PipelineCsv library

In Russian

The free, open source PipelineCsv library is designed to work with the results of analysis of in-line flaw detection data in the form of a CSV file.

The library provides a set of high-level operations with CSV file.

Data can be

• mirrored
• glued together from several CSV files
• stretched/compressed along the distance according to a given set of intermediate points
• interpreted as an iterable sequence of pipes with geodata

Installation

pip install pipeline-csv

Usage

It is necessary to define the sets of defects and markers used in your project. To do this, you need to define your class for CSV row by deriving it from the pipeline_csv.csvfile.row.Row class and override two methods of this class: defekts_dict and lineobj_dict.

from pipeline_csv.csvfile.row import Row

class TypeMarker:
    VALVE = 0
    CASE_START = 1
    CASE_END = 2

class TypeDefekt:
    CORROZ = 0
    DENT = 1
    FACTORY = 2

class MyRow(Row):

    @staticmethod
    def defekts_dict():
        return {
          TypeDefekt.CORROZ: "Corrosion",
          TypeDefekt.DENT: "Dent",
          TypeDefekt.FACTORY: "Manufacturing defect",
        }

    @staticmethod
    def lineobj_dict():
        return {
          TypeMarker.VALVE: "Valve",
          TypeMarker.CASE_START: "Casing start",
          TypeMarker.CASE_END: "Casing end",
        }

For the data mirroring operation, you need to override the markers_reverse method, which returns a dictionary that specifies the rules for replacing when mirroring.

class MyRow(Row):

    @staticmethod
    def markers_reverse():
        return {
          TypeMarker.CASE_START: TypeMarker.CASE_END,
          TypeMarker.CASE_END: TypeMarker.CASE_START,
        }

Further, the MyRow class can be used in operations with data of CSV files.

• Creating a CSV file
• Data mirroring
• Docking new data and compression/stretching
• Pipe sequence
• Defect location at the pipe
• Depth of defect
• Pipeline diameter changing

Development

git clone git@github.com:vb64/pipeline.csv.git
cd pipeline.csv
make setup PYTHON_BIN=/path/to/python3
make tests