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Ichinga Samuel
2024-11-10 12:25:50 +01:00
parent d9bd84bc2e
commit f56d0c85b3
39 changed files with 1538 additions and 1179 deletions
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backtesting/backtest_data_01_05_24_06_05_24.json
+12 -12
View File
@@ -1,17 +1,17 @@
{
"balance": 281.16,
"balance": 434.73,
"profit": 0,
"equity": 281.16,
"equity": 434.73,
"margin": 0.0,
"margin_free": 281.16,
"margin_free": 434.73,
"margin_level": 0,
"wins": 85,
"losses": 95,
"total": 180,
"win_percentage": 47.22,
"win": 877.56,
"loss": -946.4,
"net_profit": -68.84,
"profit_factor": 0.93,
"profitability": -19.67
"wins": 97,
"losses": 110,
"total": 207,
"win_percentage": 46.86,
"win": 1101.92,
"loss": -1017.19,
"net_profit": 84.73,
"profit_factor": 1.08,
"profitability": 24.21
}
check.py
+20
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@@ -0,0 +1,20 @@
import asyncio
def run():
for i in range(10):
print('running')
async def run_async():
for i in range(10):
await asyncio.sleep(1)
print('running async')
async def main():
await run_async()
run()
asyncio.run(main())
docs/lib/candle.md
+14 -51
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@@ -2,19 +2,20 @@
Candle and Candles classes for handling bars from the MetaTrader 5 terminal.
## Table of Contents
- [Candle](#candle)
- [Candle](#candle.candle)
- [\_\_init\_\_](#candle.__init__)
- [set_attributes](#candle.set_attributes)
- [is_bullish](#candle.is_bullish)
- [is_bearish](#candle.is_bearish)
- [Candles](#candles)
- [dict](#candle.dict)
- [Candles](#candles.candles)
- [\_\_init\_\_](#candles.__init__)
- [ta](#candles.ta)
- [ta_lib](#candles.ta_lib)
- [data](#candles.data)
- [rename](#candles.rename)
<a id="candle"></a>
<a id="candle.candle"></a>
### Candle
```python
class Candle
@@ -91,18 +92,18 @@ def dict(self, exclude: set = None, include: set = None) -> Dict[str, Any]
```
Return a dictionary representation of the Candle object.
#### Parameters:
| Name | Type | Description |
|-----------|------------|-----------------------------------------------------------------------------|
| `exclude` | `set[str]` | A set of attributes to exclude from the dictionary. |
| `include` | `set[str]` | A set of attributes to include in the dictionary. |
| Name | Type | Description |
|-----------|------------|-----------------------------------------------------|
| `exclude` | `set[str]` | A set of attributes to exclude from the dictionary. |
| `include` | `set[str]` | A set of attributes to include in the dictionary. |
#### Returns:
| Type | Description |
|---------------|--------------------------------------------------|
| `Dict[str, Any]` | A dictionary representation of the Candle object.|
| Type | Description |
|------------------|---------------------------------------------------|
| `Dict[str, Any]` | A dictionary representation of the Candle object. |
### <a id="candles"></a> Candles
### <a id="candles.candles"></a> Candles
```python
class Candles(Generic[_Candle])
```
@@ -111,10 +112,9 @@ object. All the data pulled from the chart is stored as a pandas DataFrame objec
This class can be sliced, iterated over, and indexed like a sequence. It also has access to the pandas_ta library.
Indexing it returns a Candle object. It can be sliced to return a new instance of the class with the sliced candles.
This slices and resets the index of the underlying dataframe object. Key based indexing is also supported on the candles
object for accessing the columns of the underlying data attribute. Add operations between two candles objects or between a
candles object and a candle object are also supported.
object for accessing the columns of the underlying data attribute.
### Attributes
### Attributes:
The attributes of this class vary depending on the columns of underlying **data** attribute. i.e. each column of the **data**
attribute is an attribute of the class.
@@ -203,40 +203,3 @@ Rename columns of the data object.
| Type | Description |
|-----------|---------------------------------------------------------------------------|
| `Candles` | A new instance of the class with the renamed columns if inplace is False. |
<id="candles.visualize"></a>
### visualize
```python
async def visualize(self, *, count: int = 50, type='candle', savefig: str | dict = None, addplot: dict = None,
style: str = 'charles', ylabel: str = 'Price', title: str = 'Chart', **kwargs)
```
Visualize the candles using the mplfinance library.
#### Parameters:
| Name | Type | Description | Default |
|----------|------------------|-----------------------------------------------------------------------------------------------|---------|
| `count` | `int` | The number of candles to visualize. | 50 |
| `type` | `str` | The type of chart to plot. | 'candle'|
| `savefig`| `str` or `dict` | The path to save the figure or a dictionary of keyword arguments to pass to the savefig method.| None |
| `addplot`| `dict` | A dictionary of keyword arguments to pass to the addplot method. | None |
| `style` | `str` | The style of the chart. | 'charles'|
| `ylabel` | `str` | The label of the y-axis. | 'Price' |
| `title` | `str` | The title of the chart. | 'Chart' |
| `kwargs` | `Any` | Additional keyword arguments to pass to the plot method. | |
<id="candles.make_addplot"></a>
```python
def make_addplot(self, *, count: int = 50, columns: list = None, **kwargs) -> dict
```
Make subplots for adding to the main plot.
#### Parameters:
| Name | Type | Description | Default |
|-----------|--------|-----------------------------------------------------------------------------------------------|---------|
| `count` | `int` | The number of candles to visualize. | 50 |
| `columns` | `list` | The columns to plot. | None |
| `kwargs` | `Any` | Additional keyword arguments to pass to the addplot method. | |
#### Returns:
| Type | Description |
|------|-----------------|
| dict | A makeplot dict |
docs/lib/executor.md
+45 -53
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@@ -3,11 +3,9 @@
## Table of Contents
- [Executor](#executor.Executor)
- [__init__](#executor.__init__)
- [add_workers](#executor.add_workers)
- [remove_workers](#executor.remove_workers)
- [add_worker](#executor.add_worker)
- [run](#executor.run)
- [trade](#executor.trade)
- [add_function](#executor.add_function)
- [add_coroutine](#executor.add_coroutine)
- [run_function](#executor.run_function)
- [execute](#executor.execute)
<a id='executor.Executor'></a>
@@ -17,12 +15,12 @@ class Executor
```
Executor class for running multiple strategies on multiple symbols concurrently.
#### Attributes:
| Name | Type | Description | Default |
|--------------|----------------------|------------------------------------------------|---------|
| `executor` | `ThreadPoolExecutor` | The default thread executor. | None |
| `workers` | `list` | List of strategies. | [] |
| `coroutines` | `dict` | Dictionary of coroutines and keyword arguments | {} |
| `functions` | `dict` | Dictionary of functions and keyword arguments | {} |
| Name | Type | Description | Default |
|--------------------|----------------------|------------------------------------------------|---------|
| `executor` | `ThreadPoolExecutor` | The default thread executor. | None |
| `strategy_runners` | `list[Strategy]` | List of strategies. | [] |
| `coroutines` | `dict` | Dictionary of coroutines and keyword arguments | {} |
| `functions` | `dict` | Dictionary of functions and keyword arguments | {} |
<a id="executor.__init__"></a>
#### \_\_init\_\_
@@ -31,72 +29,66 @@ def __init__(self):
```
Initialize the executor class.
<a id="executor.add_workers"></a>
### add\_workers
<a id="executor.add_coroutine"></a>
### add_coroutine
```python
def add_workers(strategies: Sequence[type(Strategy)])
def add_coroutine(self,*,coroutine: Callable | Coroutine,kwargs: dict = None,on_separate_thread=False):
```
Add multiple strategies at once
#### Arguments:
| Name | Type | Description |
|--------------|----------------------------|---------------------------|
| `strategies` | `Sequence[type(Strategy)]` | A sequence of strategies. |
Submit a coroutine to the executor. The coroutines are run in parallel using *asyncio.gather* except when the
on_spate_thread flag is set to True. In that case, the coroutine is run in a separate thread.
<a id="executor.remove_workers"></a>
### remove\_workers
#### Arguments:
| Name | Type | Description |
|----------------------|------------|-------------------------------------------------|
| `coroutine` | `Callable` | The coroutine |
| `kwargs` | `Dict` | The keyword arguments to pass to the coroutine. |
| `on_separate_thread` | `bool` | If True run the coroutine on a separate thread |
<a id="executor.add_function"></a>
### add_function
```python
def remove_workers(*symbols: Sequence[Symbol])
def add_function(self, *, function: Callable, kwargs: dict = None)
```
Removes any worker running on a symbol not successfully initialized.
#### Arguments:
| Name | Type | Description |
|-----------|--------------------|------------------------|
| `symbols` | `Sequence[Symbol]` | A sequence of symbols. |
Submit a function to the executor. Each functions runs on a separate thread.
<a id="executor.add_worker"></a>
### add\_worker
```python
def add_worker(strategy: type(Strategy))
```
Add a strategy instance to the list of workers
#### Arguments:
| Name | Type | Description |
|------------|------------------|----------------------|
| `strategy` | `type(Strategy)` | A strategy instance. |
| Name | Type | Description |
|------------|------------|--------------------------------------------|
| `function` | `Callable` | The function to run in the executor |
| `kwargs` | `Dict` | Keyword arguments to pass to the function. |
<a id="executor.run"></a>
### run
<a id="executor.run_function"></a>
### run_function
```python
@staticmethod
def run(func: Callable|Coroutine, kwargs: dict)
def run_function(function: Callable, kwargs: dict)
```
Wrap the input coroutine function with 'asyncio.run' so that it can be executed in a threadpool executor.
#### Arguments:
| Name | Type | Description |
|----------|-----------|--------------------------------------------|
| `func` | `Callable | Coroutine` |A coroutine function.|
| `kwargs` | `Dict` | Keyword arguments to pass to the function. |
| Name | Type | Description |
|------------|------------|--------------------------------------------|
| `function` | `Callable` | Run a function in the executor |
| `kwargs` | `Dict` | Keyword arguments to pass to the function. |
<a id="executor.trade"></a>
### trade
<a id="executor.exit"></a>
### exit
```python
def trade(strategy: Strategy)
async def exit()
```
Wrap coroutine trade method of each strategy with 'asyncio.run'.
#### Arguments:
| Name | Type | Description |
|------------|------------|----------------------|
| `strategy` | `Strategy` | A strategy instance. |
Shutdowns the executor. Due to the nature of threadpool executors, shutdown is not usually an immediate process.
This exit function is added as a coroutine function to the bot or backtester during initialization.
<a id="executor.execute"></a>
### execute
```python
async def execute(workers: int = 5)
def execute(workers: int = 5)
```
Run the strategies with a threadpool executor.
#### Arguments:
| Name | Type | Description |
|-----------|-------|-----------------------------------------------------------|
| `workers` | `int` | Number of workers to use in executor pool. Defaults to 5. |
#### Notes:
No matter the number specified, the executor will always use a minimum of 5 workers.
No matter the number specified, the number of workers will always be greater than equal to the minimum number of
workers required to run all functions, coroutines and strategies added to the executor.
docs/lib/history.md
+73 -134
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@@ -1,19 +1,17 @@
# History
## Table of contents
- [History](#history)
- [\_\_init\_\_](#__init__)
- [init](#init)
- [get_deals](#get_deals)
- [get_deals_ticket](#get_deals_ticket)
- [get_deals_position](#get_deals_position)
- [deals_total](#deals_total)
- [get_orders](#get_orders)
- [get_orders_position](#get_orders_position)
- [get_order_ticket](#get_order_ticket)
- [orders_total](#orders_total)
- [History](#history.history)
- [\_\_init\_\_](#history.__init__)
- [initialize](#history.initialize)
- [get_deals](#history.get_deals)
- [get_deals_by_ticket](#history.get_deals_by_ticket)
- [get_deals_by_position](#history.get_deals_by_position)
- [get_orders](#history.get_orders)
- [get_orders_by_position](#history.get_orders_by_position)
- [get_orders_by_ticket](#history.get_orders_by_ticket)
<a id='history'></a>
<a id='history.history'></a>
### History
```python
class History
@@ -27,170 +25,111 @@ The history class handles completed trade deals and trade orders in the trading
| `total_deals` | `int` | Total number of deals | 0 |
| `total_orders` | `int` | Total number orders | 0 |
| `group` | `str` | Filter for selecting history by symbols. | "" |
| `ticket` | `int` | Filter for selecting history by ticket number | 0 |
| `position` | `int` | Filter for selecting history deals by position | 0 |
| `initialized` | `bool` | check if initial request has been sent to the terminal to get history. | False |
| `mt5` | `MetaTrader` | MetaTrader instance | None |
| `config` | `Config` | Config instance | None |
<a id='__init__'></a>
<a id='history.__init__'></a>
### \_\_init\_\_
```python
def __init__(*,
date_from: datetime | float = 0,
date_to: datetime | float = 0,
group: str = "",
ticket: int = 0,
position: int = 0)
def __init__(*, date_from: datetime | float, date_to: datetime | float, group: str = "")
```
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|-------------|-------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------|
| `date_from` | `datetime\|float` | Date the deals are requested from. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. Defaults to twenty-four hours from the current time in 'utc' | 0 |
| `date_to` | `datetime\|float` | Date up to which the deals are requested. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. Defaults to the current time in "utc" | 0 |
| `group` | `str` | Filter for selecting history by symbols. | "" |
| `ticket` | `int` | Filter for selecting history by ticket number | 0 |
| `position` | `int` | Filter for selecting history deals by position | 0 |
<a id='init'></a>
### init
<a id='history.initialize'></a>
### initialize
```python
async def init(deals=True, orders=True) -> bool
async def initialize() -> bool
```
Get history deals and orders
#### Parameters
| Name | Type | Description | Default |
|----------|--------|---------------------------------------------------------------|---------|
| `deals` | `bool` | If true get history deals during initial request to terminal | True |
| `orders` | `bool` | If true get history orders during initial request to terminal | True |
#### Returns
| Name | Type | Description | Default |
|--------|--------|-------------------------------------------------|---------|
| `bool` | `bool` | True if all requests were successful else False | False |
Get deals and orders within the timeframe specified in the constructor.
<a id='get_deals'></a>
<a id='history.get_deals'></a>
### get_deals
```python
async def get_deals(self, *, date_from: datetime | int = None, date_to: datetime | int = None, group: str = '',
retries=3) -> list[TradeDeal]
async def get_deals(self) -> tuple[TradeDeal, ...]
```
#### Parameters:
| Name | Type | Description | Default |
|-------------|-------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------|
| `date_from` | `datetime\|float` | Date the deals are requested from. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. Defaults to twenty-four hours from the current time in 'utc' | None |
| `date_to` | `datetime\|float` | Date up to which the deals are requested. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. Defaults to the current time in "utc" | None |
| `group` | `str` | Filter for selecting history by symbols. | "" |
| `retries` | `int` | Number of retries if the request fails. | 3 |
Get deals from trading history using the parameters set in the constructor.
#### Returns
| Name | Type | Description |
|---------|-------------------------|-----------------------|
| `deals` | `tuple[TradeDeal, ...]` | A list of trade deals |
<a id='history.get_deals_by_ticket'></a>
### get_deals_by_ticket
```python
def get_deals_by_ticket(self, *, ticket: int) -> tuple[TradeDeal, ...]
