首先预览一下 PyCharm 在实际应用中的界面:(更改了PyCharm的默认风格)
安装
首先去下载最新的pycharm 2.7.3,进行安装。可以直接在官网下载。
PyCharm 的激活方式:
1,推荐购买正版。
2,可以选择试用,免费试用30天。
3,网上找激活码:
(下面的激活码来自互联网,仅供学习交流之用)
user name: EMBRACE
key:
14203-12042010
0000107Iq75C621P7X1SFnpJDivKnX
6zcwYOYaGK3euO3ehd1MiTT"2!Jny8
bff9VcTSJk7sRDLqKRVz1XGKbMqw3G
首次使用
1,点击Create New Project.
2, 输入项目名、路径、选择python解释器。如果没有出现python解释器,进入步骤3.
3,选择python解释器。可以看到,一旦添加了python解释器,pycharm就会扫描出你已经安装的python扩展包,和这些扩展包的最新版本。(估计是pycharm连接了pypi)
4,点击OK之后,就会创建一个空项目,里面包含一个.idea的文件夹,用于pycharm管理项目。
5,好了,写一个新的项目尝试一下pycharm吧!
■ 附注:
pyCharm风格(配色方案)的调整,可以在:【File】-->【Settings】 的 Editor的子选项里进行设置。
比如我这个配色方案,选择的是Dracula(吸血鬼德库拉伯爵),如下图:

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You can manage different Python versions by using pyenv, venv and Anaconda. 1) Use pyenv to manage multiple Python versions: install pyenv, set global and local versions. 2) Use venv to create a virtual environment to isolate project dependencies. 3) Use Anaconda to manage Python versions in your data science project. 4) Keep the system Python for system-level tasks. Through these tools and strategies, you can effectively manage different versions of Python to ensure the smooth running of the project.

NumPyarrayshaveseveraladvantagesoverstandardPythonarrays:1)TheyaremuchfasterduetoC-basedimplementation,2)Theyaremorememory-efficient,especiallywithlargedatasets,and3)Theyofferoptimized,vectorizedfunctionsformathematicalandstatisticaloperations,making

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TocraftexecutablePythonscripts,followthesebestpractices:1)Addashebangline(#!/usr/bin/envpython3)tomakethescriptexecutable.2)Setpermissionswithchmod xyour_script.py.3)Organizewithacleardocstringanduseifname=="__main__":formainfunctionality.4

NumPyarraysarebetterfornumericaloperationsandmulti-dimensionaldata,whilethearraymoduleissuitableforbasic,memory-efficientarrays.1)NumPyexcelsinperformanceandfunctionalityforlargedatasetsandcomplexoperations.2)Thearraymoduleismorememory-efficientandfa

NumPyarraysarebetterforheavynumericalcomputing,whilethearraymoduleismoresuitableformemory-constrainedprojectswithsimpledatatypes.1)NumPyarraysofferversatilityandperformanceforlargedatasetsandcomplexoperations.2)Thearraymoduleislightweightandmemory-ef

ctypesallowscreatingandmanipulatingC-stylearraysinPython.1)UsectypestointerfacewithClibrariesforperformance.2)CreateC-stylearraysfornumericalcomputations.3)PassarraystoCfunctionsforefficientoperations.However,becautiousofmemorymanagement,performanceo


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