Life is short, I use Python, the Python ecosystem has always been famous for its complete range of class libraries, which is also an important reason why this language is so popular.
Python built-in functions: Python’s own built-in functions. The function does not need to be imported and can be used directly. For example, to calculate the absolute value of -3.2, use the abs function directly. The method is:
abs(-3.2)
Python standard library: Python’s own standard library. The Python standard library does not need to be installed. You only need to import it through the import method first to use its methods. For example, import the string module and then use the find method in it:
import string
string.find('abcde','b')
Third-party library: Python’s third-party library. These libraries need to be installed first (some may require configuration).
External tools: libraries or packages not written in Python, related tools for Python data work.
1 file reading and writing
The reading and writing of files includes common txt, Excel, xml, binary files and other formats of data text, mainly used for reading and writing local data.
1. open(name[, mode[, buffering]])
Type: Python built-in function
Description: Python default file reading and writing Method
Recommendation: ★★★
2. numpy.loadtxt, numpy.load and numpy.fromfile
Type: Third-party library
Description: Numpy’s own read and write functions , including loadtxt, load and fromfile, used for reading and writing text and binary files
Recommendation: ★★★
3. pandas.read_*
Type: Third-party library
Description: Pandas’ own read file method, such as ead_csv, read_fwf, read_table etc., used for reading and writing text, Excel, binary files, HDF5, tables, SAS files, SQL databases, Stata files, etc.
Recommendation: ★★★
4. xlrd
Type: Third-party library
Description: Used for Excel file reading
Recommendation :★★
5. xlwt
Type: Third-party library
Description: Used for Excel file writing
Recommendation :★★
6. pyexcel-xl
Type: Third-party library
Description: Used to read and write Excel files
Recommendation: ★★
7. xluntils
Type: Third-party library
Description: Used to read and write Excel files
Recommendation :★★
8. pyExcelerator
Type: Third-party library
Description: Used to read and write Excel files
Recommendation :★
9. openpyxl
Type: Third-party library
Description: Used to read and write Excel files
Recommended :★
10. lxml
Type: Third-party library
Description: XML and HTML reading and parsing
Recommended Degree: ★★★
11. xml
Type: Python standard library
Description: xml object parsing and formatting processing
Recommended Degree: ★★★
12. libxml2
Type: Third-party library
Description: XML object parsing and formatting processing
Recommended Degree: ★
13. xpath
Type: Third-party library
Description: XML object parsing and formatting processing
Recommended Degree: ★★
14. win32com
Type: Third-party library
Description: Information about Windows system operation, Office (Word, Excel, etc.) file reading and writing, etc. Comprehensive application library
Recommendation:★
2 Web crawling and parsing
Web crawling and parsing are used to crawl information from the Internet and process HTML objects. Libraries related to the parsing and processing of xml objects are found in "01 File Reading and Writing".
15. requests
Type: Third-party library
Description: Network request library, which provides a variety of network request methods and can define complex sending information
Recommendation: ★★★
16. urllib
Type: Python standard library
Description: Python’s own library that simply reads a specific URL and obtains the returned information
Recommendation: ★★
17. urllib2
Type: Python standard library
Description: Python’s own library, which reads a specific URL and obtains the returned information, relative to urllib can handle more HTTP information, such as cookies, authentication, redirection, etc.
Recommendation: ★★
18. urlparse
Type: Python standard library
Description: Python’s own URL parsing library, which can automatically parse different fields and parameters of URLs , paths, etc.
Recommendation: ★★★
19. HTMLParser
Type: Python standard library
Description: Python’s own HTML parsing module can easily analyze HTML files.
Recommendation: ★★★
20. Scapy
Type: Third-party library
Description: Distributed crawler framework, which can be used to simulate user sending, listening and parsing and disguise Network messages, often used for crawling large network data
Recommendation: ★★★
21. Beautiful Soup
Type: Third-party library
Description: Beautiful Soup is a web page data parsing and formatting tool, usually used with Python Use together with urllib, urllib2 and other libraries
Recommendation: ★★★
3 Database connection
Database connections can be used to connect to many databases and access common database interfaces, and can be used for database maintenance, management, and daily operations such as addition, deletion, modification, and query.