```
Get deals by ticket number. This filters deals by ticket based on the deals already fetched in initialize.
#### Parameters
| Name | Type | Description |
|----------|-------|----------------------|
| `ticket` | `int` | Ticket number to get |
#### Returns:
| Name | Type | Description | Default |
|---------|--------------------|-----------------------|---------|
| `deals` | `tuple[TradeDeal]` | A list of trade deals | [] |
| Name | Type | Description |
|---------|-------------------------|------------------------|
| `deals` | `tuple[TradeDeal, ...]` | A tuple of trade deals |
<a id='get_deals_ticket'></a>
### get_deals_ticket
<a id='history.get_deals_by_position'></a>
### get_deals_by_position
```python
async def get_deals_ticket(self, *, ticket: int) -> tuple[TradeDeal]
```
Get deals by ticket number
#### Parameters:
| Name | Type | Description | Default |
|----------|------|-----------------------|---------|
| `ticket` | `int`| Ticket number to get | 0 |
#### Returns:
| Name | Type | Description | Default |
|---------|--------------------|-----------------------|---------|
| `deals` | `tuple[TradeDeal]` | A list of trade deals | [] |
<a id='get_deals_position'></a>
### get_deals_position
```python
async def get_deals_position(self, *, position: int) -> list[TradeDeal]
async def get_deals_by_position(self, *, position: int) -> tuple[TradeDeal, ...]
```
Get deals by position
#### Parameters:
| Name | Type | Description | Default |
|------------|------|-----------------------|---------|
| `position` | `int`| Position number to get | 0 |
#### Parameters
| Name | Type | Description |
|------------|-------|------------------------|
| `position` | `int` | Position number to get |
#### Returns:
| Name | Type | Description | Default |
|---------|--------------------|-----------------------|---------|
| `deals` | `tuple[TradeDeal]` | A list of trade deals | [] |
<a id='deals_total'></a>
### deals_total
```python
async def deals_total() -> int
```
Get total number of deals within the specified period in the constructor.
#### Returns
| Name | Type | Description | Default |
|---------------|-------|-----------------------|---------|
| `total_deals` | `int` | Total number of deals | 0 |
| Name | Type | Description |
|---------|-------------------------|------------------------|
| `deals` | `tuple[TradeDeal, ...]` | A tuple of trade deals |
<a id='get_orders'></a>
<a id='history.get_orders'></a>
### get_orders
```python
async def get_orders(self, *, date_from: datetime | int = None, date_to: datetime | int = None, group: str = '',
retries=3) -> tuple[TradeOrder]
async def get_orders(self) -> tuple[TradeOrder, ...]
```
Get orders from trading history using the parameters set in the constructor.
#### Parameters
| Name | Type | Description | Default |
|-------------|-------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------|
| `date_from` | `datetime\|float` | Date the deals are requested from. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. Defaults to twenty-four hours from the current time in 'utc' | None |
| `date_to` | `datetime\|float` | Date up to which the deals are requested. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. Defaults to the current time in "utc" | None |
| `group` | `str` | Filter for selecting history by symbols. | "" |
#### Returns
| Name | Type | Description | Default |
|----------|---------------------|------------------------|---------|
| `orders` | `tuple[TradeOrder]` | A list of trade orders | [] |
<a id='get_orders_position'></a>
### get_orders_position
<a id='history.get_orders_by_position'></a>
### get_orders_by_position
```python
async def get_orders_position(self, *, position: int) -> tuple[TradeOrder]
def get_orders_by_position(self, *, position: int) -> tuple[TradeOrder, ...]
```
Get orders by position.
#### Parameters
| Name | Type | Description | Default |
|------------|------|-----------------------|---------|
| `position` | `int`| Position number to get | 0 |
| Name | Type | Description |
|------------|-------|------------------------|
| `position` | `int` | Position number to get |
#### Returns
| Name | Type | Description | Default |
|----------|---------------------|------------------------|---------|
| `orders` | `tuple[TradeOrder]` | A list of trade orders | [] |
| Name | Type | Description |
|----------|--------------------------|-------------------------|
| `orders` | `tuple[TradeOrder, ...]` | A tuple of trade orders |
<a id='get_order_ticket'></a>
### get_order_ticket
<a id='history.get_orders_by_ticket'></a>
### get_orders_by_ticket
```python
async def get_order_ticket(self, ticket: int | None = None) -> TradeOrder
def get_orders_by_ticket(self, *, position: int) -> tuple[TradeOrder, ...]
```
Get a single order by ticket number.
Get orders by ticket number. This filters orders by ticket based on the orders already fetched in initialize.
#### Parameters
| Name | Type | Description | Default |
|----------|-------|----------------------|---------|
| `ticket` | `int` | Ticket number to get | 0 |
| Name | Type | Description |
|----------|-------|----------------------|
| `ticket` | `int` | ticket number to get |
#### Returns
| Name | Type | Description | Default |
|----------|---------------------|------------------------|---------|
| `order` | `TradeOrder` | A single trade order | None |
<a id='orders_total'></a>
### orders_total
```python
async def orders_total() -> int
```
Get total number of orders within the specified period in the constructor.
#### Returns
| Name | Type | Description | Default |
|----------------|-------|---------------------|---------|
| `total_orders` | `int` | Total number orders | 0 |
| Name | Type | Description |
|----------|--------------------------|-------------------------|
| `orders` | `tuple[TradeOrder, ...]` | A tuple of trade orders |
docs/lib/order.md
+75 -46
View File
@@ -1,24 +1,26 @@
# Order
## Table of contents
- [Order](#Order)
- [\_\_init\_\_](#__init__)
- [orders_total](#orders_total)
- [get_order](#get_order)
- [get_orders](#get_orders)
- [check](#check)
- [send](#send)
- [calc_margin](#calc_margin)
- [calc_profit](#calc_profit)
- [Order](#order.order)
- [\_\_init\_\_](#order.__init__)
- [orders_total](#order.orders_total)
- [get_order](#order.get_pending_order)
- [get_orders](#order.get_pending_orders)
- [check](#order.check)
- [send](#order.send)
- [calc_margin](#order.calc_margin)
- [calc_profit](#order.calc_profit)
- [calc_loss](#order.calc_loss)
- [request](#order.request)
<a id="Order"></a>
<a id="order.order"></a>
### Order
```python
class Order(TradeRequest)
class Order(_Base, TradeRequest)
```
Trade order related functions and attributes. Subclass of TradeRequest.
<a id="__init__"></a>
<a id="order.__init__"></a>
### \_\_init\_\_
```python
def __init__(**kwargs)
@@ -32,102 +34,129 @@ Provides default values for action, type_time and type_filling if not provided.
| `type_time` | `OrderTime` | Order time | OrderTime.DAY |
| `type_filling` | `OrderFilling` | Order filling | OrderFilling.FOK |
<a id="orders_total"></a>
### <a id=order.Order.orders_total> orders_total
<a id="order.orders_total"></a>
```python
async def orders_total()
```
Get the total number of active orders.
Get the total number of active pending orders.
#### Returns
| Type | Description |
|-------|-------------------------------|
| `int` | total number of active orders |
<a id="get_order"></a>
### get_order
<a id="order.get_pending_order"></a>
### get_pending order
```python
async def get_order(self, ticket: int) -> TradeOrder
async def get_pending_order(self, ticket: int) -> TradeOrder
```
Get an active trade order by ticket.
Get an active pending trade order by ticket.
<a id="get_orders"></a>
### get_orders
<a id="order.get_pending_orders"></a>
### get_pending_orders
```python
async def get_orders(self, *, ticket: int = 0, symbol: str = '', group: str = '', retries=3) -> tuple[TradeOrder]:
async def get_pending_orders(self, *, ticket: int = 0, symbol: str = '', group: str = '') -> tuple[TradeOrder, ...]:
```
Get active trade orders. If ticket is provided, it will return the order with the specified ticket.
If symbol is provided, it will return all orders for the specified symbol.
If group is provided, it will return all orders for the specified group.
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|----------|--------|--------------------------------------|---------|
| `ticket` | `int` | Order ticket | 0 |
| `symbol` | `str` | Symbol name | '' |
| `group` | `str` | Group name | '' |
#### Returns
| Type | Description |
|---------------------|------------------------------------------------------|
| `tuple[TradeOrder]` | A Tuple of active trade orders as TradeOrder objects |
#### Raises
| Exception | Description |
|--------------|-------------------|
| `OrderError` | If not successful |
#### Returns:
| Type | Description |
|--------------------------|------------------------------------------------------|
| `tuple[TradeOrder, ...]` | A Tuple of active trade orders as TradeOrder objects |
<a id="check"></a>
<a id="order.check"></a>
### check
```python
async def check() -> OrderCheckResult
async def check(**kwargs) -> OrderCheckResult
```
Check funds sufficiency for performing a required trading operation and the possibility of executing it at the current market price.
#### Returns
#### Parameters:
| Type | Description |
|--------|----------------------------------------------|
| kwargs | Update the request dict with extra arguments |
Check if an order is okay.
#### Returns:
| Type | Description |
|--------------------|----------------------------|
| `OrderCheckResult` | An OrderCheckResult object |
#### Raises:
| Exception | Description |
|--------------|-------------------|
| `OrderError` | If not successful |
<a id="send"></a>
<a id="order.send"></a>
### send
```python
async def send() -> OrderSendResult
```
Send a request to perform a trading operation from the terminal to the trade server.
#### Returns
#### Returns:
| Type | Description |
|-------------------|---------------------------|
| `OrderSendResult` | An OrderSendResult object |
#### Raises:
| Exception | Description |
|--------------|-------------------|
| `OrderError` | If not successful |
<a id="calc_margin"></a>
### calc_margin
<a id="order.calc_margin"></a>
### calc_margin:
```python
async def calc_margin() -> float
```
Return the required margin in the account currency to perform a specified trading operation.
#### Returns
#### Returns:
| Type | Description |
|---------|-----------------------------------|
| `float` | Returns float value if successful |
#### Raises
| Exception | Description |
|--------------|-------------------|
| `OrderError` | If not successful |
<a id="calc_profit"></a>
<a id="order.calc_profit"></a>
### calc_profit
```python
async def calc_profit() -> float
```
Return profit in the account currency for a specified trading operation.
#### Returns:
| Type | Description |
|---------|-----------------------------------|
| `float` | Returns float value if successful |
| `None` | If not successful |
<a id="order.calc_loss"></a>
### calc_profit
```python
async def calc_loss() -> float
```
Return loss in the account currency for a specified trading operation.
#### Returns
| Type | Description |
|---------|-----------------------------------|
| `float` | Returns float value if successful |
| `None` | If not successful |
<a id="order.request"></a>
### request
```python
@property
async def request() -> dict
```
Return the trade request object as a dict
#### Returns
| Type | Description |
|--------|----------------------------------|
| `dict` | Returns the trade request object |
docs/lib/positions.md
+98 -81
View File
@@ -1,18 +1,17 @@
# Positions
## Table of contents
- [Positions](#positions)
- [Attributes](#attributes)
- [\_\_init\_\_](#__init__)
- [positions_total](#positions_total)
- [position_get](#position_get)
- [positions_get](#positions_get)
- [close](#close)
- [close_by](#close_by)
- [close_position](#close_position)
- [close_all](#close_all)
- [Positions](#positions.positions)
- [\_\_init\_\_](#positions.__init__)
- [get_positions](#positions.get_positions)
- [get_position_by_ticket](#positions.get_position_by_ticket)
- [get_positions_by_symbol](#positions.get_positions_by_symbol)
- [close](#positions.close)
- [close_position_by_ticket](#positions.close_position_by_ticket)
- [close_position](#positions.close_position)
- [close_all](#positions.close_all)
<a id="positions"></a>
<a id="positions.positions"></a>
### Positions
```python
class Positions
@@ -20,116 +19,134 @@ class Positions
Get and handle Open positions.
#### Attributes
| Name | Type | Description | Default |
|----------|--------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------|
| `symbol` | `str` | Financial instrument name. | "" |
| `group` | `str` | The filter for arranging a group of necessary symbols. Optional named parameter. If the group is specified, the function returns only positions meeting a specified criteria for a symbol name. | "" |
| `ticket` | `int` | Position ticket. | 0 |
| `mt5` | `MetaTrader` | MetaTrader instance. | None |
| Name | Type | Description |
|-------------|-----------------------------|----------------------------|
| `positions` | `tuple[TradePosition, ...]` | Financial instrument name. |
| `mt5` | `MetaTrader` | MetaTrader instance. |
<a id="__init__"></a>
<a id="positions.__init__"></a>
### \_\_init\_\_
```python
def __init__(*, symbol: str = "", group: str = "", ticket: int = 0)
def __init__()
```
Get Open Positions.
#### Arguments
| Name | Type | Description | Default |
|----------|-------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------|
| `symbol` | `str` | Financial instrument name. | "" |
| `group` | `str` | The filter for arranging a group of symbols. Optional named parameter. If the group is specified, the function returns only positions meeting a specified criteria for a symbol name. | "" |
| `ticket` | `int` | Position ticket. | 0 |
Initialize a position instance
<a id="positions_total"></a>
### positions_total
```python
async def positions_total() -> int
```
Get the number of open positions.
#### Returns
| Type | Description |
|-------|---------------------------------------|
| `int` | Return total number of open positions |
<a id="positions_get"></a>
### positions_get
<a id="positions.get_position"></a>
### get_positions
```python
async def positions_get(self, symbol: str = '', group: str = '', ticket: int = 0, retries=3) -> list[TradePosition]:
async def get_positions(self) -> tuple[TradePosition, ...]:
```
Get open positions with the ability to filter by symbol or ticket.
#### Arguments
| Name | Type | Description | Default |
|----------|--------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------|
| `symbol` | `str` | Financial instrument name. | "" |
| `group` | `str` | The filter for arranging a group of symbols. Optional named parameter. If the group is specified, the function returns only positions meeting a specified criteria for a symbol name. | "" |
| `ticket` | `int` | Position ticket. | 0 |
Get open positions
#### Returns
| Type | Description |
|-----------------------|--------------------------------|
| `list[TradePosition]` | A list of open trade positions |
| Type | Description |
|-----------------------------|--------------------------------|
| `tuple[TradePosition, ...]` | A list of open trade positions |
<a id="position_get"></a>
### position_get
<a id="positions.get_position_by_ticket"></a>
### get_position_by_ticket
```python
async def position_get(self, *, ticket: int) -> TradePosition
async def get_position_by_ticket(self, *, ticket: int) -> TradePosition
```
Get a position by ticket number.
#### Arguments
Get a position by ticket id.
#### Parameters:
| Name | Type | Description |
|----------|-------|-----------------|
| `ticket` | `int` | Position ticket |
#### Returns
#### Returns:
| Type | Description |
|-----------------|----------------|
| `TradePosition` | Trade position |
<a id="close"></a>
<a id="positions.get_positions_by_symbol"></a>
### get_positions_by_symbol
```python
async def get_positions_by_symbol(self, *, symbol: str) -> tuple[TradePosition, ...]
```
Filter positions by symbols
#### Parameters:
| Name | Type | Description |
|----------|-------|-------------|
| `symbol` | `str` | Symbol |
#### Returns:
| Type | Description |
|-----------------------------|----------------|
| `tuple[TradePosition, ...]` | Trade position |
<a id="positions.close"></a>
### close
```python
async def close(self, *, ticket: int, symbol: str, price: float, volume: float, order_type: OrderType):
async def close(self, *, ticket: int, symbol: str, price: float, volume: float, order_type: OrderType) -> OrderSendResult:
```
Close a position by ticket number.
