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filevalidation-1.0.0
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مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
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تبلیغات ما
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مشاهده بیشترتوضیحات
Module to validate file
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | filevalidation-1.0.0 |
| نام | filevalidation |
| نسخه کتابخانه | 1.0.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Ram Prakash Jayapalan |
| ایمیل نویسنده | ramp16888@gmail.com |
| آدرس صفحه اصلی | https://github.com/ram-jayapalan/file-validation |
| آدرس اینترنتی | https://pypi.org/project/filevalidation/ |
| مجوز | - |
File Validation
----------------
Python file validation module for structured text files.
This module runs through the rules defined within a config file and validates the data based on the given rules. Complex rules can be defined using regex expressions without boundaries.
System Requirements
--------------------
**Operating System**: Windows/Linux/Mac
**Python version**: 3.7 and above
Usage
-----
The module is available as a part of PyPI and can be easily installed
using ``pip``
::
pip install filevalidation
Create a config file with ``.ini`` extension and specify the rules based off the below template
.. code-block:: yaml
# This template can be used as the base to generate configuration files as required.
# Do not use this configuration template directly for validation.
# Use "#" or ";" for commenting lines within the configuration file. Do not comment section headers (enclosed within [])
# By default : key:value pairs are case sensitive, unless explicitly specified.
[global.settings]
# Column delimiter in file
Delimiter = \t
# Expected file encoding
Encoding = utf-8
[file.rules]
# Expected filename. For complex filename, use regex pattern
Filename = <filename>_\d{8}.txt
# The below message is displayed if the file failed the filename validation test
FilenameErrorMessage = The given file did not meet the expected filename or format.
[header.rules]
# Whether the header needs to be validated across the specified rules; yes/no
ValidateHeader = yes
# Treat header as case sensitive; yes/no
CaseSensitive = yes
# The below message is displayed if the file failed the header validation test where it could not find a match for the given header(s)
# {headername} placeholder is dynamically replaced with the appropriate expected header during runtime and is optional. This placeholder cannot be used elsewhere.
HeaderErrorMessage = Could not find a match for the header "{headername}"
# Match header count to that of the given header; yes/no
MatchHeaderCount = yes
# The below message is displayed if the file failed the header validation test where the given header count and the expected header count do not match.
# {requiredcount} placeholder is dynamically replaced with the expected header count during runtime
# {availablecount} placeholder is dynamically replaced with the available header count from the file during runtime and is optional. This placeholder cannot be used elsewhere.
HeaderCountErrorMessage = Header count does not match (required : {requiredcount} | available : {availablecount})
[header]
# Expected headers here. Each header in a new line
header_1
header_2
header_n
[column.rules]
# Whether the column needs to be validated across the specified rules; yes/no
ValidateColumn = yes
[EmptyCheck]
# [EmptyCheck] can be used to valiate whether the given value is Empty or not
# The specified field/column records will be flagged if their value is empty or blank
# This check trims out any leading/trailing white spaces before validation
# Specify each FieldName to be validated in new line
# Ex: FieldName1
# FieldName2
# Note: If a field/column is not part of empty check, an empty/blank value is considered a valid value and other checks are skipped.
header_n
[EmptyCheck.description]
# Description to describe in short about the check performed. This is included in the final report
# {fieldname} placeholder is dynamically replaced with the appropriate expected header during runtime and is optional.
Description = Empty check description here.
[NumericCheck]
# [NumericCheck] can be used to valiate whether the given value is a Number
# The specified field/column records will be flagged if their value is not a number
# This validates to True if the value is integer/decimal irrespective of signed/unsigned
# Specify each FieldName to be validated in new line
# Ex: FieldName1
# FieldName2
[NumericCheck.description]
# Description to describe in short about the check performed. This is included in the final report
# {fieldname} placeholder is dynamically replaced with the appropriate expected header during runtime and is optional.
Description = Numeric check description here.
[IntegerCheck]
# [IntegerCheck] can be used to valiate whether the given number is Integer or not
# The specified field/column records will be flagged if their value is not an integer
# This validates to True if the value is a positive/negative integer value
# Specify each FieldName to be validated in new line
# Ex: FieldName1
# FieldName2
[IntegerCheck.description]
# Description to describe in short about the check performed. This is included in the final report
# {fieldname} placeholder is dynamically replaced with the appropriate expected header during runtime and is optional.
Description = Integer check description here.