22. mysql-connector-python
Type: Third-party library
Description: MySQL official driver connector
Recommendation: ★★★
23. pymysql
Type: Third-party library
Description: MySQL connection library, supports Python3
Recommendation ：★★★
24. MySQL-python
Type: Third-party library
Description: MySQL connection library
Recommendation: ★★
25. cx_Oracle
Type: Third-party library
Description: Oracle connection library
Recommendation: ★★ ★
26. psycopg2
Type: Third-party library
Description: A very popular PostgreSQL adapter in the Python programming language
Recommendation: ★★★
27. redis
Type: Python standard library
Description: Redis connection library
Recommendation: ★★ ★
28. pymongo
Type: Third-party library
Description: MongoDB official driver connector
Recommendation: ★★★
29. HappyBase
Type: Third-party library
Description: HBase connection library
Recommendation: ★★ ★
30. py2neo
Type: Third-party library
Description: Neo4j connection library
Recommendation: ★★ ★
31. cassandra-driver
Type: Third-party library
Description: Cassandra (1.2+) and DataStax Enterprise (3.1+) connection library< /span>
Recommendation: ★★★
32. sqlite3
Type: Python standard library
Description: Python’s own module for operating SQLite databases
Recommendation: ★★★
33. pysqlite2
Type: Third-party library
Description: SQLite 3.x connection library
Recommendation :★★
34. bsddb3
Type: Third-party library
Description: Berkeley DB connection library
35. bsddb
Type: Python standard library
Description: Python’s own module provides an interface to the Berkeley DB library a>
Recommendation: ★★
36. dbhash
Type: Python standard library
Description: Python’s own module, the dbhash module provides a way to open the database using the BSD database library Function. This module mirrors the interface of other Python database modules that provide access to DBM-style databases. The bsddb module requires dbhash
Recommendation: ★★
37. adodb
Type: Third-party library
Description: ADOdb is a database abstract library that supports common data and database interfaces and can be customized For database expansion, this library can parse and differentiate syntax in different databases, and has high versatility
Recommendation: ★★★
38. SQLObject
Type: Third-party library
Description: SQLObject is a popular object relational manager used to provide objects to the database Interface, where the tables are classes, behavior instances, and columns are attributes
Recommendation: ★★
39. SQLAlchemy
Type: Third-party library
Description: SQLAlchemy is a Python SQL toolkit and object-relational mapper for application developers Provides all the functions and flexible control of SQL
Recommendation: ★★
40. ctypes
Type: Third-party library
Description: ctypes is an external library of Python that provides data types compatible with C language. You can easily call functions in C DLL
Recommendation: ★★★
41. pyodbc
Type: Third-party library
Description: Python interface library for accessing the database through ODBC
Recommendation: ★★★
42. Jython
Type: Third-party library
Description: Python interface library for accessing the database through JDBC
Recommendation: ★★★
4 Data Cleaning and Transformation
Data cleaning transformation is mainly used for preprocessing before formal application of data.