#### Arguments
| Name | Type | Description | Default |
|--------------|-------------|----------------------------|---------|
| `ticket` | `int` | Position ticket. | |
| `symbol` | `str` | Financial instrument name. | |
| `price` | `float` | Closing price. | |
| `volume` | `float` | Volume to close. | |
| `order_type` | `OrderType` | Order type. | |
Close a position using its details.
<a id="close_by"></a>
### close_by
```python
async def close_by(self, pos: TradePosition):
```
#### Parameters:
| Name | Type | Description |
|--------------|-------------|----------------------------|
| `ticket` | `int` | Position ticket. |
| `symbol` | `str` | Financial instrument name. |
| `price` | `float` | Closing price. |
| `volume` | `float` | Volume to close. |
| `order_type` | `OrderType` | Order type. |
Close a position by position object.
#### Arguments
| Name | Type | Description |
|-------|-----------------|-----------------|
| `pos` | `TradePosition` | Position object |
#### Returns:
| Type | Description |
|--------------------|----------------------------------------------------|
| `OrderSendResult ` | The result of the order sent to close the position |
<a id='close_position'></a>
<a id="positions.close_position"></a>
### close_position
```python
async def close_position(self, *, position: TradePosition):
async def close_position(self, *, position: TradePosition) -> OrderSendResult:
```
Close a position by position object.
#### Arguments
#### Parameters:
| Name | Type | Description |
|------------|-----------------|-----------------|
| `position` | `TradePosition` | Position object |
<a id="close_all"></a>
#### Returns:
| Type | Description |
|-------------------|----------------------------------------------------|
| `OrderSendResult` | The result of the order sent to close the position |
<a id='positions.close_position_by_ticket'></a>
### close_position_by_ticket
```python
async def close_position_by_ticket(self, *, position: TradePosition) -> OrderSendResult:
```
Close a position by position object.
#### Parameters:
| Name | Type | Description |
|------------|-----------------|-----------------|
| `position` | `TradePosition` | Position object |
#### Returns:
| Type | Description |
|-------------------|----------------------------------------------------|
| `OrderSendResult` | The result of the order sent to close the position |
<a id="positions.close_all"></a>
### close_all
```python
async def close_all() -> int
```
Close all open positions for the trading account.
#### Returns
#### Returns:
| Type | Description |
|-------|--------------------------------------|
| `int` | Return total number of closed trades |
docs/lib/ram.md
+46 -43
View File
@@ -1,74 +1,77 @@
# Risk Assessment and Management
## Table of Contents
- [RAM](#RAM)
- [\_\_init\_\_](#__init__)
- [get\_amount](#get_amount)
- [check_losing_positions](#check_losing_positions)
- [check_risk_level](#check_balance_level)
- [RAM](#ram.ram)
- [\__init\__](#ram.__init__)
- [get_amount](#ram.get_amount)
- [check_losing_positions](#ram.check_losing_positions)
- [check_open_positions](#ram.check_open_positions)
<a id="RAM"></a>
<a id="ram.ram"></a>
### RAM
```python
class RAM
```
Risk Assessment and Management. You can customize this class based on how you want to manage risk.
#### Attributes
| Name | Type | Description | Default |
|------------------|---------|--------------------------------------------------------|---------|
| `risk_to_reward` | `float` | Risk to reward ratio | 1 |
| `risk` | `float` | Percentage of account balance to risk per trade | |
| `points` | `float` | A fixed number of points per trade can be fixed here | |
| `pips` | `float` | A fixed number of pips per trade can be fixed here | |
| `min_amount` | `float` | Minimum amount to risk per trade | |
| `max_amount` | `float` | Maximum amount to risk per trade | |
| `risk_level` | `float` | Ratio of free margin to current equity as a percentage | 50 |
| `loss_limit` | `int` | Number of open losing trades to allow at any time | 3 |
#### Attributes:
| Name | Type | Description | Default |
|------------------|-----------|---------------------------------------------------|-----------|
| `account` | `Account` | The account object | Account() |
| `risk_to_reward` | `float` | Risk to reward ratio | 2 |
| `risk` | `float` | Percentage of account balance to risk per trade | 1% |
| `fixed_amount` | `float` | A fixed amount to risk per trade | |
| `min_amount` | `float` | Minimum amount to risk per trade | |
| `max_amount` | `float` | Maximum amount to risk per trade | |
| `loss_limit` | `int` | Number of open losing trades to allow at any time | 3 |
| `open_limit` | `int` | Number of open trades to allow at any time | 3 |
<a id="__init__"></a>
<a id="ram.__init__"></a>
### \_\_init\_\_
```python
def __init__(self, *, risk_to_reward: float = 1, risk: float = 0.01, **kwargs):
def __init__(self, **kwargs):
```
Risk Assessment and Management. All provided keyword arguments are set as attributes.
#### Parameters
| Name | Type | Description | Default |
|------------------|---------|----------------------------------------------------|-----------|
| `risk_to_reward` | `float` | Risk to reward ratio | 1 |
| `risk` | `float` | Percentage of account balance to risk per trade | 0.01 # 1% |
| `kwargs` | `Dict` | Keyword arguments to be set as instance attributes | {} |
| Name | Type | Description | Default |
|------------------|--------|----------------------------------------------------|-----------|
| `kwargs` | `dict` | Keyword arguments to be set as instance attributes | {} |
<a id="get_amount"></a>
### get\_amount
<a id="ram.get_amount"></a>
### ram.get_amount
```python
async def get_amount() -> float
```
Calculate the amount to risk per trade as a percentage of balance.
#### Returns
| Type | Description |
|--------|-------------------------------------------------------|
| float | Amount to risk per trade in terms of account currency |
<a id="check_losing_positions"></a>
#### Returns:
| Type | Description |
|---------|-------------------------------------------------------|
| `float` | Amount to risk per trade in terms of account currency |
<a id="ram.check_losing_positions"></a>
### check_losing_positions
```python
async def check_losing_positions(self) -> bool:
```
Check if the number of open losing trades is greater than or equal to the loss limit.
#### Returns
| Type | Description |
|------|---------------------------------------------------------------------------------------|
| bool | True if the number of open losing trades is more than the loss limit, False otherwise |
<a id="check_balance_level"></a>
### check\_balance\_level
#### Returns:
| Type | Description |
|--------|---------------------------------------------------------------------------------------|
| `bool` | True if the number of open losing trades is more than the loss limit, False otherwise |
<a id="ram.check_open_positions"></a>
### check_open_positions
```python
async def check_balance_level(self) -> bool:
async def check_open_positions(self) -> bool:
```
Check if the balance level is greater than or equal to the fixed balance level.
#### Returns
| Type | Description |
|------|---------------------------------------------------------------------------------|
| bool | True if the balance level is more than the fixed balance level, False otherwise |
Check if the number of open positions is less than or equal the loss limit.
#### Returns:
| Type | Description |
|--------|---------------------------------------------------------------------------------------|
| `bool` | True if the number of open losing trades is more than the loss limit, False otherwise |
docs/lib/records.md
-96
View File
@@ -1,96 +0,0 @@
# Records
## Table of contents
- [Records](#records)
- [\_\_init\_\_](#__init__)
- [get\_records](#get_records)
- [read\_update](#read_update)
- [update\_rows](#update_rows)
- [update\_records](#update_records)
- [update\_record](#update_record)
<a id="records"></a>
### Records
```python
class Records()
```
This utility class read trade records from csv files, and update them based on their closing positions. To use this default
implementation the csv files should at least have the following columns `['order', 'symbol', 'actual_profit', 'win', 'closed']`
Once a trade have been closed, the actual profit and win status will be updated in the csv file.
#### Default Headers
| column | type | description |
|---------------|-------|-------------------------------------------------------|
| order | int | Order id of the trade |
| symbol | str | the name of the Symbol |
| actual_profit | float | The actual profit of the trade, this zero by default |
| win | bool | The win status of the trade, this is False by default |
| closed | bool | The status of the trade, this is False by default |
#### Attributes
| name | type | description |
|-------------|--------|--------------------------------------------------------------|
| records_dir | Path | Absolut path to directory containing record of placed trades |
| config | Config | Config object |
<a id="__init__"></a>
### \_\_init\_\_
```python
def __init__(records_dir: Path | str = '')
```
Initialize an instance of the class
#### Parameters
| name | type | description |
|--------------|------|----------------------------------------------------------------|
| records_dir | Path | Absolute path to directory containing record of placed trades. |
<a id="get_records"></a>
### get\_records
```python
async def get_records()
```
Get trade records from records_dir folder
#### Yields
| type | description |
|------|--------------------|
| Path | Trade record files |
<a id="read_update"></a>
### read\_update
```python
async def read_update(file: Path)
```
Read and update trade records
#### Parameters
| name | type | description |
|------|------|-------------------|
| file | Path | Trade record file |
<a id="update_rows"></a>
### update\_rows
```python
async def update_rows(rows: list[dict]) -> list[dict]
```
Update the rows of entered trades in the csv file with the actual profit.
#### Parameters
| name | type | description |
|------|------------|---------------------------------------------------------------------------|
| rows | list[dict] | A list of dictionaries from the dictionary writer object of the csv file. |
#### Returns
| type | description |
|------------|---------------------------------------------------------------|
| list[dict] | A list of dictionaries with the actual profit and win status. |
<a id="update_records"></a>
### update\_records
```python
async def update_records()
```
Update trade records in the records_dir folder.
<a id="update_record"></a>
### update\_record
```python
async def update_record(file: Path | str)
```
Update a single trade record file.
docs/lib/result.md
+40 -20
View File
@@ -1,18 +1,20 @@
# Result
## Table of Contents
- [Result](#result)
- [__init__](#__init__)
- [get_data](#get_data)
- [to_csv](#to_csv)
- [to_json](#to_json)
- [Result](#result.result)
- [__init__](#result.__init__)
- [save](#result.save)
- [get_data](#result.get_data)
- [to_csv](#result.to_csv)
- [to_json](#result.to_json)
<a id="result"></a>
<a id="result.result"></a>
```python
class Result()
class Result
```
A base class for handling trade results and strategy parameters for record keeping and analysis.
#### Attributes
#### Attributes:
| Name | Type | Description |
|--------------|-------------------|-----------------------------------|
| `result` | `OrderSendResult` | The result of the trade |
@@ -20,39 +22,57 @@ A base class for handling trade results and strategy parameters for record keepi
| `name` | `str` | The name of the result object |
<a id="__init__"></a>
### \_\_init\_\_
<a id="result.__init__"></a>
### \__init\__
```python
def __init__(result: OrderSendResult, parameters: dict = None, name: str = '')
def __init__(*, result: OrderSendResult, parameters: dict = None, name: str = '')
```
Prepare result data for record keeping and analysis.
#### Parameters
#### Parameters:
| Name | Type | Description |
|--------------|-------------------|-----------------------------------|
| `result` | `OrderSendResult` | The result of the trade |
| `parameters` | `dict` | The parameters used for the trade |
| `name` | `str` | The name of the result object |
<a id="get_data"></a>
### get\_data
<a id="result.get_data"></a>
### get_data
```python
def get_data(self) -> dict:
def get_data(self) -> dict
```
Get the result data as a dictionary
#### Returns
#### Returns:
| Type | Description |
|--------|-----------------|
| `dict` | The result data |
<a id="to_csv"></a>
### to\_csv
<a id="result.to_save"></a>
### to_save
```python
async def to_save(*, trade_record_mode: Literal["csv", "json"] = None)
```
Save to json or csv depending on the trade record mode.
#### Returns:
| Name | Type | Description | Default |
|---------------------|--------------------------|-----------------------|---------|
| `trade_record_mode` | `Literal["csv", "json"]` | The trade record mode | None |
<a id="result.to_csv"></a>
### to_csv
```python
async def to_csv()
```
Record trade results and associated parameters as a csv file
<a id="to_json"></a>
### to\_json
<a id="result.to_json"></a>
### to_json
```python
async def to_json()
```
docs/lib/sessions.md
+127 -45
View File
@@ -1,28 +1,38 @@
from aiomql import TradePositionfrom aiomql.lib.sessions import Duration
# Session and Sessions
Sessions allow you to run a strategy at specific times of the day.
## Table of Contents
- [Session](#session)
- [\_\_init\_\_](#session.__init__)
- [\__init\__](#session.__init__)
- [begin](#session.begin)
- [close](#session.close)
- [action](#session.action)
- [Sessions](#sessions)
- [\_\_init\_\_](#sessions.__init__)
- [in_session](#session.in_session)
- [duration](#session.duration)
- [close_positions](#session.close_positions)
- [close_all](#session.close_all)
- [close_win](#session.close_win)
- [close_loss](#session.close_loss)
- [close_until](#session.until)
- [Sessions](#sessions.sessions)
- [\__init\__](#sessions.__init__)
- [find](#sessions.find)
- [find_next](#sessions.find_next)
- [check](#sessions.check)
- [delta](#delta)
- [until](#until)
- [delta](#sessions_mod.delta)
- [backtest_sleep](#sessions_mod.backtest_sleep)
<a id="session"></a>
<a id="session.session"></a>
## Session
```python
class Session
```
A session is a time period between two `datetime.time` objects specified in utc.
#### Attributes
#### Attributes:
| Name | Type | Description | Default |
|----------------|-------------------------------------------------------------------|------------------------------------------------------------------------|---------|
| `start` | `datetime.time` | The start time of the session. | None |
@@ -39,7 +49,7 @@ opened during the session or not or even by a strategy using the session. This i
positions opened by the strategy. This will be handled in a future release.
<a id="session.__init__"></a>
### \_\_init\_\_
### \__init\__
```python
def __init__(*,
start: int | time,
@@ -51,8 +61,8 @@ def __init__(*,
custom_start: Callable = None,
custom_end: Callable = None)
```
Create a session.
#### Arguments
Create a session
#### Parameters:
| Name | Type | Description | Default |
|----------------|-------------------------------------------------------------------|---------------------------------------------------------------------|---------|
| `start` | `int` \| `datetime.time` | The start time of the session in UTC. | None |
@@ -63,6 +73,7 @@ Create a session.
| `custom_end` | `Callable` | A custom function to call when the session ends. Default is None. | None |
| `name` | `str` | The name of the session. Default is None. | None |
<a id="session.begin"></a>
### begin
```python
@@ -70,6 +81,7 @@ async def begin()
```
Call the action specified in on_start or custom_start.
<a id="session.close"></a>
### close
```python
@@ -77,72 +89,143 @@ async def close()
```
Call the action specified in on_end or custom_end.
<a id="session.in_session"></a>
### in_session
```python
def in_session() -> bool
```
Check if the current time is within the current session.
<a id="session.duration"></a>
### duration
```python
def duration() -> Duration
```
Get the duration of the session in hours, minutes, and seconds.
<a id="session.close_positions"></a>
### close_positions
```python
async def close_positions(*, positions: tuple[TradePosition, ...])
```
Close positions in the sessions. This is used by the `close_all` action.
