| Name | dup-fmt JSON |
| Version |
0.1.4
JSON |
| download |
| home_page | |
| Summary | The utility formatter objects for the data engine package |
| upload_time | 2023-09-07 07:38:10 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8.10 |
| license | |
| keywords |
data
formatter
|
| VCS |
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# Data Utility Package: *Formatter*
[](https://github.com/korawica/dup-fmt/actions/workflows/tests.yml)
[](https://codecov.io/gh/korawica/dup-fmt)
[](https://pypi.org/project/dup-fmt/)
[](https://github.com/korawica/dup-fmt)
**Type**: `DUP` | **Tag**: `Data Utility Package` `Data` `Utility` `Formatter`
**Table of Contents**:
- [Formatter Objects](#formatter-objects)
- [Datetime](#datetime)
- [Version](#version)
- [Serial](#serial)
- [Naming](#naming)
- [Storage](#storage)
- [Constant](#constant)
- [FormatterGroup Object](#formattergroup-object)
This **Formatter** package was created for `parse` and `format` any string values
that match format pattern with Python regular expression. This package be the
co-pylot project for stating to my **Python Software Developer** role.
**Install from PyPI**:
```shell
pip install dup-fmt
```
:dart: First objective of this project is include necessary formatter objects for
any data components package which mean we can `parse` any complicate names on
data source and ingest the right names to in-house or data target.
For example, we want to get filename with the format like, `filename_20220101.csv`,
on the file system storage, and we want to incremental ingest the latest file with
date **2022-03-25** date. So we will implement `Datetime` object and parse
that filename to it,
```python
Datetime.parse('filename_20220101.csv', 'filename_%Y%m%d.csv').value == datetime.today()
```
The above example is :yawning_face: **NOT SURPRISE!!!** for us because Python
already provide build-in package `datetime` to parse by `{dt}.strptime` and
format by `{dt}.strftime` with any datetime string value. This package will the
special thing when we group more than one formatter objects together as
`Naming`, `Version`, and `Datetime`.
**For complex filename format like**:
```text
{filename:%s}_{datetime:%Y_%m_%d}.{version:%m.%n.%c}.csv
```
From above filename format string, the `datetime` package does not enough for
this scenario right? but you can handle by your hard-code object or create the
better package than this project.
> **Note**: \
> Any formatter object was implemented the `self.valid` method for help us validate
> format string value like the above example scenario,
> ```python
> this_date = Datetime.parse('20220101', '%Y%m%d')
> this_date.valid('any_files_20220101.csv', 'any_files_%Y%m%d.csv') # True
> ```
## Formatter Objects
- [Datetime](#datetime)
- [Version](#version)
- [Serial](#serial)
- [Naming](#naming)
- [Storage](#storage)
- [Constant](#constant)
The main purpose is **Formatter Objects** for `parse` and `format` with string
value, such as `Datetime`, `Version`, and `Serial` formatter objects. These objects
were used for parse any filename with put the format string value. The formatter
able to enhancement any format value from sting value, like in `Datetime`, for `%B`
value that was designed for month shortname (`Jan`, `Feb`, etc.) that does not
support in build-in `datetime` package.
> **Note**: \
> The main usage of this formatter object is `parse` and `format` method.