43. frozenset([iterable])
Type: Python built-in function
Description: Returns a new frozenset object, optionally obtained from iterable Elements
Recommendation: ★★★
44. int(x)
Type: Python built-in function
Description: Returns the integer part of x
Recommendation: ★★★
45. isinstance(object, classinfo)
Type: Python built-in function
Description: Returns whether object is the specified classinfo instance information
Recommendation: ★★★
46. len(s)
Type: Python built-in function
Description: Returns the length or number of items of the object
Recommendation: ★★★
47. long(x)
Type: Python built-in function
Description: Returns a long integer object constructed from a string or number x< /span>
Recommendation: ★★★
48. max(iterable[, key])
Type: Python built-in function
Description: Returns an iterable or the largest of two or The largest term among multiple parameters
Recommendation: ★★★
49. min(iterable[, key])
Type: Python built-in function
Description: Returns an iterable or the largest of two or Minimum term among multiple parameters
Recommendation: ★★★
50. range(start, stop[, step])
Type: Python built-in function
Description: Used to create loops together with for loops List, control the number of iterations and obtain the loop value by specifying start (start), stop (end) and step (step size)
Recommendation: ★★★
51. raw_input(prompt)
Type: Python built-in function
Description: Capture user input and return it as a string (it is not recommended to use input as User input capture function)
Recommendation: ★★★
52. round(number[, ndigits])
Type: Python built-in function
Description: Returns the rounded floating value of number ndigits after the decimal point Points
Recommendation: ★★★
53. set([iterable])
Type: Python built-in function
Description: Returns a new collection object, optionally obtained from iterable Elements
Recommendation: ★★★
54. slice(start, stop[, step])
Type: Python built-in function
Description: Returns the range (start, stop , step) slice object of the index set specified
Recommendation: ★★
55. sorted(iterable[, cmp[, key[, reverse]]])
Type: Python built-in function
Description: From iterable Returns a new sorted list of items
Recommendation: ★★★
56. xrange(start, stop[, step])
Type: Python built-in function
Description: This function is very similar to range() , but returns an xrange object instead of a list
Recommendation: ★★★
57. string
Type: Python standard library
Description: String processing library, which can realize string search, split, combination, replacement, Deduplication, case conversion and other formatting processing
Recommendation: ★★★
58. re
Type: Python standard library
Description: Regular expression module, often used in text and string processing
Recommendation: ★★★
59. random
Type: Python standard library
Description: This module implements pseudo-random number generators for various distributions and supports uniform data distribution , normal (Gaussian) distribution, lognormal distribution, negative exponential distribution, gamma and beta distribution, etc.
Recommendation: ★★★
60. os
Type: Python standard library
Description: Used for directory operations such as creating, deleting, modifying permissions, switching paths, and calling Execute system commands
Recommendation: ★★★
61. os.path
Type: Python standard library
Description: Commonly used for directory traversal, combination, segmentation, judgment and other operations Judgment, search, and merge of data files
Recommendation: ★★★
62. prettytable
Type: Python standard library
Description: Formatted table output module
Recommendation: ★★
63. json
Type: Python standard library
Description: Conversion of Python objects and json objects
Recommended Degree: ★★★
64. base64
Type: Python standard library
Description: Encode and decode arbitrary binary strings into Base16, Base32 and Base64
Recommendation: ★★★
5 Data calculation and statistical analysis
Data calculation and statistical analysis are mainly used for data exploration, calculation and preliminary data analysis.
65. numpy
Type: Third-party library
Description: NumPy is the basic toolkit for Python scientific computing. Many Python data calculation libraries are Rely on it
Recommendation: ★★★
66. scipy
Type: Third-party library
Description: Scipy is a set of themed toolkits that specialize in solving different scenarios of scientific and engineering computing< /span>
Recommendation: ★★★
67. pandas
Type: Third-party library
Description: Pandas is a library for Python data analysis. Its main function is to perform data analysis. Pandas provides a two-dimensional tabular data structure DataFrame for structured data analysis, which is similar to the data frame in R. It can provide refined operations such as slicing, dicing, aggregation, and subset selection in the database. Data analysis provides convenience
Recommendation: ★★★
68. statsmodels
Type: Third-party library