#### Parameters:
| Name | Type | Description |
|-------------|-----------------------------|---------------------------------------|
| `positions` | `tuple[TradePosition, ...]` | A tuple of TradePosition objects. |
<a id="session.close_all"></a>
### close_all
```python
async def close_all()
```
Close all open positions
<a id="session.close_win"></a>
### close_win
```python
async def close_win()
```
Close only winning positions
<a id="session.close_loss"></a>
### close_loss
```python
async def close_loss()
```
Close only losing positions
<a id="session.action"></a>
### action
```python
async def action(action): pass
async def action(*, action: Literal["close_all", "close_win", "close_loss", "custom_start", "custom_end"]): pass
```
Used by begin and close to call the action specified.
#### Arguments
| Name | Type | Description | Default |
|----------|---------------------------------------------------------------------------------|---------------------|---------|
| `action` | `Literal['close_all', 'close_win', 'close_loss', 'custom_start', 'custom_end']` | The action to take. | None |
#### Parameters:
| Name | Type | Description |
|----------|---------------------------------------------------------------------------------|---------------------|
| `action` | `Literal['close_all', 'close_win', 'close_loss', 'custom_start', 'custom_end']` | The action to take. |
<a id="sessions"></a>
<a id="session.until"></a>
### until
```python
def until() -> int
```
Get the seconds until the session starts from the current time.
<a id="sessions.sessions"></a>
## Sessions
```python
class Sessions()
```
Sessions allow you to run code at specific times of the day. It is a collection of Session objects.
Sessions are sorted by start time. The sessions object is an asynchronous context manager.
### Attributes:
| Name | Type | Description | Default |
|-------------------|-----------------|----------------------------|---------|
| `sessions` | `list[Session]` | A list of Session objects. | [] |
| `current_session` | `Session` | The current session. | None |
<a id="sessions.__init__"></a>
#### \_\_init\_\_
#### \__init\__
```python
def __init__(*sessions)
def __init__(*sessions: Iterable[Session])
```
Create a Sessions object.
#### Arguments
| Name | Type | Description | Default |
|------------|------------------|-----------------------------|---------|
| `sessions` | `tuple[Session]` | A tuple of Session objects. | None |
#### Parameters:
| Name | Type | Description |
|------------|---------------------|--------------------------------|
| `sessions` | `Iterable[Session]` | A iterable of Session objects. |
<a id="sessions.find"></a>
### find
```python
def find(obj: time) -> Session | None
def find(*, moment: time = None) -> Session | None
```
Find a session that contains a datetime.time object.
#### Arguments
| Name | Type | Description | Default |
|-------|-----------------|-------------------------|---------|
| `obj` | `datetime.time` | A datetime.time object. | None |
#### Returns
#### Parameters:
| Name | Type | Description | Default |
|----------|--------|-------------------------|---------|
| `moment` | `time` | A datetime.time object. | None |
#### Returns:
| Type | Description |
|-----------|----------------------------------------|
| `Session` | A Session object or None if not found. |
<a id="sessions.find_next"></a>
### find\_next
### find_next
```python
def find_next(obj: time) -> Session
def find_next(*, moment: time = None) -> Session
```
Find the next session that contains a datetime.time object.
#### Arguments
| Name | Type | Description | Default |
|-------|-----------------|-------------------------|---------|
| `obj` | `datetime.time` | A datetime.time object. | |
#### Returns
#### Parameters:
| Name | Type | Description | Default |
|----------|--------|-------------------------|---------|
| `moment` | `time` | A datetime.time object. | |
#### Returns:
| Type | Description |
|-----------|-------------------|
| `Session` | A Session object. |
<a id="sessions.check"></a>
### check
```python
@@ -150,13 +233,15 @@ async def check(): pass
```
Check if the current session has started and if not, wait until it starts.
<a id="delta"></a>
<a id="sessions_mod.delta"></a>
### delta
```python
def delta(obj: time) -> timedelta: pass
```
Get the timedelta of a datetime.time object.
#### Arguments:
#### Parameters:
| Name | Type | Description | Default |
|-------|-----------------|-------------------------|---------|
| `obj` | `datetime.time` | A datetime.time object. | None |
@@ -165,13 +250,10 @@ Get the timedelta of a datetime.time object.
|-------------|---------------------|
| `timedelta` | A timedelta object. |
<a id="until"></a>
### until
<a id="sessions_mod.backtest_sleep"></a>
### backtest_sleep
```python
def until()
async def backtest_sleep(secs)
```
Get the seconds until the session starts from the current time.
#### Returns:
| Type | Description |
|-------|---------------------------------------|
| `int` | The seconds until the session starts. |
Sleep method for backtesting.
docs/lib/strategy.md
+89 -26
View File
@@ -2,46 +2,56 @@
The base class for creating strategies.
## Table of Contents
- [Strategy](#strategy)
- [\_\_init\_\_](#init)
- [sleep](#sleep)
- [trade](#trade)
- [Strategy](#strategy.strategy)
- [\_\_init\_\_](#strategy.__init__)
- [sleep](#strategy.sleep)
- [live_sleep](#strategy.live_sleep)
- [backtest_sleep](#strategy.backtest_sleep)
- [run_strategy](#strategy.run_strategy)
- [live_strategy](#strategy.live_strategy)
- [backtest_strategy](#strategy.backtest_strategy)
- [trade](#strategy.trade)
- [test](#strategy.test)
<a id="strategy"></a>
<a id="strategy.strategy"></a>
### Strategy
```python
class Strategy(ABC)
```
The base class for creating strategies.
#### Attributes
| Name | Type | Description | Default |
|--------------|--------------|----------------------------------------------|---------|
| `name` | `str` | A name for the strategy. | None |
| `account` | `Account` | Account instance. | None |
| `mt5` | `MetaTrader` | MetaTrader instance. | None |
| `config` | `Config` | Config instance. | None |
| `symbol` | `Symbol` | The Financial Instrument as a Symbol Object | None |
| `parameters` | `Dict` | A dictionary of parameters for the strategy. | None |
| `sessions` | `Sessions` | Trading sessions. | None |
### Notes
Define the name of a strategy as a class attribute. If not provided, the class name will be used as the name.
#### Attributes:
| Name | Type | Description | Default |
|-----------------------|--------------------------------|------------------------------------------------|---------|
| `name` | `str` | A name for the strategy. | None |
| `symbol` | `Symbol` | The Financial Instrument as a Symbol Object | None |
| `sessions` | `Sessions` | Trading sessions. | None |
| `mt5` | `MetaTrader \| MetaBackTester` | MetaTrader instance. | None |
| `config` | `Config` | Config instance. | None |
| `parameters` | `dict` | A dictionary of parameters for the strategy. | None |
| `backtest_controller` | `BackTesterController` | A controller for the backtester. |
| `current_session` | `Session` | The current trading session |
| `running` | `bool` | A flag to indicate if the strategy is running. | True |
<a id="init"></a>
<a id="strategy.__init__"></a>
### \_\_init\_\_
```python
def __init__(*, symbol: Symbol, params: dict = None, sessions: Sessions)
def __init__(*, symbol: Symbol, params: dict = None, sessions: Sessions, name: str = "")
```
Initiate the parameters dict and add name and symbol fields. Use class name as strategy name if name is not provided.
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|------------|------------|-----------------------------|---------|
| `symbol` | `Symbol` | The Financial instrument | None |
| `symbol` | `Symbol` | The Financial instrument | |
| `params` | `Dict` | Trading strategy parameters | None |
| `sessions` | `Sessions` | Trading sessions | None |
| `name` | `str` | The name of the strategy | "" |
<a id="sleep"></a>
<a id="strategy.sleep"></a>
### sleep
```python
@staticmethod
@@ -50,16 +60,69 @@ async def sleep(secs: float)
Sleep for the needed amount of seconds in between requests to the terminal.
computes the accurate amount of time needed to sleep ensuring that the next request is made at the start of
a new bar and making cooperative multitasking possible.
#### Parameters
This method calls the `live_sleep` method during live trading or `backtest_sleep`.
#### Parameters:
| Name | Type | Description | Default |
|--------|---------|----------------------------------------------------------------|---------|
| `secs` | `float` | The time in seconds. Usually the timeframe you are trading on. | None |
<a id="trade"></a>
<a id="strategy.live_sleep"></a>
### live_sleep
```python
async def live_sleep(*, secs: float)
```
Sleep method for live trading
<a id="strategy.backtest_sleep"></a>
### backtest_sleep
```python
async def backtest_sleep(*, secs: float)
```
Sleep method for backtesting
<a id="strategy.trade"></a>
### trade
```python
@abstractmethod
async def trade()
```
Place trades using this method. This is the main method of the strategy.
It will be called by the strategy runner.
Place trades using this method.
Implement this method in your own strategy as you wish.
<a id="strategy.test"></a>
### test
```python
@abstractmethod
async def test()
```
Use for backtesting. If not implemented use the trade method.
<a id="strategy.run_strategy"></a>
### run_strategy
```python
async def run_strategy()
```
Run the strategy by calling the trade or test method repeatedly in a while loop.
This method actually calls the `live_strategy` or `backtest_strategy` depending on the mode.
<a id="strategy.live_strategy"></a>
### live_strategy
```python
async def live_strategy()
```
Runs the strategy in live mode.
<a id="strategy.backtest_strategy"></a>
### backtest_strategy
```python
async def live_strategy()
```
Runs the strategy in backtest mode.
docs/lib/symbol.md
+179 -165
View File
@@ -2,336 +2,350 @@
Symbol class for handling a financial instrument.
## Table of Contents
- [Symbol](#Symbol)
- [info_tick](#info_tick)
- [symbol_select](#symbol_select)
- [info](#info)
- [init](#init)
- [book_add](#book_add)
- [book_get](#book_get)
- [book_release](#book_release)
- [compute_volume](#compute_volume)
- [currency_conversion](#currency_conversion)
- [convert_currency](#convert_currency)
- [copy_rates_from](#copy_rates_from)
- [copy_rates_from_pos](#copy_rates_from_pos)
- [copy_rates_range](#copy_rates_range)
- [copy_ticks_from](#copy_ticks_from)
- [copy_ticks_range](#copy_ticks_range)
- [check_volume](#check_volume)
- [round_off_volume](#round_off_volume)
- [Symbol](#symbol.symbol)
- [info_tick](#symbol.info_tick)
- [symbol_select](#symbol.symbol_select)
- [info](#symbol.info)
- [initialize](#symbol.initialize)
- [book_add](#symbol.book_add)
- [book_get](#symbol.book_get)
- [book_release](#symbol.book_release)
- [compute_volume](#symbol.compute_volume)
- [convert_currency](#symbol.convert_currency)
- [copy_rates_from](#symbol.copy_rates_from)
- [copy_rates_from_pos](#symbol.copy_rates_from_pos)
- [copy_rates_range](#symbol.copy_rates_range)
- [copy_ticks_from](#symbol.copy_ticks_from)
- [copy_ticks_range](#symbol.copy_ticks_range)
- [check_volume](#symbol.check_volume)
- [round_off_volume](#symbol.round_off_volume)
<a id="Symbol"></a>
<a id="symbol.symbol"></a>
### Symbol
```python
class Symbol(SymbolInfo)
class Symbol(_Base, SymbolInfo)
```
Main class for handling a financial instrument. A subclass of `SymbolInfo` where most of the attributes are defined.
for working with a financial instrument.
#### Attributes
#### Attributes:
| Name | Type | Description | Default |
|-----------|--------------|---------------------------------------|---------|
| `name` | `str` | The name of the symbol. | None |
| `mt5` | `MetaTrader` | MetaTrader instance. | None |
| `config` | `Config` | Config instance. | None |
| `account` | `Account` | Account instance. | None |
| `tick` | `Tick` | The current price tick of the symbol. | None |
#### Notes
Full properties are on the SymbolInfo Object.
Make sure Symbol is always initialized with a name argument
#### Notes:
Make sure Symbol is always initialized with a name argument.
<a id="info_tick"></a>
### info\_tick
<a id="symbol.info_tick"></a>
### info_tick
```python
async def info_tick(*, name: str = "") -> Tick
```
Get the current price tick of a financial instrument.
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|--------|-------|-------------------------|---------|
| `name` | `str` | The name of the symbol. | '' |
#### Returns
#### Returns:
| Type | Description |
|--------|----------------------|
| `Tick` | Return a Tick Object |
#### Raises
| Exception | Description |
|--------------|---------------------------------------------------|
| `ValueError` | If request was unsuccessful and None was returned |
<a id="symbol_select"></a>
### symbol\_select
<a id="symbol.symbol_select"></a>
### symbol_select
```python
async def symbol_select(*, enable: bool = True) -> bool
```
Select a symbol in the MarketWatch window or remove a symbol from the window.
Update the select property
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|----------|--------|---------------------------------------------------------------------------------------------------------|---------|
| `enable` | `bool` | Switch. Optional unnamed parameter. If 'false', a symbol should be removed from the MarketWatch window. | None |
#### Returns
#### Returns:
| Type | Description |
|--------|--------------------------------------|
| `bool` | True if successful, otherwise False. |
<a id="info"></a>
<a id="symbol.info"></a>
### info
```python
async def info() -> SymbolInfo
```
Get data on the specified financial instrument and update the symbol object properties
#### Returns
#### Returns:
| Type | Description |
|--------------|--------------------------|
| `SymbolInfo` | SymbolInfo if successful |
#### Raises
#### Raises:
| Exception | Description |
|--------------|---------------------------------------------------|
| `ValueError` | If request was unsuccessful and None was returned |
<a id="init"></a>
<a id="symbol.initialize"></a>
### init
```python
async def init() -> bool
async def initialize() -> bool
```
Initialized the symbol by pulling properties from the terminal
#### Returns
#### Returns:
| Type | Description |
|--------|--------------------------------------------------------|
| `bool` | Returns True if symbol info was successful initialized |
<a id="book_add"></a>
### book\_add
<a id="symbol.book_add"></a>
### book_add
```python
async def book_add() -> bool
```
Subscribes the MetaTrader 5 terminal to the Market Depth change events for a specified symbol.
If the symbol is not in the list of instruments for the market, This method will return False
#### Returns
If the symbol is not in the list of instruments for the market, This method will return False.
#### Returns:
| Type | Description |
|--------|--------------------------------------|
| `bool` | True if successful, otherwise False. |
<a id="book_get"></a>
### book\_get
<a id="symbol.book_get"></a>
### book_get
```python
async def book_get() -> tuple[BookInfo]
async def book_get() -> tuple[BookInfo, ...]
```
Returns a tuple of BookInfo featuring Market Depth entries for the specified symbol.
#### Returns
| Type | Description |
|-------------------|-------------------------------------------------------------------|
| `tuple[BookInfo]` | Returns the Market Depth contents as a tuples of BookInfo Objects |
#### Raises
| Exception | Description |
|--------------|---------------------------------------------------|
| `ValueError` | If request was unsuccessful and None was returned |
#### Returns:
| Type | Description |
|------------------------|-------------------------------------------------------------------|
| `tuple[BookInfo, ...]` | Returns the Market Depth contents as a tuples of BookInfo Objects |
<a id="book_release"></a>
### book\_release
<a id="symbol.book_release"></a>
### book_release
```python
async def book_release() -> bool
```
Cancels subscription of the MetaTrader 5 terminal to the Market Depth change events for a specified symbol.
