python_lazy_streams | Java inspired streams in Python

by brettschneider Python Version: v1.0.1 License: AGPL-3.0

X-Ray Key Features Code Snippets(1)Community Discussions Vulnerabilities Install Support

kandi X-RAY | python_lazy_streams Summary

python_lazy_streams is a Python library. python_lazy_streams has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can install using 'pip install python_lazy_streams' or download it from GitHub, PyPI.

Inspired by Java 8’s streams, this Python module provides a fluent syntax for manipulating and querying Python lists. It’s called lazy\_streams because it lazy-evaluates the requests to increase performance and decrease resource requirements.

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Support

python_lazy_streams has a low active ecosystem.

It has 28 star(s) with 4 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 2 have been closed. On average issues are closed in 702 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of python_lazy_streams is v1.0.1

Quality

python_lazy_streams has 0 bugs and 0 code smells.

Security

python_lazy_streams has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

python_lazy_streams code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

python_lazy_streams is licensed under the AGPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

python_lazy_streams releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

python_lazy_streams saves you 169 person hours of effort in developing the same functionality from scratch.

It has 419 lines of code, 73 functions and 3 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed python_lazy_streams and discovered the below as its top functions. This is intended to give you an instant insight into python_lazy_streams implemented functionality, and help decide if they suit your requirements.

Returns a _MaterializationResult
Convert a list of promises into a list of promises
Convert to a list
Returns a list of item objects
Flattens a list
Calculate the flattened list
Item
Status of the device
Return the item at index
Return the number of threads in the queue
Return the number of threads in the pool

Get all kandi verified functions for this library.

python_lazy_streams Key Features

No Key Features are available at this moment for python_lazy_streams.

python_lazy_streams Examples and Code Snippets

Unable to tokenize sentences using gensim and nltk in python

Python

Lines of Code : 27

License : Strong Copyleft (CC BY-SA 4.0)

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In [9]: df = pd.DataFrame(np.random.randint(0,10, (10,3)), columns=list('abc'))

In [10]: df
Out[10]:
   a  b  c
0  0  7  3
1  5  0  5
2  7  7  9
3  2  0  0
4  6  9  2
5  8  5  2
6  5  0  2
7  3  2  5
8  4  8  6
9  0  5  1

In [11]: [c for

Community Discussions

No Community Discussions are available at this moment for python_lazy_streams.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install python_lazy_streams

You can install using 'pip install python_lazy_streams' or download it from GitHub, PyPI.
You can use python_lazy_streams like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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