Description: Statsmodels is a statistical modeling and econometrics toolkit for Python, including some descriptions It integrates a variety of linear regression models, generalized linear regression models, discrete data distribution models, time series analysis models, non-parametric estimation, survival analysis, principal component analysis, kernel density estimation and a wide range of Functions such as statistical testing and drawing
Recommendation: ★★★
69. abs(x)
Type: Python built-in function
Description: Return the absolute value of x
Recommendation: ★★★
70. cmp(x, y)
Type: Python built-in function
Description: Compare two objects x and y and return according to the result an integer. If x < y, the return value is negative, if x == y, it is zero, if x > y, the return value is positive
Recommendation: ★★
71. float(x)
Type: Python built-in function
Description: Returns a floating point number constructed from a number or string x
Recommendation: ★★★
72. pow(x, y[, z])
Type: Python built-in function
Description: Returns x raised to the y power. If z exists, return x raised to the y power, modulo z
Recommendation: ★★★
73. sum(iterable[, start])
Type: Python built-in function
Description: Iterate from left to right and return the sum< /span>
Recommendation: ★★★
74. math
Type: Python standard library
Description: Mathematical function library, including sine, cosine, tangent, cotangent, radian conversion, Logarithmic operations, pi, absolute value, rounding and other mathematical calculation methods
Recommendation: ★★★
75. cmath
Type: Python standard library
Description: Basically the same as math, the difference is that cmath operates on complex numbers< a i=3> Recommendation: ★★
76. decimal
Type: Python standard library
Description: Decimal floating point arithmetic
Recommendation :★★
77. fractions
Type: Python standard library
Description: The fraction module provides support for rational number arithmetic
Recommendation: ★★
6 Natural Language Processing and Text Mining
Natural language processing and text mining libraries are mainly used for data processing and modeling with natural language text as the object.
78. nltk
Type: Third-party library
Description: NLTK is a Python natural language processing tool, which is used to classify natural language , parsing and semantic understanding. There are currently more than 50 corpora and vocabulary resources
Recommendation: ★★★
79. pattern
Type: Third-party library
Description: Pattern is a network data mining Python toolkit that provides network mining ( Such as network services, web crawlers, etc.), natural language processing (such as part-of-speech tagging, sentiment analysis, etc.), machine learning (such as vector space models, classification models, etc.), graphical network analysis models
Recommendation: ★★★
80. gensim
Type: Third-party library
Description: Gensim is a professional topic model (a method of discovering hidden themes in text Statistical modeling method) Python toolkit to provide scalable statistical semantics, analyze the semantic structure of plain text, and retrieve semantically similar documents
Recommendation: ★★★
81. Zhiba Word Segmentation
Type: Third-party library
Description: Zhiba Word Segmentation is a popular domestic Python text processing toolkit. The word segmentation mode is divided into Three modes: precise mode, full mode and search engine mode, supporting traditional Chinese word segmentation, custom dictionaries, etc. It is a very good Python Chinese word segmentation solution, which can implement word segmentation, dictionary management, keyword extraction, part-of-speech tagging, etc.
Recommendation: ★★★
82. SnowNLP
Type: Third-party library
Description: SnowNLP is a class library written in Python that can easily process Chinese text content. This library is a class library inspired by TextBlob and written for Chinese processing. Unlike TextBlob, NLTK is not used here. All algorithms are implemented by ourselves, and it comes with some trained dictionaries< a i=3> Recommendation: ★★
83. smallseg
Type: Third-party library
Description: Smallseg is an open source, lightweight Chinese word segmentation toolkit based on DFA . You can customize the dictionary, return the registered word list and unregistered word list after cutting, and have a certain ability to recognize new words
Recommendation: ★★
84. spaCy
Type: Third-party library
Description: spaCy is a Python natural language processing toolkit that combines Python and Cython to make natural Language processing capabilities have reached industrial strength
Recommendation: ★★★
85. TextBlob
Type: Third-party library
Description: TextBlob is a Python library for processing text data, which can be used for part-of-speech tagging and emotion Analysis, text translation, noun phrase extraction, text classification, etc.
Recommendation: ★★
86. PyNLPI
Type: Third-party library
Description: PyNLPI is a collection library suitable for various natural language processing tasks and can be used for Chinese Text segmentation, keyword analysis, etc., especially important is that it supports Chinese and English mapping, UTF-8 and GBK encoded strings, etc.