#### Returns
#### Returns:
| Type | Description |
|--------|--------------------------------------|
| `bool` | True if successful, otherwise False. |
<a id="compute_volume"></a>
<a id="symbol.compute_volume"></a>
### compute_volume
```python
async def compute_volume(*args, **kwargs) -> float
async def compute_volume(self) -> float
```
Computes the volume of a trade based on the amount or any other parameter.
This is a dummy method that returns the minimum volume of the symbol. It is meant to be overridden by a subclass.
This default implementation returns the minimum volume of the symbol. It is meant to be overridden by a subclass.
#### Parameters
| Name | Type | Description | Default |
|--------------|---------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------|
| `amount` | `float` | Amount to risk in the trade | None |
| `points` | `float` | Number of pips to target | None |
| `use_limits` | `bool` | If True, the minimum volume is returned if the computed volume is less than the minimum volume and the maximum volume is returned if the computed volume is greater than the maximum volume for the symbol | False |
#### Returns
| Type | Description |
|---------|---------------------------------|
| `float` | Returns the volume of the trade |
<a id="currency_conversion"></a>
### currency\_conversion
<a id="symbol.check_volume"></a>
### check_volume
```python
async def currency_conversion(*, amount: float, base: str,
quote: str) -> float
async def check_volume(*, volume: float) -> tuple[bool, float]
```
Convert from one currency to the other. Returns the amount in terms of the base currency.
#### Parameters
| Name | Type | Description | Default |
|----------|---------|--------------------------------------------------------|---------|
| `amount` | `float` | Amount to convert given in terms of the quote currency | None |
| `base` | `str` | The base currency of the pair | None |
| `quote` | `str` | The quote currency of the pair | None |
#### Returns
Check if the volume is within the limits of permitted volume for
the symbol. If not, return the nearest limit.
#### Returns:
| Type | Description |
|----------------------|-------------------------------------------------------------------------------|
| `tuple[bool, float]` | True and the input volume if within bounds, else False and the nearest limit. |
<a id="symbol.round_off_volume"></a>
### round_off_volume
```python
async def round_off_volume(*, volume: float, round_down: bool = False) -> float
```
Round off the volume to the nearest volume step.
#### Parameters:
| Name | Type | Description | Default |
|--------------|---------|---------------------------------------------------|---------|
| `volume` | `float` | The volume | |
| `round_down` | `float` | Round up or round down to the nearest volume step | False |
#### Returns:
| Type | Description |
|---------|---------------------------------|
| `float` | Returns the volume of the trade |
<a id="symbol.amount_in_quote_currency"></a>
### amount_in_quote_currency
```python
async def amount_quote_currency(*, amount: float) -> float
```
Convert an amount in the account_currency to the quote currency of the symbol.
#### Parameters:
| Name | Type | Description |
|----------|---------|-----------------------|
| `amount` | `float` | The amount to convert |
<a id="symbol.convert_currency"></a>
### convert_currency
```python
async def convert_currency(*, amount: float, from_currency: str, to_currency: str) -> float
```
Convert from one currency to the other.
#### Parameters:
| Name | Type | Description |
|-----------------|---------|--------------------------------------------------------|
| `amount` | `float` | Amount to convert given in terms of the quote currency |
| `from_currency` | `str` | The currency to convert from |
| `to_currency` | `str` | The currency to convert to |
#### Returns:
| Type | Description |
|---------|--------------------------------------|
| `float` | Amount in terms of the base currency |
#### Raises
| Exception | Description |
|--------------|----------------------|
| `ValueError` | If conversion failed |
<a id="convert_currency"></a>
```python
async def convert_currency(self, *, amount: float, base: str, quote: str) -> float:
```
Alias for currency_conversion
<a id="copy_rates_from"></a>
### copy\_rates\_from
<a id="symbol.copy_rates_from"></a>
### copy_rates_from
```python
async def copy_rates_from(*,
timeframe: TimeFrame,
date_from: datetime | int,
count: int = 500) -> Candles
async def copy_rates_from(*, timeframe: TimeFrame, date_from: datetime | int, count: int = 500) -> Candles
```
Get bars from the MetaTrader 5 terminal starting from the specified date.
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|-------------|-----------------|----------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|
| `timeframe` | `TimeFrame` | Timeframe the bars are requested for. Set by a value from the TimeFrame enumeration. | Required unnamed parameter |
| `date_from` | `datetime, int` | Date of opening of the first bar from the requested sample. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. | Required unnamed parameter |
| `count` | `int` | Number of bars to receive. | Required unnamed parameter |
#### Returns
#### Returns:
| Type | Description |
|-----------|---------------------------------------------------------------------------|
| `Candles` | Returns a Candles object as a collection of rates ordered chronologically |
#### Raises
#### Raises:
| Exception | Description |
|--------------|---------------------------------------------------|
| `ValueError` | If request was unsuccessful and None was returned |
<a id="copy_rates_from_pos"></a>
### copy\_rates\_from\_pos
<a id="symbol.copy_rates_from_pos"></a>
### copy_rates_from_pos
```python
async def copy_rates_from_pos(*,
timeframe: TimeFrame,
count: int = 500,
start_position: int = 0) -> Candles
async def copy_rates_from_pos(*,timeframe: TimeFrame, count: int = 500, start_position: int = 0) -> Candles
```
Get bars from the MetaTrader 5 terminal starting from the specified index.
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|------------------|-------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------|
| `timeframe` | `TimeFrame` | TimeFrame value from TimeFrame Enum. Required keyword only parameter | Required keyword only parameter |
| `count` | `int` | Number of bars to return. Keyword argument defaults to 500 | 500 |
| `start_position` | `int` | Initial index of the bar the data are requested from. The numbering of bars goes from present to past. Thus, the zero bar means the current one. Keyword argument defaults to 0. | 0 |
#### Returns
#### Returns:
| Type | Description |
|-----------|----------------------------------------------------------------------------|
| `Candles` | Returns a Candles object as a collection of rates ordered chronologically. |
#### Raises
#### Raises:
| Exception | Description |
|--------------|---------------------------------------------------|
| `ValueError` | If request was unsuccessful and None was returned |
<a id="copy_rates_range"></a>
### copy\_rates\_range
<a id="symbol.copy_rates_range"></a>
### copy_rates_range
```python
async def copy_rates_range(*, timeframe: TimeFrame, date_from: datetime | int,
date_to: datetime | int) -> Candles
```
Get bars in the specified date range from the MetaTrader 5 terminal.
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|-------------|---------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------|
| `timeframe` | `TimeFrame` | Timeframe for the bars using the TimeFrame enumeration. Required unnamed parameter. | Required unnamed parameter |
| date_from | datetime, int | Date the bars are requested from. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. Bars with the open time >= date_from are returned. Required unnamed parameter. | Required unnamed parameter |
| date_to | datetime, int | Date, up to which the bars are requested. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. Bars with the open time <= date_to are returned. Required unnamed parameter. | Required unnamed parameter |
#### Returns
#### Returns:
| Type | Description |
|-----------|----------------------------------------------------------------------------|
| `Candles` | Returns a Candles object as a collection of rates ordered chronologically. |
#### Raises
#### Raises:
| Exception | Description |
|--------------|---------------------------------------------------|
| `ValueError` | If request was unsuccessful and None was returned |
<a id="copy_ticks_from"></a>
### copy\_ticks\_from
<a id="symbol.copy_ticks_from"></a>
### copy_ticks_from
```python
async def copy_ticks_from(*,
date_from: datetime | int,
count: int = 100,
flags: CopyTicks = CopyTicks.ALL) -> Ticks
async def copy_ticks_from(*, date_from: datetime | int, count: int = 100, flags: CopyTicks = CopyTicks.ALL) -> Ticks
```
Get ticks from the MetaTrader 5 terminal starting from the specified date.
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|-------------|-----------------|---------------------------------------------------------------------------------------------------------------------|----------------------------|
| `date_from` | `datetime, int` | Date the ticks are requested from. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. | Required unnamed parameter |
| `count` | `int` | Number of requested ticks. Defaults to 100 | Required unnamed parameter |
| `flags` | `CopyTicks` | A flag to define the type of the requested ticks from CopyTicks enum. INFO is the default | Required unnamed parameter |
#### Returns
#### Returns:
| Type | Description |
|---------|--------------------------------------------------------------------------|
| `Ticks` | Returns a Ticks object as a collection of ticks ordered chronologically. |
#### Raises
#### Raises:
| Exception | Description |
|--------------|---------------------------------------------------|
| `ValueError` | If request was unsuccessful and None was returned |
<a id="copy_ticks_range"></a>
### copy\_ticks\_range
<a id="symbol.copy_ticks_range"></a>
### copy_ticks_range
```python
async def copy_ticks_range(*,
date_from: datetime | int,
date_to: datetime | int,
flags: CopyTicks = CopyTicks.ALL) -> Ticks
async def copy_ticks_range(*, date_from: datetime | int, date_to: datetime | int, flags: CopyTicks = CopyTicks.ALL) -> Ticks
```
Get ticks for the specified date range from the MetaTrader 5 terminal.
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|-------------|-----------------|-----------------------------------------------------------------------------------------------------------------------------|----------------------------|
| `date_from` | `datetime, int` | Date the ticks are requested from. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. | Required unnamed parameter |
| `date_to` | `datetime, int` | Date, up to which the ticks are requested. Set by the 'datetime' object or as a number of seconds elapsed since 1970.01.01. | Required unnamed parameter |
| `flags` | `CopyTicks` | A flag to define the type of the requested ticks from CopyTicks enum. INFO is the default | Required unnamed parameter |
#### Returns
#### Returns:
| Type | Description |
|---------|--------------------------------------------------------------------------|
| `Ticks` | Returns a Ticks object as a collection of ticks ordered chronologically. |
#### Raises
#### Raises:
| Exception | Description |
|--------------|---------------------------------------------------|
| `ValueError` | If request was unsuccessful and None was returned |
<a id="check_volume"></a>
### check_volume
```python
async def check_volume(*, volume: float) -> tuple[bool, float]
```
Checks if the volume is within the minimum and maximum volume for the symbol. If not, return the nearest limit.
#### Parameters
| Name | Type | Description | Default |
|--------|---------|---------------------|---------|
| volume | `float` | The volume to check | None |
#### Returns
| Type | Description |
|----------------------|-----------------------------------------------------|
| `tuple[bool, float]` | The boolean is True if the volume is within limits. |
<a id="round_off_volume"></a>
### round_off_volume
```python
async def round_off_volume(*, volume: float, round_down: bool = True) -> float
```
Rounds off the volume to the nearest minimum or maximum volume for the symbol.
#### Parameters
| Name | Type | Description | Default |
|--------------|---------|---------------------------|---------|
| `volume` | `float` | The volume to round off | None |
| `round_down` | `bool` | To round_up or round_down | True |
#### Returns
| Type | Description |
|---------|---------------------|
| `float` | The rounded volume. |
docs/lib/terminal.md
+30 -23
View File
@@ -1,27 +1,27 @@
# Terminal
## Table of Contents
- [Terminal](#terminal)
- [initialize](#initialize)
- [version](#version)
- [info](#info)
- [symbols_total](#symbols_total)
- [Terminal](#terminal.terminal)
- [initialize](#terminal.initialize)
- [version](#terminal.version)
- [info](#terminal.info)
- [symbols_total](#terminal.symbols_total)
<a id="terminal"></a>
<a id="terminal.terminal"></a>
### Terminal
```python
class Terminal(TerminalInfo)
class Terminal(_Base, TerminalInfo)
```
Terminal Class. Get information about the MetaTrader 5 terminal. The class is a subclass of the TerminalInfo
class. It inherits all the attributes and methods of the TerminalInfo class and adds some useful methods.
#### Attributes
| Name | Type | Description | Default |
|---------------|--------------|------------------------------------------------------------------------------|---------|
| `initialized` | `bool` | check if initial request has been sent to the terminal to get terminal info. | False |
| `mt5` | `MetaTrader` | MetaTrader instance | None |
| `config` | `Config` | Config instance | None |
<a id="initialize"></a>
#### Attributes:
| Name | Type | Description | Default |
|-----------|--------------|-------------------------------|---------|
| `version` | `Version` | MetaTrader5 Terminal Version. | None |
<a id="terminal.initialize"></a>
### initialize
```python
async def initialize() -> bool
@@ -30,28 +30,33 @@ Establish a connection with the MetaTrader 5 terminal. There are three call opti
The terminal for connection is found automatically. Call specifying the path to the MetaTrader 5 terminal we
want to connect to. word path as a keyword argument Call specifying the trading account path and parameters
i.e. login, password, server, as keyword arguments, path can be omitted.
#### Returns
#### Returns:
| Type | Description |
|--------|-------------------------------|
| `bool` | True if successful else False |
<a id="version"></a>
<a id="terminal.version"></a>
### version
```python
async def version()
```
Get the MetaTrader 5 terminal version. This method returns the terminal version, build and release date as
a tuple of three values
#### Returns
#### Returns:
| Type | Description |
|-----------|------------------------------------|
| `Version` | version of tuple as Version object |
#### Raises
#### Raises:
| Exception | Description |
|--------------|--------------------------------------------|
| `ValueError` | If the terminal version cannot be obtained |
<a id="info"></a>
<a id="terminal.info"></a>
### info
```python
async def info()
@@ -59,19 +64,21 @@ async def info()
Get the connected MetaTrader 5 client terminal status and settings. gets terminal info in the form of a
named tuple structure (namedtuple). Return None in case of an error. The info on the error can be
obtained using last_error().
#### Returns
#### Returns:
| Type | Description |
|----------------|----------------------------------------------------|
| `TerminalInfo` | Terminal status and settings as a terminal object. |
<a id="symbols_total"></a>
### symbols\_total
<a id="terminal.symbols_total"></a>
### symbols_total
```python
async def symbols_total() -> int
```
Get the number of all financial instruments in the MetaTrader 5 terminal.
#### Returns
#### Returns:
| Type | Description |
|-------|-----------------------------------|
| `int` | Total number of available symbols |
docs/lib/ticks.md
+56 -22
View File
@@ -2,23 +2,25 @@
Module for working with price ticks.
## Table of Contents
- [Tick](#tick)
- [Tick](#tick.tick)
- [\_\_init\_\_](#tick.__init__)
- [set\_attributes](#tick.set_attributes)
- [Ticks](#ticks)
- [\_\_init\_\_](#ticks.__init__)
- [set_attributes](#tick.set_attributes)
- [Ticks](#ticks.ticks)
- [\__init\__](#ticks.__init__)
- [ta](#ticks.ta)
- [ta\_lib](#ticks.ta_lib)
- [ta_lib](#ticks.ta_lib)
- [data](#ticks.data)
- [rename](#ticks.rename)
<a id='tick'></a>
<a id='tick.tick'></a>
## Tick
```python
class Tick()
```
Price Tick of a Financial Instrument.
#### Attributes
#### Attributes:
| Name | Type | Description | Default |
|---------------|------------|-----------------------------------------------------------------------|---------|
| `symbol` | `Symbol` | The Financial Instrument as a Symbol Object | None |
@@ -32,35 +34,62 @@ Price Tick of a Financial Instrument.
| `volume_real` | `float` | Volume for the current Last price | None |
| `Index` | `int` | Custom attribute representing the position of the tick in a sequence. | None |
<a id="tick.__init__"></a>
### \_\_init\_\_
### \__init\__
```python
def __init__(self, **kwargs):
```
Initialize the Tick class. Set attributes from keyword arguments.The `bid`, `ask`, `last`, `time` and `volume` must be present
<a id="tick.set_attributes"></a>
### set\_attributes
### set_attributes
```python
def set_attributes(**kwargs)
```
Set attributes from keyword arguments
<a id="ticks"></a>
<a id="tick.dict"></a>
### dict
```python
def dict(exclude: set = None, include: set = None) -> dict
```
Return a dictionary of the tick attributes.
