
Includes unit tests for most implementations, ensuring code quality and correctness

Cons of Python

Lacks a structured learning path or curriculum for beginners
May be overwhelming for newcomers due to the vast number of algorithms without guided explanations
Doesn't cover general Python programming concepts or best practices

Code Comparison

Python-100-Days (Day 1 - Hello World):

print('Hello, world!')

Python (Binary Search implementation):

def binary_search(array, target):
    left, right = 0, len(array) - 1
    while left <= right:
        mid = (left + right) // 2
        if array[mid] == target:
            return mid
        elif array[mid] < target:
            left = mid + 1
        else:
            right = mid - 1
    return -1

The Python repository focuses on algorithm implementations, while Python-100-Days provides a structured learning approach covering various Python concepts and projects. Python-100-Days is more suitable for beginners looking for a guided learning experience, while Python is better for those specifically interested in studying algorithms and data structures.

developer-roadmap

294,506

Interactive roadmaps, guides and other educational content to help developers grow in their careers.

Pros of developer-roadmap

Provides a comprehensive overview of various tech stacks and career paths
Regularly updated with new technologies and industry trends
Visual roadmaps make it easy to understand learning progression

Cons of developer-roadmap

Less focused on hands-on coding practice compared to Python-100-Days
May be overwhelming for beginners due to the breadth of information
Lacks in-depth explanations for specific technologies or concepts

Code Comparison

Python-100-Days provides specific code examples for learning Python:

def fibonacci(n):
    a, b = 0, 1
    for _ in range(n):
        yield a
        a, b = b, a + b

developer-roadmap doesn't include code samples, focusing instead on visual roadmaps and technology recommendations.

Summary

Python-100-Days offers a structured, hands-on approach to learning Python over 100 days, with code examples and exercises. developer-roadmap provides a broader overview of various tech stacks and career paths in software development, using visual roadmaps to guide learners. While Python-100-Days is more focused on a single language, developer-roadmap covers a wider range of technologies and career options, making it suitable for those exploring different areas of software development.

coding-interview-university

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Pros of coding-interview-university

Comprehensive coverage of computer science fundamentals and algorithms
Language-agnostic approach, focusing on concepts rather than specific implementations
Extensive resource list for further learning and practice

Cons of coding-interview-university

Less hands-on coding practice compared to Python-100-Days
May be overwhelming for beginners due to its breadth of topics
Lacks a structured day-by-day learning path

Code Comparison

Python-100-Days provides more practical coding examples:

# Day 7: String and Operations
s1 = 'hello ' * 3
print(s1)  # Output: hello hello hello
s2 = 'world'
s1 += s2
print(s1)  # Output: hello hello hello world

coding-interview-university focuses on pseudocode and conceptual understanding:

Algorithm: Binary Search
Input: sorted array A, target value T
Output: index of T in A, or -1 if not found

1. Set L = 0 and R = length(A) - 1
2. While L <= R:
   a. Set M = (L + R) / 2
   b. If A[M] == T, return M
   c. If A[M] < T, set L = M + 1
   d. If A[M] > T, set R = M - 1
3. Return -1

This comparison highlights the different approaches of the two repositories, with Python-100-Days offering more practical coding exercises and coding-interview-university providing a broader theoretical foundation for computer science concepts.

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```
python manage.py makemigrations app
python manage.py migrate
```
éè¿æ°æ®è¡¨åå»ºæ¨¡åï¼ååå·¥ç¨ï¼ï¼ä¾å¦å¨Djangoé¡¹ç®ä¸å¯ä»¥éè¿ä¸é¢çå½ä»¤çææ¨¡åã
```
python manage.py inspectdb > app/models.py
```

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