segpy | A Python package for reading and writing SEG Y files
kandi X-RAY | segpy Summary
kandi X-RAY | segpy Summary
segpy is a Python library. segpy has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. However segpy has 6 bugs. You can install using 'pip install segpy' or download it from GitHub, PyPI.
A Python package for reading and writing SEG Y files.
A Python package for reading and writing SEG Y files.
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Quality
Security
License
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segpy has a low active ecosystem.
It has 86 star(s) with 49 fork(s). There are 12 watchers for this library.
It had no major release in the last 12 months.
There are 26 open issues and 26 have been closed. On average issues are closed in 81 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of segpy is 2.1.0
Quality
segpy has 6 bugs (3 blocker, 0 critical, 3 major, 0 minor) and 81 code smells.
Security
segpy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
segpy code analysis shows 0 unresolved vulnerabilities.
There are 1 security hotspots that need review.
License
segpy 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
segpy releases are not available. You will need to build from source code and install.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
segpy saves you 4173 person hours of effort in developing the same functionality from scratch.
It has 8860 lines of code, 1065 functions and 70 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed segpy and discovered the below as its top functions. This is intended to give you an instant insight into segpy implemented functionality, and help decide if they suit your requirements.
- Create a YAML reader from a file - like object
- Load a reader from the cache file
- Create a reader from a file - like object
- Locate the cache file
- Extract timeslice from a timeslice
- Create a dtype from a data sample format
- The inline_numbers
- Make a masked array
- Extract a timeslice from a file
- Create a Segment YAML reader
- Retrieve the trace header
- Compute the ld exp
- Read traces from a segy file
- Return the length of the trace length in bytes
- Extract a header field from a trace header
- Extract an inline
- Handle metadata
- Extract the trace positions from a file
- Extract the revision from the binary header
- List of trace indexes
- Report a segy file
- Print report
- Extract xline from a 3D reader
- Writes SEGY data to file
- Extract a trace from a trace index
- Retrieve the traces from a trace index
- Extract trace headers from fields
Get all kandi verified functions for this library.
segpy Key Features
No Key Features are available at this moment for segpy.
segpy Examples and Code Snippets
No Code Snippets are available at this moment for segpy.
Community Discussions
No Community Discussions are available at this moment for segpy.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install segpy
You can install using 'pip install segpy' or download it from GitHub, PyPI.
You can use segpy 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.
You can use segpy 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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