# kabutobashi
[](https://github.com/gsy0911/kabutobashi/actions?query=workflow%3Apytest)
[](https://codecov.io/gh/gsy0911/kabutobashi)
[](https://github.com/psf/black)
[](https://pycqa.github.io/isort/)
[](http://mypy-lang.org/)
[](https://pypi.org/project/kabutobashi/)
[](https://pypi.org/project/kabutobashi/)
[](https://kabutobashi.readthedocs.io/en/latest/?badge=latest)
## concept
class-relationship.
- `E`: Entity
- `VO`: ValueObject
- `S`: Service
- `A`: Aggregate
```mermaid
graph TD;
subgraph Stock
stock[Stock:E]
brand[StockBrand:E]
record[StockRecord:E]
indicator[StockIndicator:E]
stock --> brand
stock --> record
stock --> indicator
end
subgraph Stock-to-Analysis
aggregate[StockCodeSingleAggregate:A]
processed[StockDataProcessed:VO]
estimated[StockDataEstimated:VO]
aggregate --- |Info| stock
aggregate --- |Method| processed
aggregate --- |Analysis| estimated
end
subgraph Repositories/Storage
repositories[(Storage/Database)] --- | read/write | stock
end
subgraph Pages
raw_html[RawHtml:VO]
decoder[Decoder:S]
decoded_html[DecodedHtml:VO]
raw_html --> decoder
decoder --> decoded_html
decoded_html --> repositories
decoded_html --> stock
end
subgraph Repositories/Web
web[[Web]] --> | crawl | raw_html
end
```
## usage
```python
import kabutobashi as kb
df = kb.example()
methods = kb.methods + [kb.basic, kb.pct_change, kb.volatility]
analysis = kb.stock_analysis
agg = kb.StockCodeSingleAggregate.of(entity=df, code="1234").with_processed(methods).with_estimated(stock_analysis=analysis)
print(agg)
# n日前までの営業日の日付リストを取得する関数
target_date = "2020-01-01"
date_list = kb.get_past_n_days(target_date, n=40)
```
# Core Concept
`@block`-decorator and `Flow`-class is important.
`@block` automatically generates input and output functions, allowing you to focus solely on the processing.
`Flow` allows you to focus solely on the process flow and input parameters.
## About `@block`-decorator
simple decorator is like below.
```python
def simple_decorator(func):
def wrap_func() -> str:
res = func()
return f"Hello, {res}"
return wrap_func
@simple_decorator
def world() -> str:
return "world"
world() # => "Hello, world"
```
A `decorator` is something that dynamically generates and adds processes to functions or classes, similar to its name.
First, prepare a function as follows and decorate it with `@block`.
```python
from kabutobashi import block
@block()
class UdfBlock:
term: int = 10
def _process(self):
return {"doubled_term": self.term * 2}
```
The classes above is equivalent to the following class definition.
```python
import pandas as pd
from kabutobashi.domain.entity.blocks import BlockGlue
class UdfBlock:
series: pd.DataFrame = None
params: dict = None
term: int = 10
block_name: str = "udf_block"
def _process(self):
return {"doubled_term": self.term * 2}
def process(self):
return self._process()
def factory(self, glue: BlockGlue) -> "UdfBlock":
# Omitted. In reality, processes are described.
...
def _factory(self, glue: BlockGlue) -> "UdfBlock":
# Omitted. In reality, processes are described.
...
def glue(self, glue: BlockGlue) -> BlockGlue:
# Omitted. In reality, processes are described.
...
```
In classes decorated with `@block`, it is not recommended to execute the `__init__()` method. Instead, it is recommended to use the `factory()` class-method.
`factory()` method description.
`process()` method description.
`glue()` method description.
Up to this point, the use of the `@block` decorator with classes such as UdfClass has described, but using the Block class on its own is not intended. Please read the following explanation of the `Flow` class for more details.
### Read-Block
- input
- params
- output
- series
### Crawl-Block
- input
- params
- output
- output.params
### Extract-Block
- input
- params
- output
- output.params
### PreProcess-Block
- input
- series
- params
- output
- series
### Process-Block
- input
- series
- params
- output
- output.series
### Parameterize-Block
- input
- series
- params
- output
- output.params
### Reduce-Block
- input
- series
- params
- output
- params
## About `Flow`-class
> Blocks are meant to be combined.
Processes always consist of combinations of multiple simple operations. And the only tedious part is aligning their inputs and outputs.
Therefore, in `Flow`-class, it automatically resolves the sequence of those processes for users, as long as you provide the initial values.