Recommendation: ★★★
87. synonyms
Type: Third-party library
Description: Chinese synonyms toolkit, which can be used for many tasks of natural language understanding: text alignment, Recommendation algorithm, similarity calculation, semantic offset, keyword extraction, concept extraction, automatic summary, search engine, etc.
Recommendation: ★★★
7 Image and video processing
Image processing and video processing are mainly suitable for image-based operations, processing, analysis and mining, such as face recognition, image recognition, target tracking, image understanding, etc.
88. PIL/Pillow
Type: Third-party library
Description: PIL is a commonly used library for image reading, processing and analysis. Provides a variety of data processing and transformation operation methods and attributes. PIL only supports version 2.7 and has not been updated for a long time. A group of volunteers released a new branch Pillow based on PIL. Pillow supports both Python2 and Python3 and adds many new features
Recommendation: ★★
89. OpenCV
Type: Third-party library
Description: OpenCV is a powerful image and video working library. It provides a variety of program interfaces and supports cross-platform (including mobile) applications. OpenCV is designed to be efficient, it is written in optimized C/C++ and the library can take advantage of multi-core processing. In addition to basic processing of images, it also supports image data modeling and pre-built a variety of image recognition engines, such as face recognition
Recommendation: ★★★
90. scikit-image
Type: Third-party library
Description: scikit-image (also called skimage) is an image processing library that supports Color mode conversion, filters, drawing, image processing, feature detection and other functions
Recommendation: ★★
91. imageop
Type: Python standard library
Description: Python’s own function for basic image operations, including cropping, scaling, and mode Convert
Recommendation:★
92. colorsys
Type: Python standard library
Description: Python’s own function to convert different image color modes
Recommendation:★
93. imghdr
Type: Python standard library
Description: Python’s own function, returns the type of image file
Recommendation: ★
8 Audio processing
Audio processing is mainly suitable for sound-based processing, analysis and modeling, and is mainly used in speech recognition, speech synthesis, semantic understanding, etc.
94. TimeSide
Type: Third-party library
Description: TimeSide is a library capable of audio analysis, imaging, transcoding, streaming and tagging A Python framework for processing complex processing of very large data sets with any audio or video content
Recommendation: ★★★
95. audiolazy
Type: Third-party library
Description: audiolazy is a library for real-time sound data stream processing, supporting real-time data applications Processing, infinite data sequence representation, data flow representation, etc.
Recommendation: ★★
96. pydub
Type: Third-party library
Description: pydub supports multiple formats of sound files and can perform various signal processing (such as compression , equalization, normalization), signal generation (such as sine, square wave, sawtooth, etc.), sound effect registration, mute processing, etc.
Recommendation: ★★★
97. audioop
Type: Python standard library
Description: Python’s own functions that can implement some common operations on sound clips a>
Recommendation: ★★
98. tinytag
Type: Third-party library
Description: tinytag is used to read metadata of various sound files, covering MP3, OGG , OPUS, MP4, M4A, FLAC, WMA, Wave and other formats
Recommendation: ★★
99. aifc
Type: Python standard library
Description: Python’s own function to read and write AIFF and AIFC files< a i=3> Recommendation: ★
100. sunau
Type: Python standard library
Description: Python’s own function, read and write Sun AU files
Recommendation: ★
101. wave
Type: Python standard library
Description: Python’s own function to read and write WAV files
Recommendation: ★★
102. chunk
Type: Python standard library
Description: Python’s own function to read files in EA IFF 85 block format a>
Recommendation: ★
103. sndhdr
Type: Python standard library
Description: Python’s own function that returns the type of sound file
Recommendation: ★
104. ossaudiodev
Type: Python standard library
Description: This module supports access to the OSS (Open Sound System) audio interface< a i=3> Recommendation: ★★★
9 Data Mining/Machine Learning/Deep Learning
Data mining, machine learning and deep learning are the core modules of Python for data modeling and mining learning.