#### Parameters:
| Name | Type | Description | Default |
|-----------|-------|-----------------------------------------------------|---------|
| `exclude` | `set` | A set of attributes to exclude from the dictionary. | None |
| `include` | `set` | A set of attributes to include in the dictionary. | None |
<a id="ticks.ticks"></a>
## Ticks
```python
class Ticks()
class Ticks
```
Container data class for price ticks. Arrange in chronological order. Saves data with a pandas DataFrame.
Supports iteration, slicing and assignment. Similar to `Candles` class but for price ticks.
#### Attributes:
| Name | Type | Description | Default |
|---------------|-------------|----------------------------------------------------------------------|---------|
| `data` | `DataFrame` | DataFrame of price ticks arranged in chronological order. | None |
| `time` | `Series` | Time of the last prices update for the symbol | None |
| `bid` | `Series` | Current Bid price | None |
| `ask` | `Series` | Current Ask price | None |
| `last` | `Series` | Price of the last deal (Last) | None |
| `volume` | `Series` | Volume for the current Last price | None |
| `time_msc` | `Series` | Time of the last prices update for the symbol in milliseconds | None |
| `flags` | `Series` | Tick flags | None |
| `volume_real` | `Series` | Volume for the current Last price | None |
| `Index` | `Series` | Custom attribute representing the position of the tick in a sequence | None |
#### Attributes
| Name | Type | Description | Default |
|--------|-------------|-----------------------------------------------------------|---------|
| `data` | `DataFrame` | DataFrame of price ticks arranged in chronological order. | None |
<a id="ticks.__init__"></a>
### \_\_init\_\_
### \__init\__
```python
def __init__(*, data: DataFrame | Iterable, flip=False)
```
@@ -71,6 +100,7 @@ Initialize the Ticks class. Creates a DataFrame of price ticks from the data arg
| `data` | `DataFrame` \| `Iterable` | Dataframe of price ticks or any iterable object that can be converted to a pandas DataFrame | None |
| `flip` | `bool` | If flip is True reverse data chronological order. | False |
<a id="ticks.ta"></a>
### ta
```python
@@ -78,23 +108,25 @@ Initialize the Ticks class. Creates a DataFrame of price ticks from the data arg
def ta()
```
Access to the pandas_ta library for performing technical analysis on the underlying data attribute.
#### Returns
#### Returns:
| Name | Type | Description |
|-------------|-------------|-----------------------|
| `pandas_ta` | `pandas_ta` | The pandas_ta library |
<a id="ticks.ta_lib"></a>
### ta\_lib
### ta_lib
```python
@property
def ta_lib()
```
Access to the ta library for performing technical analysis. Not dependent on the underlying data attribute.
#### Returns
#### Returns:
| Name | Type | Description |
|------|------|----------------|
| `ta` | `ta` | The ta library |
<a id="ticks.data"></a>
### data
```python
@@ -102,23 +134,25 @@ Access to the ta library for performing technical analysis. Not dependent on the
def data() -> DataFrame
```
DataFrame of price ticks arranged in chronological order.
#### Returns
#### Returns:
| Name | Type | Description |
|--------|-------------|-----------------------------------------------------------|
| `data` | `DataFrame` | DataFrame of price ticks arranged in chronological order. |
<a id="ticks.rename"></a>
### rename
```python
def rename(inplace=True, **kwargs) -> _Ticks | None
```
Rename columns of the candle class.
#### Arguments
#### Arguments:
| Name | Type | Description | Default |
|-----------|--------|-------------------------------------------------------------------------------------------|---------|
| `inplace` | `bool` | Rename the columns inplace or return a new instance of the class with the renamed columns | True |
| `kwargs` | | The new names of the columns | |
#### Returns
#### Returns:
| Type | Description |
|---------|---------------------------------------------------------------------------|
| `Ticks` | A new instance of the class with the renamed columns if inplace is False. |
docs/lib/trade_records.md
+113 -69
View File
@@ -2,126 +2,170 @@
## Table of contents
- [Trade Records](#trade_records)
- [\_\_init\_\_](#__init__)
- [get_csv_records](#get_csv_records)
- [get_json_records](#get_json_records)
- [read_update_csv](#read_update_csv)
- [read_update_json](#read_update_json)
- [update_rows](#update_rows)
- [update_row](#update_row)
- [update_csv_records](#update_csv_records)
- [update_json_records](#update_json_records)
- [update_csv_record](#update_csv_record)
- [update_json_record](#update_json_record)
- [\_\_init\_\_](#trade_records.__init__)
- [get_csv_records](#trade_records.get_csv_records)
- [get_json_records](#trade_records.get_json_records)
- [read_update_csv](#trade_records.read_update_csv)
- [read_update_json](#trade_records.read_update_json)
- [update_rows](#trade_records.update_rows)
- [update_row](#trade_records.update_row)
- [update_csv_records](#trade_records.update_csv_records)
- [update_json_records](#trade_records.update_json_records)
- [update_csv_record](#trade_records.update_csv_record)
- [update_json_record](#trade_records.update_json_record)
<a id="trade_records"></a>
<a id="trade_records.trade_records"></a>
### Trade Records
```python
class TradeRecords()
```
This utility class read trade records from csv and json files, and update them based on their closing positions.
To use this default implementation the csv or json file should be able to provide the following data.
`['order', 'symbol', 'actual_profit', 'win', 'closed']`
Once a trade have been closed, the actual profit and win status will be updated in the csv file.
Once a trade have been closed, the actual profit and win status will be updated in the file.
#### Default Headers
| column | type | description |
|---------------|-------|-------------------------------------------------------|
| order | int | Order id of the trade |
| symbol | str | the name of the Symbol |
| actual_profit | float | The actual profit of the trade, this zero by default |
| win | bool | The win status of the trade, this is False by default |
| closed | bool | The status of the trade, this is False by default |
#### Attributes:
| name | type | description |
|---------------|----------|-------------------------------------------|
| `config` | `Config` | Config object |
| `records_dir` | `Path` | A directory for finding the trade records |
#### Attributes
| name | type | description |
|-------------|--------|--------------------------------------------------------------|
| records_dir | Path | Absolut path to directory containing record of placed trades |
| config | Config | Config object |
<a id="__init__"></a>
### \_\_init\_\_
<a id="trade_records.__init__"></a>
### \__init\__
```python
def __init__(records_dir: Path | str = '')
def __init__(*, records_dir: Path | str = '')
```
Initialize an instance of the class.
#### Parameters
| name | type | description |
|--------------|------|----------------------------------------------------------------|
| records_dir | Path | Absolute path to directory containing record of placed trades. |
<a id="get_csv_records"></a>
#### Parameters:
| name | type | description |
|---------------|--------|----------------------------------------------------------------|
| `records_dir` | `Path` | Absolute path to directory containing record of placed trades. |
<a id="trade_records.get_csv_records"></a>
### get_csv_records
```python
async def get_csv_records()
```
Get trade records from records_dir folder.
#### Yields
#### Yields:
| type | description |
|------|--------------------|
| Path | Trade record files |
<a id="get_json_records"></a>
<a id="trade_records.get_json_records"></a>
### get_json_records
```python
async def get_json_records()
```
Get trade records from records_dir folder.
#### Yields
| type | description |
|------|--------------------|
| Path | Trade record files |
<a id="read_update_csv"></a>
<a id="trade_records.read_update_csv"></a>
### read_update_csv
```python
async def read_update_csv(file: Path)
async def read_update_csv(*, file: Path)
```
Read and update trade records from a csv file.
#### Parameters
| name | type | description |
|------|------|-------------------|
| file | Path | Trade record file |
<a id="read_update_json"></a>
#### Parameters:
| name | type | description |
|--------|--------|-------------------|
| `file` | `Path` | Trade record file |
<a id="trade_records.read_update_json"></a>
### read_update_json
```python
async def read_update_json(file: Path)
async def read_update_json(*, file: Path)
```
Read and update trade records from a json file.
#### Parameters
| name | type | description |
|------|------|-------------------|
| file | Path | Trade record file |
<a id="update_rows"></a>
#### Parameters:
| name | type | description |
|--------|--------|-------------------|
| `file` | `Path` | Trade record file |
<a id="trade_records.update_rows"></a>
### update_rows
```python
async def update_rows(rows: list[dict]) -> list[dict]
async def update_rows(*, rows: list[dict]) -> list[dict]
```
Update the rows of entered trades with the actual profit.
#### Parameters
| name | type | description |
|------|------------|---------------------------------------------------------------------------|
| rows | list[dict] | A list of dictionaries from the dictionary writer object of the csv file. |
#### Returns
| type | description |
|------------|---------------------------------------------------------------|
| list[dict] | A list of dictionaries with the actual profit and win status. |
#### Parameters:
| name | type | description |
|--------|--------------|---------------------------------------------------------------------------|
| `rows` | `list[dict]` | A list of dictionaries from the dictionary writer object of the csv file. |
<a id="update_row"></a>
#### Returns:
| Type | Description |
|--------------|---------------------------------------------------------------|
| `list[dict]` | A list of dictionaries with the actual profit and win status. |
<a id="trade_records.update_row"></a>
### update_row
```python
async def update_row(row: dict) -> dict
```
Update the row of an entered trade with the actual profit.
#### Parameters
| name | type | description |
|------|------|-------------------------------------------|
| row | dict | A dictionary from the csv file row object |
#### Returns
| type | description |
|------|------------------------------------|
#### Parameters:
| Name | Type | Description |
|-------|--------|-------------------------------------------|
| `row` | `dict` | A dictionary from the csv file row object |
#### Returns:
| Type | Description |
|------|-------------------------------------|
| dict | A dictionary with the actual profit |
<a id="trade_records.update_csv_record"></a>
### update_csv_record
```python
async def update_csv_record(*, file: Path | str)
```
Update a single trade record csv file
#### Parameters:
| Name | Type | Description |
|--------|--------|-------------------------|
| `file` | `Path` | A trade record csv file |
<a id="trade_records.update_csv_records"></a>
### update_csv_records
```python
def update_csv_records()
```
Update csv trade records in the records_dir folder.
<a id="trade_records.update_json_record"></a>
### update_csv_record
```python
async def update_json_record(*, file: Path | str)
```
Update a single trade record json file
#### Parameters:
| Name | Type | Description |
|--------|--------|--------------------------|
| `file` | `Path` | A trade record json file |
<a id="trade_records.update_json_records"></a>
### update_json_records
```python
def update_json_records()
```
Update json trade records in the records_dir folder.
docs/lib/trader.md
+133 -64
View File
@@ -3,111 +3,180 @@ Trader class module. Handles the creation of an order and the placing of trades
## Table of Contents
- [Trader](#trader)
- [\_\_init\_\_](#__init__)
- [create\_order](#create_order)
- [set\_order\_limits](#set_order_limits)
- [set\_trade\_stop_levels](#set_trade_stop_levels)
- [send\_order](#send_order)
- [check_order](#check_order)
- [record_trade](#record_trade)
- [place\_trade](#place_trade)
- [\_\_init\_\_](#trader.__init__)
- [set_trade_stop_levels_points](#trader.set_trade_stop_levels_points)
- [set_trade_stop_levels_pips](#trader.set_trade_stop_levels_pips)
- [create_order_with_points](#trade.create_order_with_points)
- [create_order_with_sl](#trade.create_order_with_sl)
- [create_order_with_stops](#trade.create_order_with_stops)
- [create_order_no_stops](#trade.create_order_no_stops)
- [send_order](#trader.send_order)
- [check_order](#trader.check_order)
- [record_trade](#trader.record_trade)
- [place_trade](#trader.place_trade)
<a name="trader"></a>
<a name="trader.trader"></a>
### Trader
```python
class Trader()
```
Base class for creating a Trader object. Handles the creation of an order and the placing of trades
#### Attributes
| Name | Type | Description | Default |
|----------|----------|-------------------------------------------------------|---------|
| `ram` | `RAM` | Risk Assessment Management System. | None |
| `config` | `Config` | Config instance. | None |
| `order` | `Order` | Order instance. | None |
| `symbol` | `Symbol` | The Financial Instrument | None |
| `params` | `Dict` | A dictionary of parameters associated with the trade. | None |
<a name="init"></a>
#### Attributes:
| Name | Type | Description | Default |
|--------------|----------|-------------------------------------------------------|---------|
| `ram` | `RAM` | Risk Assessment Management System. | None |
| `config` | `Config` | Config instance. | None |
| `order` | `Order` | Order instance. | None |
| `symbol` | `Symbol` | The Financial Instrument | None |
| `parameters` | `dict` | A dictionary of parameters associated with the trade. | None |
<a name="trader.__init__"></a>
### \_\_init\_\_
```python
def __init__(*, symbol: Symbol, ram: RAM = None)
```
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|----------|----------|-----------------------------------------|---------|
| `symbol` | `Symbol` | The Financial instrument | None |
| `symbol` | `Symbol` | The Financial instrument | |
| `ram` | `RAM` | Risk Assessment and Management instance | None |
<a name="create_order"></a>
### create\_order
```python
async def create_order(*, order_type: OrderType, `kwargs)
```
Complete the order object with the required values. Creates a simple order.
#### Parameters
| Name | Type | Description | Default |
|--------------|-------------|-------------------------------------------------------|---------|
| `order_type` | `OrderType` | Type of order | None |
| `kwargs` | | keyword arguments as required for the specific trader | |
<a name="set_order_limits"></a>
### set\_order\_limits
<a name="trader.set_trade_stop_levels_pips"></a>
### set_trade_stop_levels_pips
```python
async def set_order_limits(pips: float):
async def set_trade_stop_levels_pips(*, pips: float, risk_to_reward: float = None):
```
Sets the stop loss and take profit for the order. This method uses pips as defined for forex instruments.
#### Parameters
| Name | Type | Description | Default |
|--------|---------|-------------|---------|
| `pips` | `float` | Target pips | None |
<a name="set_trade_stop_levels"></a>
### set\_trade\_stop\_levels
#### Parameters:
| Name | Type | Description | Default |
|------------------|---------|-------------------------------|---------|
| `pips` | `float` | Target pips | |
| `risk_to_reward` | `float` | Optional risk to reward ratio | None |
<a name="trader.set_trade_stop_levels_points"></a>
### set_trade_stop_levels_points
```python
async def set_trade_stop_levels(*, points)
async def set_trade_stop_levels_points(*, points: float, risk_to_reward: float = None):
```
sets the stop loss and take profit for the order. This method uses points as defined by MetaTrader5 for all symbols.
#### Parameters
| Name | Type | Description | Default |
|----------|---------|---------------|---------|
| `points` | `float` | Target points | None |
Sets the stop loss and take profit for the order. This method uses points as defined for forex instruments.