### Datetime
```python
from dup_fmt import Datetime
datetime = Datetime.parse(
value='This_is_time_20220101_000101',
fmt='This_is_time_%Y%m%d_%H%M%S'
)
datetime.format('This_datetime_format_%Y%b-%-d_%H:%M:%S')
```
```text
>>> 'This_datetime_format_2022Jan-1_00:01:01'
```
[Supported Datetime formats](/docs/en/docs/API.md#datetime)
### Version
```python
from dup_fmt import Version
version = Version.parse(
value='This_is_version_2_0_1',
fmt='This_is_version_%m_%n_%c',
)
version.format('New_version_%m%n%c')
```
```text
>>> 'New_version_201'
```
[Supported Version formats](/docs/en/docs/API.md#version)
### Serial
```python
from dup_fmt import Serial
serial = Serial.parse(
value='This_is_serial_62130',
fmt='This_is_serial_%n'
)
serial.format('Convert to binary: %b')
```
```text
>>> 'Convert to binary: 1111001010110010'
```
[Supported Serial formats](/docs/en/docs/API.md#serial)
### Naming
```python
from dup_fmt import Naming
naming = Naming.parse(
value='de is data engineer',
fmt='%a is %n'
)
naming.format('Camel case is %c')
```
```text
>>> 'Camel case is dataEngineer'
```
[Supported Naming formats](/docs/en/docs/API.md#naming)
### Storage
```python
from dup_fmt import Storage
storage = Storage.parse(
value='This file have 250MB size',
fmt='This file have %M size'
)
storage.format('The byte size is: %b')
```
```text
>>> 'The byte size is: 2097152000'
```
[Supported Storage formats](/docs/en/docs/API.md#storage)
### Constant
```python
from dup_fmt import Constant, make_const
from dup_fmt.exceptions import FormatterError
const = make_const({
'%n': 'normal',
'%s': 'special',
})
try:
parse_const: Constant = const.parse(
value='This_is_constant_normal',
fmt='This_is_constant_%n'
)
parse_const.format('The value of %%s is %s')
except FormatterError as err:
print(err)
```
```text
>>> 'The value of %s is special'
```
> **Note**: \
> This package already implement environment constant object, `dup_fmt.EnvConstant`.
## FormatterGroup Object
The **FormatterGroup** object, `FormatterGroup`, which is the grouping of needed
mapping formatter objects and its alias formatter object ref name together. You
can define a name of formatter that you want, such as `name` for `Naming`, or
`timestamp` for `Datetime`.
**Parse**:
```python
from dup_fmt import make_group, Naming, Datetime, FormatterGroupType
group: FormatterGroupType = make_group({'name': Naming, 'datetime': Datetime})
group.parse(
'data_engineer_in_20220101_de',
fmt='{name:%s}_in_{timestamp:%Y%m%d}_{name:%a}'
)
```
```text
>>> {
>>> 'name': Naming.parse('data engineer', '%n'),
>>> 'timestamp': Datetime.parse('2022-01-01 00:00:00.000000', '%Y-%m-%d %H:%M:%S.%f')
>>> }
```
**Format**:
```python
from dup_fmt import FormatterGroup
from datetime import datetime
group_01: FormatterGroup = group({
'name': 'data engineer',
'datetime': datetime(2022, 1, 1)
})
group_01.format('{name:%c}_{timestamp:%Y_%m_%d}')
```
```text
>>> dataEngineer_2022_01_01
```
## License
This project was licensed under the terms of the [MIT license](LICENSE).
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"description": "# Data Utility Package: *Formatter*\n\n[](https://github.com/korawica/dup-fmt/actions/workflows/tests.yml)\n[](https://codecov.io/gh/korawica/dup-fmt)\n[](https://pypi.org/project/dup-fmt/)\n[](https://github.com/korawica/dup-fmt)\n\n**Type**: `DUP` | **Tag**: `Data Utility Package` `Data` `Utility` `Formatter`\n\n**Table of Contents**:\n\n- [Formatter Objects](#formatter-objects)\n - [Datetime](#datetime)\n - [Version](#version)\n - [Serial](#serial)\n - [Naming](#naming)\n - [Storage](#storage)\n - [Constant](#constant)\n- [FormatterGroup Object](#formattergroup-object)\n\nThis **Formatter** package was created for `parse` and `format` any string values\nthat match format pattern with Python regular expression. This package be the\nco-pylot project for stating to my **Python Software Developer** role.\n\n**Install from PyPI**:\n\n```shell\npip install dup-fmt\n```\n\n:dart: First objective of this project is include necessary formatter objects for\nany data components package which mean we can `parse` any complicate names on\ndata source and ingest the right names to in-house or data target.