105. Scikit-Learn
Type: Third-party library
Description: scikit-learn (also called SKlearn) is a Python-based machine learning A comprehensive library with built-in supervised learning and unsupervised learning machine learning methods, including various mainstream algorithm categories such as regression, clustering, classification, streaming learning, anomaly detection, neural networks, and integration methods. It also supports preset data sets, It is a very complete and popular machine learning tool library for data preprocessing, model selection and evaluation.
Recommendation: ★★★
106. TensorFlow
Type: Third-party library
Description: TensorFlow is Google’s second-generation machine learning system with built-in deep learning extensions Supported, any calculation that can be expressed with a computational flow graph can be done using TensorFlow
Recommendation: ★★★
107. NuPIC
Type: Third-party library
Description: NuPIC is a machine using the HTM (Hierarchical Temporal Memory) learning algorithm as a tool Intelligent platform. NuPIC is suitable for a variety of problems, especially for anomaly detection and prediction applications
Recommendation: ★★★
108. PyTorch
Type: Third-party library
Description: PyTorch is a deep learning framework launched by FaceBook. It is based on Python (not lua) The dynamic calculation graph it provides is significantly different from other learning frameworks such as Tensorflow.
Recommendation: ★★
109. Orange
Type: Third-party library
Description: Orange provides interactive data analysis functions through a graphical operation interface, especially suitable for Classification, clustering, regression, feature selection and cross-validation work
Recommendation: ★★★
110. theano
Type: Third-party library
Description: Theano is a very mature deep learning library. It is tightly integrated with Numpy and supports GPU computing, unit testing and self-verification
Recommendation: ★★★
111. keras
Type: Third-party library
Description: Keras is an advanced neural network API written in Python that can run on TensorFlow or On top of Theano, its development focuses on achieving rapid experiments
Recommendation: ★★
112. neurolab
Type: Third-party library
Description: Neurolab is a basic neural network algorithm library with flexible network configuration and Python learning algorithm. It contains different variants implemented through Recurrent Neural Networks (RNN), and the library is one of the best choices among similar RNN APIs
Recommendation: ★★
113. PyLearn2
Type: Third-party library
Description: PyLearn2 is a deep learning library based on Theano, which is designed to provide great flexibility flexibility and allows researchers to freely control, the flexible and open configuration of parameters and attributes is the highlight
Recommendation: ★★★
114. OverFeat
Type: Third-party library
Description: OverFeat is a deep learning library, mainly used for image classification and positioning object detection< /span>
Recommendation: ★★
115. Pyevolve
Type: Third-party library
Description: Pyevolve is a complete genetic algorithm framework that also supports genetic programming
Recommendation: ★★
116. Caffe2
Type: Third-party library
Description: Cafffe2 is also a deep learning framework launched by FaceBook, which is more suitable for research than PyTorch. , Caffe2 is suitable for large-scale deployment and is mainly used for computer vision. It has a good application effect in image recognition classification
Recommendation: ★★
10 Data Visualization
Data visualization is mainly used for data result display, data model verification, graphical interaction and exploration.
