Analyze stock
Project description
kabutobashi
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.
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
.
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.
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) -> dict:
return {"doubled_term": self.term * 2}
def process(self) -> BlockGlue:
# _process() method can be Tuple[Optional[dict], Optional[pd.DataFrame]]
res = self._process()
return BlockGlue(params=res, series=None, block_outputs={})
def factory(self, glue: BlockGlue) -> "UdfBlock":
# Omitted. In reality, processes are described.
...
def _factory(self, glue: BlockGlue) -> dict:
# 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.
sequenceDiagram
autonumber
participant G as glue()
participant UC as UdfBlock::class
create participant S1 as factory()
UC->>S1: create
create participant S2 as _factory()
UC->>S2: create or defined by user
create participant P1 as process()
UC->>P1: create
create participant P2 as _process()
UC->>P2: create or defined by user
Note over S1: Generate udf_block_instance
G->>+S1: Request
S1->>+S2: Request
Note over S2: User can modify _factory()
S2-->>S2: get params from glue
S2-->>S2: get series from glue
S2-->>-S1: params and series
create participant UI as UdfBlock::instance
S1->>UI: UdfBlock(params, series)
S1->>UI: setattr params to udf_block_instance
S1-->>-G: udf_block_instance
G->>+UI: udf_block_instance.process()
UI->>+P1: process()
Note over P1: execute process()
P1->>P2: Request
Note over P2: execute user defined function
P2-->>P1: params or series
P1-->>-UI: BlockGlue(params, series)
UI-->>-G: block_glue_instance
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.
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.
usage
import kabutobashi as kb
# 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)
initialize Database
import kabutobashi as kb
kb.KabutobashiDatabase().initialize()
# add data
kb.crawl_info_multiple(code="1375", page="1", database_dir="...")
kb.crawl_info_multiple(code="1375", page="2", database_dir="...")
kb.crawl_info_multiple(code="1375", page="etc...", database_dir="...")
# add data daily
kb.crawl_info(code="1375", database_dir="...")
# analysis and add data
kb.analysis(code="1375", database_dir="...")
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