This article mainly introduces what abilities python engineers need to have, which has certain reference value. Friends who need it can refer to it. I hope that you will gain a lot after reading this article. Let the editor take you to understand it together.
The language Python has recently become more and more popular, and it has been paid more and more attention at the national level by the PYTHON library "IMITATION" . In addition to taking the college entrance examination and primary and secondary education, which was discussed before, now even ordinary college students cannot escape the evil hand of Python. This year, Python has joined the NCRE (National Computer Rank Examination) luxury package, with traditional powerful languages such as Java, C and C++. The first certification exam, which belongs to Python, will be held in September this year, and passing the exam can obtain national recognition The second-level computer certificate. Python has started with national certification, so what are the skill requirements for Python national registered engineers? First, let us take a look at the outline of this certification exam: Basic requirements 1. Master the basic grammar rules of the Python language. 2. Learn no less than 2 basic Python standard libraries. 3. Master no less than 2 third-party Python libraries, and master the methods of obtaining and installing third-party libraries.
Ability to read and analyze Python programs. 5. Proficient in idle development environment, can convert script program into executable program. 6. Know the names of major third-party libraries in the Python computing ecosystem in the following areas (not limited to): web crawlers, data analysis, data visualization, machine learning. Web development, etc. Exam content 1. Basic grammatical elements of the Python language 1. Programs with basic grammatical elements: program frame indentation format comments, variables, naming, reserved words, data types, assignment statement references. 2. Basic input and output functions: input().eval(), print(). 3. The writing style of the source program. language features. 2. Basic data type 1. Numeric types: Integer types, floating point types, and complex types. 2. Numerical operations: digital operators, digital manipulation functions. 3. String type and format: index slice, basic format() formatting method.
String type: the number of operators and processing methods for strings. 5. Type judgment and conversion between types. Third, the program's control structure 1. The control structure of the three programs. 2. The branch structure of the program: single branch structure, two branch structure, multi-branch structure. 3. Programs with loop structure: traversal loop, infinite loop, break, continue loop control. 4. Exception handler: try-excepl. 4. Functionality and code reuse1. Define and use functions. 2. Transfer function parameter passing: optional parameter, parameter name transfer, function return value. 3. The scope of variables: local variables and global variables. 5. Combine data type 1. Basic concepts of union data types. 2. List type: definition, index. 3. List operation: operation function, operation method list. 4. Dictionary type: definition, index. 5. Dictionary type operation: dictionary operation function, dictionary operation method.
Usage: file open; read and write and close. 2. Dimensions of data organization: one-dimensional data and two-dimensional data. 3. One-dimensional data processing: representation, storage and processing. 4. Two-dimensional data processing: refers to storage and processing. 5. Read and write one or two-dimensional data files using CSV format. 7. Python Computing Ecology 1. The standard library; the turtle library (required). The random library (required). The time library (optional). 2. Basic Python built-in functions. 3. Obtain and install third-party libraries. 4. Third-party libraries: jieba library (required), wordcloud library (optional). 5. The wider Python computing ecosystem only needs the name of the third-party library, not limited to the following areas; web crawler data analysis, text processing, data visualization, user graphical interface, machine learning, web development, game development, etc.
You need to learn a lot to become a business where engineers can stand. If you're interested in the web, then you need to master Django and the Flask framework, two of the most commonly used application frameworks for development married in Python. If you want to join the hot Al army, then you need to master the Python machine learning library scikit-learn TensorFlow, Keras, Theano, Coffee and other machine learning frameworks. Of course, you can choose only one of them. Don't be greedy. The difference between each is Baidu. If you want to be a crawler engineer in the future, you must master urllib, urllib2, requests, bs4 and other packages. If it is a large-scale crawler, you also need to master a crawler framework such as Scrapy. In the past scientific aspects of data, details were mainly used for data analysis and data mining. There are mainly 5 packages in this field, pandas, Numpy, Scipy Matplotlib, scikit-learn.
The country's determination to work hard in the Python space is clear. Are you ready to welcome the age? Python has basic learning materials that are freely available.