117. Matplotlib
Type: Third-party library
Description: Matplotlib is a 2D plotting library for Python that is available in various hardcopy formats and cross-platform An interactive environment that generates publication-quality graphics, developers can generate a variety of high-quality graphics with just a few lines of code
Recommendation: ★★★
118. pyecharts
Type: Third-party library
Description: A powerful visualization tool library based on Baidu Echarts, which provides numerous graphical functions. Especially capable of displaying complex relationships
Recommendation: ★★★
119. seaborn
Type: Third-party library
Description: Seaborn is a more advanced API encapsulation based on Matplotlib. It can As a supplement to Matplotlib
Recommendation: ★★★
120. bokeh
Type: Third-party library
Description: Bokeh is an interactive visualization library that can achieve beautiful appearance in WEB browsers The visual effects
Recommendation: ★★★
121. Plotly
Type: Third-party library
Description: The graphics library provided by Plotly enables online WEB interaction and provides publication-quality Graphics, supporting line charts, scatter plots, area charts, bar charts, error bars, box plots, histograms, heat maps, subplots, multi-axis, polar charts, bubble charts, rose charts, heat maps, funnel charts, etc. Many graphics
Recommendation: ★★★
122. VisPy
Type: Third-party library
Description: VisPy is a Python library for interactive scientific visualization, designed to be fast, Scalable and easy to use
Recommendation: ★★
123. PyQtGraph
Type: Third-party library
Description: PyQtGraph is a pure Python graph and graph built on PyQt4/PySide and numpy GUI library, mainly used for mathematics/science/engineering applications
Recommendation: ★★
124. ggplot
Type: Third-party library
Description: ggplot is a graphics output library implemented in Python, similar to the graphics display in R Version
Recommendation: ★★★
11 Interactive learning and integrated development
Interactive learning and integrated development are mainly used for Python development, debugging and integration, including Python integrated development environment and IDE.
125. IPython/ Jupyter
Type: Third-party library
Description: IPython is an interactive shell based on Python, which is better than the default Python shell It is much easier to use. It supports automatic variable completion, automatic indentation, interactive help, magic commands, system commands, etc., and has many useful built-in functions and functions. Starting from IPython 4.0, IPython has derived two branches: IPython and Jupyter. Before this branch officially appeared, IPython actually already had the ipython notebook function. Therefore, Jupyter is more like an upgraded version of ipython notebook.
Recommendation: ★★★
126. Elpy
Type: Third-party library
Description: Elpy is Emacs’ development environment for Python. It combines and configures many other Software packages, all written in Emacs Lisp and Python
Recommendation: ★★
127. PTVS
Type: Third-party library
Description: Python tool for Visual Studio
Recommendation: ★★
128. PyCharm
Type: External tool
Description: PyCharm comes with a set of tools that can help users improve their efficiency when developing in the Python language. , such as debugging, syntax highlighting, project management, code jumping, smart prompts, auto-completion, unit testing, version control, and can integrate IPython, system terminal command line, etc., almost all Python work can be achieved in PyCharm Process
Recommendation: ★★★
129. LiClipse
Type: External tool
Description: LiClipse is a free multi-language IDE based on Eclipse, which supports Python development through PyDev. Application
Recommendation: ★★
130. Spyder
Type: External tool
Description: Spyder is an open source Python IDE supported by IPython and many popular Python libraries , is an interactive development environment with advanced editing, interactive testing, debugging and digital computing environment
Recommendation: ★★
12 Other Python Collaborative Data Work Tools
Other Python collaborative data work tools refer to other tools or libraries commonly used in data work in addition to the above topics.
131. tesseract-ocr
Type: External tool
Description: This is an open source OCR image and text recognition project supported by Google, supporting more than 200 languages (including Chinese), and supports custom training character sets, supporting multi-platform use across Windows, Linux, and Mac OSX
Recommendation: ★★★
132. RPython
Type: Third-party library
Description: R integrated library
Recommendation: ★★ ★
133. Rpy2
Type: Third-party library
Description: Python library connected to R
134. matpython
Type: Third-party library
Description: MATLAB integrated library
Recommendation: ★★ ★
135. Lunatic Python
Type: Third-party library
Description: Lua integrated library
Recommendation: ★ ★
136. PyCall.jl
Type: Third-party library
Description: Julia integrated library
Recommendation: ★★
137. PySpark
Type: Third-party library
Description: Python API provided by Spark
Recommendation: ★★★
138. dumbo
Type: Third-party library
Description: This module allows Pythoners to easily write and run Hadoop programs. The program version is relatively early , can be used as a reference
Recommendation: ★★
139. dpark
Type: Third-party library
Description: Python’s clone version of Spark, similar to MapReduce framework
Recommendation: ★★
140. streamparse
Type: Third-party library
Description: Streamparse allows running Python code on real-time data streams through Storm
Recommendation: ★★★