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"description": "# kabutobashi\n\n[](https://github.com/gsy0911/kabutobashi/actions?query=workflow%3Apytest)\n[](https://codecov.io/gh/gsy0911/kabutobashi)\n[](https://github.com/psf/black)\n[](https://pycqa.github.io/isort/)\n[](http://mypy-lang.org/)\n\n[](https://pypi.org/project/kabutobashi/)\n[](https://pypi.org/project/kabutobashi/)\n[](https://kabutobashi.readthedocs.io/en/latest/?badge=latest)\n\n## concept\n\nclass-relationship.\n\n- `E`: Entity\n- `VO`: ValueObject\n- `S`: Service\n- `A`: Aggregate\n\n```mermaid\ngraph TD;\n \n subgraph Stock\n stock[Stock:E]\n brand[StockBrand:E]\n record[StockRecord:E]\n indicator[StockIndicator:E]\n \n stock --> brand\n stock --> record\n stock --> indicator\n end\n\n subgraph Stock-to-Analysis\n aggregate[StockCodeSingleAggregate:A]\n processed[StockDataProcessed:VO]\n estimated[StockDataEstimated:VO]\n \n aggregate --- |Info| stock\n aggregate --- |Method| processed\n aggregate --- |Analysis| estimated\n end\n\n subgraph Repositories/Storage\n repositories[(Storage/Database)] --- | read/write | stock\n end\n\n subgraph Pages\n raw_html[RawHtml:VO]\n decoder[Decoder:S]\n decoded_html[DecodedHtml:VO]\n\n raw_html --> decoder\n decoder --> decoded_html\n decoded_html --> repositories\n decoded_html --> stock\n end\n\n subgraph Repositories/Web\n web[[Web]] --> | crawl | raw_html\n end\n```\n\n\n## usage\n\n```python\nimport kabutobashi as kb\n\ndf = kb.example()\nmethods = kb.methods + [kb.basic, kb.pct_change, kb.volatility]\nanalysis = kb.stock_analysis\nagg = kb.StockCodeSingleAggregate.of(entity=df, code=\"1234\").with_processed(methods).with_estimated(stock_analysis=analysis)\nprint(agg)\n\n# n\u65e5\u524d\u307e\u3067\u306e\u55b6\u696d\u65e5\u306e\u65e5\u4ed8\u30ea\u30b9\u30c8\u3092\u53d6\u5f97\u3059\u308b\u95a2\u6570\ntarget_date = \"2020-01-01\"\ndate_list = kb.get_past_n_days(target_date, n=40)\n\n```\n\n\n# Core Concept\n\n`@block`-decorator and `Flow`-class is important.\n`@block` automatically generates input and output functions, allowing you to focus solely on the processing.\n`Flow` allows you to focus solely on the process flow and input parameters.\n\n## About `@block`-decorator\n\nsimple decorator is like below.\n\n```python\ndef simple_decorator(func):\n def wrap_func() -> str:\n res = func()\n return f\"Hello, {res}\"\n return wrap_func\n\n\n@simple_decorator\ndef world() -> str:\n return \"world\"\n\n\nworld() # => \"Hello, world\"\n```\n\nA `decorator` is something that dynamically generates and adds processes to functions or classes, similar to its name.\n\n\nFirst, prepare a function as follows and decorate it with `@block`.\n\n```python\nfrom kabutobashi import block\n\n@block()\nclass UdfBlock:\n term: int = 10\n\n def _process(self):\n return {\"doubled_term\": self.term * 2}\n```\n\nThe classes above is equivalent to the following class definition.\n\n```python\nimport pandas as pd\nfrom kabutobashi.domain.entity.blocks import BlockGlue\n\nclass UdfBlock:\n series: pd.DataFrame = None\n params: dict = None\n term: int = 10\n block_name: str = \"udf_block\"\n\n def _process(self):\n return {\"doubled_term\": self.term * 2}\n \n def process(self):\n return self._process()\n\n def factory(self, glue: BlockGlue) -> \"UdfBlock\":\n # Omitted. In reality, processes are described.\n ...\n\n def _factory(self, glue: BlockGlue) -> \"UdfBlock\":\n # Omitted. In reality, processes are described.\n ...\n\n def glue(self, glue: BlockGlue) -> BlockGlue:\n # Omitted. In reality, processes are described.\n ...\n\n```\n\nIn classes decorated with `@block`, it is not recommended to execute the `__init__()` method. Instead, it is recommended to use the `factory()` class-method.\n\n`factory()` method description.\n`process()` method description.\n`glue()` method description.\n\n\nUp to this point, the use of the `@block` decorator with classes such as UdfClass has described, but using the Block class on its own is not intended. Please read the following explanation of the `Flow` class for more details.\n\n### Read-Block\n\n- input\n - params\n- output\n - series\n\n### Crawl-Block\n\n- input\n - params\n- output\n - output.params\n\n### Extract-Block\n\n- input\n - params\n- output\n - output.params\n\n### PreProcess-Block\n\n- input\n - series\n - params\n- output\n - series\n\n### Process-Block\n\n- input\n - series\n - params\n- output\n - output.series\n\n### Parameterize-Block\n\n- input\n - series\n - params\n- output\n - output.params\n\n### Reduce-Block\n\n- input\n - series\n - params\n- output\n - params\n\n## About `Flow`-class\n\n> Blocks are meant to be combined.\n\nProcesses always consist of combinations of multiple simple operations. And the only tedious part is aligning their inputs and outputs.\n\nTherefore, in `Flow`-class, it automatically resolves the sequence of those processes for users, as long as you provide the initial values.\n\n",
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