\n\nFor example, we want to get filename with the format like, `filename_20220101.csv`,\non the file system storage, and we want to incremental ingest the latest file with\ndate **2022-03-25** date. So we will implement `Datetime` object and parse\nthat filename to it,\n\n```python\nDatetime.parse('filename_20220101.csv', 'filename_%Y%m%d.csv').value == datetime.today()\n```\n\nThe above example is :yawning_face: **NOT SURPRISE!!!** for us because Python\nalready provide build-in package `datetime` to parse by `{dt}.strptime` and\nformat by `{dt}.strftime` with any datetime string value. This package will the\nspecial thing when we group more than one formatter objects together as\n`Naming`, `Version`, and `Datetime`.\n\n**For complex filename format like**:\n\n```text\n{filename:%s}_{datetime:%Y_%m_%d}.{version:%m.%n.%c}.csv\n```\n\nFrom above filename format string, the `datetime` package does not enough for\nthis scenario right? but you can handle by your hard-code object or create the\nbetter package than this project.\n\n> **Note**: \\\n> Any formatter object was implemented the `self.valid` method for help us validate\n> format string value like the above example scenario,\n> ```python\n> this_date = Datetime.parse('20220101', '%Y%m%d')\n> this_date.valid('any_files_20220101.csv', 'any_files_%Y%m%d.csv') # True\n> ```\n\n## Formatter Objects\n\n- [Datetime](#datetime)\n- [Version](#version)\n- [Serial](#serial)\n- [Naming](#naming)\n- [Storage](#storage)\n- [Constant](#constant)\n\nThe main purpose is **Formatter Objects** for `parse` and `format` with string\nvalue, such as `Datetime`, `Version`, and `Serial` formatter objects. These objects\nwere used for parse any filename with put the format string value. The formatter\nable to enhancement any format value from sting value, like in `Datetime`, for `%B`\nvalue that was designed for month shortname (`Jan`, `Feb`, etc.) that does not\nsupport in build-in `datetime` package.\n\n> **Note**: \\\n> The main usage of this formatter object is `parse` and `format` method.\n\n### Datetime\n\n```python\nfrom dup_fmt import Datetime\n\ndatetime = Datetime.parse(\n value='This_is_time_20220101_000101',\n fmt='This_is_time_%Y%m%d_%H%M%S'\n)\ndatetime.format('This_datetime_format_%Y%b-%-d_%H:%M:%S')\n```\n\n```text\n>>> 'This_datetime_format_2022Jan-1_00:01:01'\n```\n\n[Supported Datetime formats](/docs/en/docs/API.md#datetime)\n\n### Version\n\n```python\nfrom dup_fmt import Version\n\nversion = Version.parse(\n value='This_is_version_2_0_1',\n fmt='This_is_version_%m_%n_%c',\n)\nversion.format('New_version_%m%n%c')\n```\n\n```text\n>>> 'New_version_201'\n```\n\n[Supported Version formats](/docs/en/docs/API.md#version)\n\n### Serial\n\n```python\nfrom dup_fmt import Serial\n\nserial = Serial.parse(\n value='This_is_serial_62130',\n fmt='This_is_serial_%n'\n)\nserial.format('Convert to binary: %b')\n```\n\n```text\n>>> 'Convert to binary: 1111001010110010'\n```\n\n[Supported Serial formats](/docs/en/docs/API.md#serial)\n\n### Naming\n\n```python\nfrom dup_fmt import Naming\n\nnaming = Naming.parse(\n value='de is data engineer',\n fmt='%a is %n'\n)\nnaming.format('Camel case is %c')\n```\n\n```text\n>>> 'Camel case is dataEngineer'\n```\n\n[Supported Naming formats](/docs/en/docs/API.md#naming)\n\n### Storage\n\n```python\nfrom dup_fmt import Storage\n\nstorage = Storage.parse(\n value='This file have 250MB size',\n fmt='This file have %M size'\n)\nstorage.format('The byte size is: %b')\n```\n\n```text\n>>> 'The byte size is: 2097152000'\n```\n\n[Supported Storage formats](/docs/en/docs/API.md#storage)\n\n### Constant\n\n```python\nfrom dup_fmt import Constant, make_const\nfrom dup_fmt.exceptions import FormatterError\n\nconst = make_const({\n '%n': 'normal',\n '%s': 'special',\n})\ntry:\n parse_const: Constant = const.parse(\n value='This_is_constant_normal',\n fmt='This_is_constant_%n'\n )\n parse_const.format('The value of %%s is %s')\nexcept FormatterError as err:\n print(err)\n```\n\n```text\n>>> 'The value of %s is special'\n```\n\n> **Note**: \\\n> This package already implement environment constant object, `dup_fmt.EnvConstant`.\n\n## FormatterGroup Object\n\nThe **FormatterGroup** object, `FormatterGroup`, which is the grouping of needed\nmapping formatter objects and its alias formatter object ref name together. 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