<a name="send_order"></a>
### send\_order
#### Parameters:
| Name | Type | Description | Default |
|------------------|---------|-------------------------------|---------|
| `points` | `float` | Target points | |
| `risk_to_reward` | `float` | Optional risk to reward ratio | None |
<a name="trader.create_order_no_stops"></a>
### create_order_no_stops
```python
async def send_order()
async def create_order_no_stops(*, order_type: OrderType, volume: float = None)
```
Sends the order to the broker for execution. Record the trade.
Create an order without setting stop loss and take profit. Using minimum lot size.
<a name="check_order"></a>
#### Parameters:
| Name | Type | Description | Default |
|--------------|-------------|---------------------|---------|
| `order_type` | `OrderType` | The order type | |
| `volume` | `float` | The volume to trade | None |
<a name="trader.create_order_with_stops"></a>
### create_order_with_stops
```python
async def create_order_with_stops(*, order_type: OrderType, sl: float, tp: float, amount_to_risk: float = None)
```
Create an order with stop loss and take profit levels. Use the amount to risk per trade to
calculate the volume.
#### Parameters:
| Name | Type | Description | Default |
|------------------|-------------|--------------------|---------|
| `order_type` | `OrderType` | The order type | |
| `sl` | `float` | The stop loss` | |
| `tp` | `float` | The take profit` | |
| `amount_to_risk` | `float` | The amount to risk | None |
<a name="trader.create_order_with_sl"></a>
### create_order_with_sl
```python
async def create_order_with_sl(*, order_type: OrderType, sl: float, amount_to_risk: float = None, risk_to_reward: float = None)
```
Create an order with a given stop_loss level. Use the amount to risk per trade to calculate the volume.
#### Parameters:
| Name | Type | Description | Default |
|------------------|-------------|------------------------------------------|---------|
| `order_type` | `OrderType` | The order type | |
| `sl` | `float` | The stop loss` | |
| `risk_to_reward` | `float` | Risk to reward ratio. Optional parameter | None |
| `amount_to_risk` | `float` | The amount to risk | None |
<a name="trader.create_order_with_points"></a>
### create_order_with_points
```python
async def create_order_with_points(*, order_type: OrderType, points: float, amount_to_risk: float = None, risk_to_reward: float = None)
```
Create an order with specific points to risk. Use the amount to risk per trade to calculate the volume.
#### Parameters:
| Name | Type | Description | Default |
|------------------|-------------|------------------------------------------|---------|
| `order_type` | `OrderType` | The order type | |
| `points` | `float` | Points to risk | |
| `risk_to_reward` | `float` | Risk to reward ratio. Optional parameter | None |
| `amount_to_risk` | `float` | The amount to risk | None |
<a name="trader.send_order"></a>
### send_order
```python
async def send_order() -> OrderSendResult
```
Sends the order to the broker for execution.
#### Returns:
| Type | Description |
|-------------------|----------------------------|
| `OrderSendResult` | The OrderSendResult object |
<a name="trader.check_order"></a>
### check_order
```python
async def check_order()
async def check_order() -> OrderCheckResult
```
Checks the status of the order before placing the trade.
#### Returns
| Type | Description |
|--------|-----------------------------------|
| `bool` | True if order is valid else False |
<a name="record_trade"></a>
#### Returns:
| Type | Description |
|--------------------|-----------------------------|
| `OrderCheckResult` | The OrderCheckResult object |
<a name="trader.record_trade"></a>
### record_trade
```python
async def record_trade(result: OrderSendResult, parameters: dict = None, name: str = '', exclude: set = None)
async def record_trade(*, result: OrderSendResult, parameters: dict = None, name: str = '')
```
Records the trade and the order details if `Config.record_trades` is true. Trades are recorded as either json or csv.
#### Parameters
#### Parameters:
| Name | Type | Description | Default |
|--------------|-------------------|--------------------------------------------------------------|---------|
| `result` | `OrderSendResult` | The result of the placed order | None |
| `result` | `OrderSendResult` | The result of the placed order | |
| `parameters` | `dict` | parameters to saved instead of the ones in `self.parameters` | None |
| `name` | `str` | Name for the csv or json file | '' |
| `exclude` | `set` | Set of keys to exclude from the saved parameters | None |
<a name="place_trade"></a>
### place\_trade
<a name="trader.place_trade"></a>
### place_trade
```python
@abstractmethod
async def place_trade(self, *args, **kwargs):
async def place_trade(self, *args, **kwargs)
```
Places a trade. All traders must implement this method.
sample_backtest.py
+2 -2
View File
@@ -30,13 +30,13 @@ async def back_tester():
back_test_engine = BackTestEngine(
start=start,
end=end,
speed=300,
speed=3600,
stop_time=stop_time,
close_open_positions_on_exit=True,
assign_to_config=True,
preload=True,
account_info={'balance': 350}
)
await back_test_engine.setup_account(balance=350)
backtester = BackTester(backtest_engine=back_test_engine)
backtester.add_strategies(strategies=strategies)
await backtester.start()
src/aiomql/core/backtesting/backtest_controller.py
+1 -1
View File
@@ -69,7 +69,7 @@ class BackTestController:
if self.backtest_engine.stop_testing:
logger.info(
"Stop trading called in control at %s",
self.backtest_engine.cursor.time,
datetime.fromtimestamp(self.backtest_engine.cursor.time).strftime("%Y-%m-%d %H:%M:%S"),
)
break
await self.backtest_engine.wrap_up()
src/aiomql/core/backtesting/backtest_engine.py
+29 -5
View File
@@ -75,7 +75,7 @@ class BackTestEngine:
preloaded_ticks: dict[str, DataFrame]
preload: bool
account_lock: RLock
account_info: dict
def __init__(
self,
*,
@@ -89,7 +89,8 @@ class BackTestEngine:
stop_time: float | datetime = None,
close_open_positions_on_exit: bool = True,
preload=True,
assign_to_config: bool = False,
assign_to_config: bool = True,
account_info: dict = None
):
self._data = data or BackTestData()
self.mt5 = MetaTrader()
@@ -127,6 +128,7 @@ class BackTestEngine:
self.preload = preload
self.preloaded_ticks = {}
self.account_lock = RLock()
self.account_info = account_info or {}
def __next__(self) -> Cursor:
try:
@@ -152,7 +154,7 @@ class BackTestEngine:
):
if self._data.span and self._data.range:
start = start or self._data.span[0]
end = end or self._data.span[-1] + 1
end = end or self._data.span[-1] + speed
start = (
start.astimezone(tz=UTC)
if isinstance(start, datetime)
@@ -172,8 +174,9 @@ class BackTestEngine:
if restart is False and self._data.cursor is not None:
self.cursor = self._data.cursor
new_range = range(self.range[self.cursor.index], self.range.stop)
new_span = range(self.span[self.cursor.index], self.span.stop)
index = self.cursor.index // speed
new_range = range(self.range[index], self.range.stop, speed)
new_span = range(self.span[index], self.span.stop, speed)
self.iter = zip(new_range, new_span)
# self.go_to(time=self.cursor.time)
else:
@@ -647,6 +650,7 @@ class BackTestEngine:
@error_handler
async def setup_account(self, **kwargs):
kwargs = {**self.account_info, **kwargs}
default = {
"profit": self._account.profit,
"margin": self._account.margin,
@@ -664,6 +668,26 @@ class BackTestEngine:
self._account.set_attrs(**default)
self.update_account()
@error_handler_sync
def setup_account_sync(self, **kwargs):
kwargs = {**self.account_info, **kwargs}
default = {
"profit": self._account.profit,
"margin": self._account.margin,
"equity": self._account.equity,
"margin_free": self._account.margin_free,
"margin_level": self._account.margin_level,
"balance": self._account.balance,
**{k: v for k, v in kwargs.items() if k in self._account.__match_args__},
}
if self.use_terminal:
acc_info = self.mt5._account_info()
default = {**acc_info._asdict(), **default}
self._account.set_attrs(**default)
self.update_account()
@cached_property
def prices(self) -> dict[str, DataFrame]:
prices = {}
src/aiomql/core/meta_backtester.py
+39 -1
View File
@@ -43,7 +43,10 @@ class MetaBackTester(MetaTrader):
self.config.backtest_engine = value
async def last_error(self) -> tuple[int, str]:
return -1, ""
if self.config.use_terminal_for_backtesting is False:
return -1, ""
else:
return await super().last_error()
async def initialize(
self,
@@ -66,6 +69,41 @@ class MetaBackTester(MetaTrader):
return True
def initialize_sync(
self,
*,
path: str = "",
login: int = 0,
password: str = "",
server: str = "",
timeout: int | None = None,
portable=False,
) -> bool:
if self.config.use_terminal_for_backtesting:
return super().initialize_sync(
path=path,
login=login,
password=password,
server=server,
timeout=timeout,
)
return True
def login_sync(
self,
*,
login: int = 0,
password: str = "",
server: str = "",
timeout: int = 60000,
) -> bool:
if self.config.use_terminal_for_backtesting:
return super().login_sync(
login=login, password=password, server=server, timeout=timeout
)
return True
async def login(
self,
*,
src/aiomql/lib/backtester.py
+95 -10
View File
@@ -1,12 +1,16 @@
import asyncio
from typing import Type, Iterable, Callable, Coroutine
import logging
from typing import Type, Iterable, Callable, Coroutine
from datetime import datetime, UTC
from MetaTrader5 import Tick
from .executor import Executor
from ..core.config import Config
from ..core.backtesting.backtest_controller import BackTestController
from ..core.meta_backtester import MetaBackTester
from ..core.backtesting.backtest_engine import BackTestEngine
from ..core.constants import CopyTicks
from .symbol import Symbol as Symbol
from .strategy import Strategy as Strategy
@@ -19,10 +23,8 @@ class BackTester:
Attributes:
executor: The default thread executor.
config (Config): Config instance
mt (MetaTrader): MetaTrader instance
mt (MetaBackTester): MetaTrader instance
"""
config: Config
executor: Executor
mt: MetaBackTester
@@ -38,6 +40,41 @@ class BackTester:
self.backtest_controller = BackTestController()
self.strategies = []
def initialize_sync(self):
"""Prepares the bot by signing in to the trading account and initializing the symbols for the trading session.
Starts the global task queue.
Raises:
SystemExit if sign in was not successful
"""
try:
self.mt.initialize_sync()
login = self.mt.login_sync()
if not login:
logger.critical(f"Unable to sign in to MetaTrder 5 Terminal")
raise Exception("Unable to sign in to MetaTrader 5 Terminal")
logger.info("Login Successful")
self.backtest_engine.setup_account_sync()
self.init_strategies_sync()
if (strategies := len(self.executor.strategy_runners)) == 0:
logger.warning(
"No strategies were added to the backtester. Exiting ..."
)
raise Exception("No strategies added to the backtester")
self.config.task_queue.worker_timeout = 5
self.add_coroutine(
coroutine=self.config.task_queue.run, on_separate_thread=True
)
self.add_coroutine(coroutine=self.executor.exit)
self.add_coroutine(
coroutine=self.backtest_controller.control, on_separate_thread=True
)
parties = strategies + 1
self.backtest_controller.set_parties(parties=parties)
except Exception as err:
logger.error(f"{err}. Backtester initialization failed")
raise SystemExit
async def initialize(self):
"""Prepares the bot by signing in to the trading account and initializing the symbols for the trading session.
Starts the global task queue.
@@ -52,7 +89,13 @@ class BackTester:
logger.critical(f"Unable to sign in to MetaTrder 5 Terminal")
raise Exception("Unable to sign in to MetaTrader 5 Terminal")
logger.info("Login Successful")
await self.backtest_engine.setup_account()
await self.init_strategies()
if (strategies := len(self.executor.strategy_runners)) == 0:
logger.warning(
"No strategies were added to the backtester. Exiting ..."
)
raise Exception("No strategies added to the backtester")
self.config.task_queue.worker_timeout = 5
self.add_coroutine(
coroutine=self.config.task_queue.run, on_separate_thread=True
@@ -61,11 +104,6 @@ class BackTester:
self.add_coroutine(
coroutine=self.backtest_controller.control, on_separate_thread=True
)
if (strategies := len(self.executor.strategy_runners)) == 0:
logger.warning(
"No strategies were added to the backtester. Exiting ..."
)
raise Exception("No strategies added to the backtester")
parties = strategies + 1
self.backtest_controller.set_parties(parties=parties)
except Exception as err:
@@ -95,7 +133,8 @@ class BackTester:
def execute(self):
"""Execute the bot."""
asyncio.run(self.start())
self.initialize_sync()
self.executor.execute()
async def start(self):
"""Initialize the bot and execute it. Similar to calling `execute` method but is a coroutine."""
@@ -150,7 +189,53 @@ class BackTester:
self.executor.add_strategy(strategy=strategy)
return res
def init_strategy_sync(self, *, strategy: Strategy) -> bool:
"""Initialize a single strategy. This method is called internally by the bot."""
try:
if self.backtest_engine.use_terminal is False:
info = self.backtest_engine.symbols[strategy.symbol.name]
tick = self.backtest_engine.prices[strategy.symbol.name].loc[self.backtest_engine.cursor.time]
tick = Tick(tick)
info = info._asdict() | {
"bid": tick.bid,
"bidhigh": tick.bid,
"bidlow": tick.bid,
"ask": tick.ask,
"askhigh": tick.ask,
"asklow": tick.bid,
"last": tick.last,
"volume_real": tick.volume_real,
}
strategy.symbol.set_attributes(**info)
self.executor.add_strategy(strategy=strategy)
return True
else:
info = self.mt._symbol_info(strategy.symbol.name)
time = datetime.fromtimestamp(self.backtest_engine.cursor.time, tz=UTC)
tick = self.mt._copy_ticks_from(strategy.symbol.name, time, 1, CopyTicks.ALL)
tick = Tick(tick[-1]) if tick is not None else None
info = info._asdict() | {
"bid": tick.bid,
"bidhigh": tick.bid,
"bidlow": tick.bid,
"ask": tick.ask,
"askhigh": tick.ask,
"asklow": tick.bid,
"last": tick.last,
"volume_real": tick.volume_real,
}
strategy.symbol.set_attributes(**info)
self.executor.add_strategy(strategy=strategy)
return True
except Exception as err:
logger.error("%s: Unable to initialize strategy", err)
return False
async def init_strategies(self):
"""Initialize the symbols for the current trading session. This method is called internally by the bot."""
tasks = [self.init_strategy(strategy=strategy) for strategy in self.strategies]
await asyncio.gather(*tasks)
def init_strategies_sync(self):
"""Initialize the symbols for the current trading session. This method is called internally by the bot."""
[self.init_strategy_sync(strategy=strategy) for strategy in self.strategies]
src/aiomql/lib/candle.py
+3 -58
View File
@@ -78,7 +78,7 @@ class Candle:
return self.time < other.time
def __hash__(self):
return hash(self.time)
return id(self)
def __getitem__(self, item):
return self.__dict__[item]
@@ -117,7 +117,7 @@ class Candle:
Returns:
bool: True or False
"""
return self.open > self.close
return self.close < self.open
def dict(self, *, exclude: set = None, include: set = None) -> dict:
"""
@@ -185,7 +185,7 @@ class Candles:
data (DataFrame|Candles|Iterable): A pandas dataframe, a Candles object or any suitable iterable
Keyword Args:
flip (bool): Reverse the chronological order of the candles to the oldest first. Defaults to False.
flip (bool): Reverse the chronological order of the candles to the most recent first. Defaults to False.
candle_class: A subclass of Candle to use as the candle class. Defaults to Candle.