[DecimalCheck]
# [DecimalCheck] can be used to valiate whether the given number is Decimal or not
# The specified field/column records will be flagged if their value is not a decimal
# This validates to True if the value is a positive/negative decimal value
# Specify each FieldName to be validated in new line
# Ex: FieldName1
# FieldName2
[DecimalCheck.description]
# Description to describe in short about the check performed. This is included in the final report
# {fieldname} placeholder is dynamically replaced with the appropriate expected header during runtime and is optional.
Description = Decimal check description here.
[FormatCheck]
# [FormatCheck] validates the value on the given regex format.
# The specified field/column records will be flagged if their value is not of expected format
# Optionally, count can be specified to match the expected count of occurence of the given pattern
# Optionally, ignorecase can be set to True or False to manage case-sensitivity on the regex pattern
# Ex: FieldName = {"pattern": "[A-Za-z]", "count": 1}
# Ex: FieldName = {"pattern": "[A-Za-z]"}
# Ex: FieldName = {"pattern": "[A-Za-z]", "ignorecase": True}
header_n = {"pattern": "^(C|B|X)$"}
[FormatCheck.description]
# Description to describe in short about the check performed. This is included in the final report
# {fieldname} placeholder is dynamically replaced with the appropriate expected header during runtime and is optional.
Description = Format check description here.
[LengthCheck]
# [LengthCheck] validates if the value falls between the min and max values. Here min value is optional
# The specified field/column records will be flagged if their value is not of expected length
# This check trims out any leading/trailing white spaces before validation
# Ex: FieldName = {"min": 2, "max": 10}
# Ex: FieldName = {"max": 255}
# key:value is case-sensitive
header_n = {"min": 1, "max": 1}
[LengthCheck.description]
# Description to describe in short about the check performed. This is included in the final report
# {fieldname} placeholder is dynamically replaced with the appropriate expected header during runtime and is optional.
Description = Length check description here.
With the config rules in place, create an instance of ``ValidateFile`` class and pass the path to the config file and source file as args. Then call the ``getresult()`` method which will return the validation summary as a python dictionary.
.. code-block:: python
from validatefile.main import ValidateFile
val = ValidateFile(configfile='/path/to/config/file', sourcefile='/path/to/source/file')
res = val.getresult(outputdir=None)
print(res)
When ``outputdir`` (path to a directory) is specified in ``getresult()``, validation results are written to an output file (tab delimited text file) in the given directory. This output file along with the source columns will contain 2 additional columns - ``_is_error`` and ``_error_desc``
where
* ``_is_error`` - (bool) This flag will be set to ``1`` if the line item / record failed any of the validation with respect to the given rules
* ``_error_desc`` - (str) Contains description of the error that caused the ``_is_error`` flag to appear as ``1``
.. code-block:: python
from validatefile.main import ValidateFile
val = ValidateFile(configfile='/path/to/config/file', sourcefile='/path/to/source/file')
res = val.getresult(outputdir='/path/to/output/dir')
print(res)
Sample outputs:
* No errors
.. code-block:: python
{'Results': {'TotalRecordsAnalysed': 1000000, 'RecordsPassed': 1000000, 'RecordsFailed': 0, 'ErrorDetails': [], 'OutputFile': '/path/to/output/file.txt'}}
* Contains errors
.. code-block:: python
{'Results': {'TotalRecordsAnalysed': 100, 'RecordsPassed': 0, 'RecordsFailed': 100, 'ErrorDetails': [{'FormatCheck': 100}], 'OutputFile': '/path/to/output/file.txt'}}
.. code-block:: python
{'Results': {'TotalRecordsAnalysed': 10, 'RecordsPassed': 0, 'RecordsFailed': 10, 'ErrorDetails': [{'Level': 'Filename', 'Error': 'The given file did not meet the expected filename or format.'}, {'FormatCheck': 10}], 'OutputFile': '/path/to/output/file.txt'}}
نحوه نصب
نصب پکیج whl filevalidation-1.0.0:
pip install filevalidation-1.0.0.whl
نصب پکیج tar.gz filevalidation-1.0.0:
pip install filevalidation-1.0.0.tar.gz