PEtab | TSV based data format for parameter estimation problems

by PEtab-dev Python Version: v0.1.14 License: MIT

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kandi X-RAY | PEtab Summary

PEtab is a Python library typically used in Simulation applications. PEtab has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install PEtab' or download it from GitHub, PyPI.

PEtab is built around SBML and based on tab-separated values (TSV) files. It is meant as a standardized way to provide information for parameter estimation, which is out of the current scope of SBML. This includes for example:.

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Quality

Security

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Support

PEtab has a low active ecosystem.

It has 32 star(s) with 10 fork(s). There are 12 watchers for this library.

It had no major release in the last 12 months.

There are 58 open issues and 176 have been closed. On average issues are closed in 86 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of PEtab is v0.1.14

Quality

PEtab has 0 bugs and 0 code smells.

Security

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

PEtab code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

PEtab is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

PEtab 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.

PEtab saves you 3460 person hours of effort in developing the same functionality from scratch.

It has 7411 lines of code, 325 functions and 47 files.

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

Top functions reviewed by kandi - BETA

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

Convert md to rst
Link links to images
Reads the content of a file

Get all kandi verified functions for this library.

PEtab Key Features

No Key Features are available at this moment for PEtab.

PEtab Examples and Code Snippets

No Code Snippets are available at this moment for PEtab.

Community Discussions

Trending Discussions on PEtab

How can i open and process super heavy 800PB csv file?

QUESTION

How can i open and process super heavy 800PB csv file?

Asked 2020-Jan-01 at 16:48

How can i open a file that is 800 petabytes?

It's a file for some data science competition- 807167556410028 kb = 800000,556410028 TB = ~800PB

It's archived into 600 mb but i can't unzip it due to big size. Is it possible to read the first 1000 rows from the zipped archive with pandas?

...

ANSWER

Answered 2020-Jan-01 at 16:48

import zipfile
archive = zipfile.ZipFile('bigfile.zip')
file = archive.open('big.csv')
textfilereader = pd.read_csv(file, chunksize=1000000)
df = textfilereader.get_chunk()

#df now is the dataframe.

Source https://stackoverflow.com/questions/59514763

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

Vulnerabilities

No vulnerabilities reported

Install PEtab

You can install using 'pip install PEtab' or download it from GitHub, PyPI.
You can use PEtab 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.