"""
if isinstance(data, DataFrame):
@@ -289,58 +289,3 @@ class Candles:
"""
res = self._data.rename(columns=kwargs, inplace=inplace)
return self if inplace else self.__class__(data=res)
def make_addplot(self, *, count: int = 50, columns: list = None, **kwargs) -> dict:
"""
Make subplots for adding to the main plot
Args:
count (int): The numbers of candles to make the addplot for. Defaults to 50.
columns (list[str]): The columns to make the plot from. Defaults to None.
**kwargs: Valid arguments for the mplfinance make_addplot function
"""
columns = columns or []
data = self._data[-count:]
data.index = pd.to_datetime(data["time"], unit="s")
return mplt.make_addplot(data[columns], **kwargs)
def visualize(
self,
*,
count: int = 50,
_type="candle",
savefig: str | dict = None,
addplot: dict = None,
style: str = "charles",
ylabel: str = "Price",
title: str = "Chart",
**kwargs,
):
"""Visualize the candles using the mplfinance library.
Args:
count (int): The number of candles to visualize, counting from behind, i.e the most recent candles.
Defaults to 50.
_type: Type of chart, defaults to candle
savefig (str|dict): The path to save the figure or a dictionary of parameters to pass to the savefig method.
addplot: Additional plots to add to the chart. Defaults to None. They should match the dimension of the
original data which is specified via the count parameter.
style (str): The style of the chart. Defaults to 'charles'.
ylabel (str): The label of the y-axis. Defaults to 'Price'.
title (str): The title of the chart. Defaults to 'Chart'.
kwargs: valid kwargs for the plot function.
"""
kwargs |= {
key: arg
for key, arg in (
("savefig", savefig),
("addplot", addplot),
("style", style),
("ylabel", ylabel),
("title", title),
("type", _type),
)
if arg
}
data = self._data[-count:]
data.index = pd.to_datetime(data["time"], unit="s")
mplt.plot(data, **kwargs)
src/aiomql/lib/executor.py
-1
View File
@@ -19,7 +19,6 @@ class Executor:
coroutines (list[Coroutine]): A list of coroutines to run in the executor
functions (dict[Callable, dict]): A dictionary of functions to run in the executor
"""
executor: ThreadPoolExecutor
tasks: list[asyncio.Task]
config: Config
src/aiomql/lib/history.py
+13 -58
View File
@@ -3,11 +3,9 @@ from datetime import datetime
from logging import getLogger
import pytz
from pandas import DataFrame
import pandas as pd
from ..core.config import Config
from ..core.meta_trader import MetaTrader, CopyTicks, OrderType
from ..core.meta_trader import MetaTrader
from ..core.models import TradeDeal, TradeOrder
from ..core.meta_backtester import MetaBackTester
from .._utils import backoff_decorator
@@ -30,21 +28,26 @@ class History:
mt5: MetaTrader | MetaBackTester
config: Config
deals: tuple[TradeDeal, ...]
orders: tuple[TradeOrder, ...]
total_deals: int
total_orders: int
group: str
def __init__(
self,
*,
date_from: datetime | int,
date_to: datetime | int,
date_from: datetime | float,
date_to: datetime | float,
group: str = "",
use_utc: bool = True,
):
"""
Args:
date_from (datetime, int): Date the orders are requested from. Set by the 'datetime' object or as a
date_from (datetime, float): Date the orders are requested from. Set by the 'datetime' object or as a
number of seconds elapsed since 1970.01.01. Defaults to twenty-four hours from the current time in 'utc'
date_to (datetime, int): Date up to which the orders are requested. Set by the 'datetime' object or as a
date_to (datetime, float): Date up to which the orders are requested. Set by the 'datetime' object or as a
number of seconds elapsed since 1970.01.01. Defaults to the current time in "utc"
group (str): Filter for selecting history by symbols. Defaults to an empty string
@@ -73,7 +76,7 @@ class History:
"""Get history deals and orders"""
deals, orders = await asyncio.gather(
self.get_deals(), self.get_orders(), return_exceptions=True
)
)
self.deals = deals if isinstance(deals, tuple) else ()
self.orders = orders if isinstance(orders, tuple) else ()
self.total_deals = len(self.deals)
@@ -82,8 +85,9 @@ class History:
@backoff_decorator
async def get_deals(self) -> tuple[TradeDeal, ...]:
"""Get deals from trading history using the parameters set in the constructor.
Returns:
tuple[TradeDeal]: A list of trade deals
tuple[TradeDeal, ...]: A list of trade deals
"""
deals = await self.mt5.history_deals_get(
date_from=self.date_from, date_to=self.date_to, group=self.group
@@ -160,52 +164,3 @@ class History:
key=lambda x: x.time_done_msc,
)
)
async def track_order(
self, *, position: int = None, end_time: datetime = None
) -> DataFrame:
"""
Track an order from the time it was opened to the time it was closed or any given time.
The tracking is done by getting the ticks
for the order symbol from the time the order was opened to the time it was closed. The profit for each tick is
calculated using the order type, symbol, initial volume, open price and the bid or ask price of the tick
depending on the order type.
Args:
end_time (datetime): The time to stop tracking the order. If not provided, the tracking will continue until
the order is closed.
position (int): The position ticket
end_time (int): The time to stop tracking the order in seconds. If not provided, the tracking will continue
until the order is closed.
Returns:
DataFrame: A pandas DataFrame of the ticks and profit for the order.
"""
orders = self.get_orders_by_position(position=position)
deals = self.get_deals_by_position(position=position)
open_order = orders[0]
open_deal = deals[0]
close_deal = deals[-1]
time_done = (
datetime.timestamp(end_time) if end_time is not None else close_deal.time
)
time_done_msc = int(time_done * 1000)
open_order.set_attributes(
time_done_msc=time_done_msc, time_done=time_done, price_open=open_deal.price
)
ticks = await self.mt5.copy_ticks_range(
open_order.symbol,
open_order.time_setup,
open_order.time_done,
CopyTicks.ALL,
)
data = pd.DataFrame(ticks)
profit = lambda x: self.mt5._order_calc_profit(
open_order.type,
open_order.symbol,
open_order.volume_initial,
open_order.price_open,
x.ask if open_order.type == OrderType.BUY else x.bid,
)
data["profits"] = data.apply(profit, axis=1)
data["time"] = pd.to_datetime(data["time"], unit="s")
data.set_index("time", inplace=True)
return data
src/aiomql/lib/order.py
+6 -7
View File
@@ -37,11 +37,11 @@ class Order(_Base, TradeRequest):
"""Get the number of active pending orders.
Returns:
(int): total number of active orders
(int): total number of active pending orders
"""
return await self.mt5.orders_total()
async def get_order(self, *, ticket: int) -> TradeOrder | None:
async def get_pending_order(self, *, ticket: int) -> TradeOrder | None:
"""
Get a pending order by ticket number.
@@ -57,17 +57,16 @@ class Order(_Base, TradeRequest):
return TradeOrder(**order_._asdict())
return order
async def get_orders(
self, *, ticket: int = 0, symbol: str = "", group: str = ""
) -> tuple[TradeOrder, ...]:
async def get_pending_orders(self, *, ticket: int = 0, symbol: str = "", group: str = "") -> tuple[TradeOrder, ...]:
"""Get the list of active pending orders for the current symbol.
Keyword Args:
Args:
ticket (int): Order ticket number
symbol (str): Symbol name
group (str): Group name
Returns:
tuple[TradeOrder]: A Tuple of active trade orders as TradeOrder objects
tuple[TradeOrder, ...]: A Tuple of active pending trade orders as TradeOrder objects
"""
orders = await self.mt5.orders_get(symbol=symbol, ticket=ticket, group=group)
if orders is not None:
src/aiomql/lib/positions.py
+1 -1
View File
@@ -58,7 +58,7 @@ class Positions:
return None
return TradePosition(**position._asdict())
async def get_position_by_symbol(self, *, symbol: str) -> tuple[TradePosition, ...]:
async def get_positions_by_symbol(self, *, symbol: str) -> tuple[TradePosition, ...]:
"""Get open positions by symbol.
Args:
symbol (str): Financial instrument name.
src/aiomql/lib/result.py
+1 -4
View File
@@ -12,7 +12,6 @@ logger = getLogger(__name__)
class Result:
"""A base class for handling trade results and strategy parameters for record keeping and reference purpose.
The data property must be implemented in the subclass
Attributes:
config (Config): The configuration object
@@ -22,9 +21,7 @@ class Result:
config: Config
lock = Lock()
def __init__(
self, *, result: OrderSendResult, parameters: dict = None, name: str = ""
):
def __init__(self, *, result: OrderSendResult, parameters: dict = None, name: str = ""):
"""
Prepare result data
Args:
src/aiomql/lib/sessions.py
-5
View File
@@ -214,11 +214,6 @@ class Sessions:
Attributes:
sessions (list[Session]): A list of Session objects.
current_session (Session): The current session.
Methods:
find: Find a session that contains a datetime.time object.
find_next: Find the next session that contains a datetime.time object.
check: Check if the current session has started and if not, wait until it starts.
"""
sessions: list[Session]
src/aiomql/lib/strategy.py
+4
View File
@@ -27,6 +27,10 @@ class Strategy(ABC):
parameters (Dict): A dictionary of parameters for the strategy.
sessions (Sessions): The sessions to use for the strategy.
running (bool): A flag to indicate if the strategy is running.
backtest_controller (BackTestController): A controller for running the backtester.
current_session (Session): The current session.
mt5 (MetaTrader|MetaBackTester): The MetaTrader object.
config (Config): The config object.
Notes:
Define the name of a strategy as a class attribute. If not provided, the class name will be used as the name.
src/aiomql/lib/symbol.py
+5 -8
View File
@@ -1,5 +1,4 @@
"""Symbol class for handling a financial instrument."""
import asyncio
from datetime import datetime
from logging import getLogger
@@ -41,6 +40,7 @@ class Symbol(_Base, SymbolInfo):
super().__init__(**kwargs)
self.account = Account()
@backoff_decorator
async def info_tick(self, *, name: str = "") -> Tick | None:
"""Get the current price tick of a financial instrument.
@@ -127,14 +127,11 @@ class Symbol(_Base, SymbolInfo):
Returns:
tuple[BookInfo]: Returns the Market Depth contents as a tuples of BookInfo Objects
Raises:
ValueError: If request was unsuccessful and None was returned
"""
infos = await self.mt5.market_book_get(self.name)
book_info = await self.mt5.market_book_get(self.name)
if infos is not None:
book_infos = (BookInfo(**info._asdict()) for info in infos)
if book_info is not None:
book_infos = (BookInfo(**info._asdict()) for info in book_info)
return tuple(book_infos)
raise ValueError(f"Could not get book info for {self.name}")
@@ -147,7 +144,7 @@ class Symbol(_Base, SymbolInfo):
"""
return await self.mt5.market_book_release(self.name)
def check_volume(self, *, volume) -> tuple[bool, float]:
def check_volume(self, *, volume: float) -> tuple[bool, float]:
"""Check if the volume is within the limits of the symbol. If not, return the nearest limit.
Args:
src/aiomql/lib/terminal.py
-3
View File
@@ -15,9 +15,6 @@ Version = NamedTuple(
class Terminal(_Base, TerminalInfo):
"""Terminal Class. Get information about the MetaTrader 5 terminal. The class is a subclass of the TerminalInfo
class. It inherits all the attributes and methods of the TerminalInfo class and adds some useful methods.
Notes:
Other attributes are defined in the TerminalInfo Class
"""
version: Version | None = None
src/aiomql/lib/ticks.py
-57
View File
@@ -5,8 +5,6 @@ import time
from pandas import DataFrame, Series
import pandas_ta as ta
import mplfinance as mplt
import pandas as pd
from ..core.constants import TickFlag
@@ -212,58 +210,3 @@ class Ticks:
"""
res = self._data.rename(columns=kwargs, inplace=inplace)
return res if inplace else self.__class__(data=res)
def make_addplot(self, *, count: int = 50, columns: list = None, **kwargs) -> dict:
"""
Make subplots for adding to the main plot
Args:
count (int): The numbers of candles to make the addplot for. Defaults to 50.
columns (list[str]): The columns to make the plot from. Defaults to None.
**kwargs: Valid arguments for the mplfinance make_addplot function
"""
columns = columns or []
data = self._data[-count:]
data.index = pd.to_datetime(data["time"], unit="s")
return mplt.make_addplot(data[columns], **kwargs)
def visualize(
self,
*,
count: int = 50,
_type="candle",
savefig: str | dict = None,
addplot: dict = None,
style: str = "charles",
ylabel: str = "Price",
title: str = "Chart",
**kwargs,
):
"""Visualize the candles using the mplfinance library.
Args:
count (int): The number of candles to visualize, counting from behind, i.e the most recent candles.
Defaults to 50.
_type: Type of chart, defaults to candle
savefig (str|dict): The path to save the figure or a dictionary of parameters to pass to the savefig method.
addplot: Additional plots to add to the chart. Defaults to None. They should match the dimension of the
original data which is specified via the count parameter.
style (str): The style of the chart. Defaults to 'charles'.
ylabel (str): The label of the y-axis. Defaults to 'Price'.
title (str): The title of the chart. Defaults to 'Chart'.
kwargs: valid kwargs for the plot function.
"""
kwargs |= {
key: arg
for key, arg in (
("savefig", savefig),
("addplot", addplot),
("style", style),
("ylabel", ylabel),
("title", title),
("type", _type),
)
if arg
}
data = self._data[-count:]
data.index = pd.to_datetime(data["time"], unit="s")
mplt.plot(data, **kwargs)
src/aiomql/lib/trader.py
+4 -5
View File
@@ -47,16 +47,17 @@ class Trader(ABC):
self.order = Order(symbol=symbol.name)
self.parameters = {}
def set_trade_stop_levels_pips(self, *, pips: float):
def set_trade_stop_levels_pips(self, *, pips: float, risk_to_reward: float = None):
"""Sets the stop loss and take profit for the order.
This method uses pips as defined for forex instruments. It is assumed that order_type and price are already
set before calling this method.
Args:
pips (float): Target pips
risk_to_reward (float): Optional risk to reward ratio
"""
pips = pips * self.symbol.pip
sl, tp = pips, pips * self.ram.risk_to_reward
sl, tp = pips, pips * (risk_to_reward or self.ram.risk_to_reward)
price = self.order.price
if self.order.type == OrderType.BUY:
self.order.sl, self.order.tp = round(price - sl, self.symbol.digits), round(
@@ -176,9 +177,7 @@ class Trader(ABC):
self.order.volume = volume
self.set_trade_stop_levels_points(points=points, risk_to_reward=risk_to_reward)
async def create_order_no_stops(
self, *, order_type: OrderType, volume: float = None
):
async def create_order_no_stops(self, *, order_type: OrderType, volume: float = None):
"""Create an order without setting stop loss and take profit. Using minimum lot size.
Args:
tests/backtest/integration/test_backtesting.py
+1 -1
View File
@@ -150,10 +150,10 @@ async def test_wrapup(positions, buy_order, sell_order, backtest_engine, config)
backtest_engine.fast_forward(steps=5000)
await backtest_engine.tracker()
await positions.close_position_by_ticket(ticket=bo.order)
await backtest_engine.wrap_up()
last_balance = backtest_engine._account.balance
last_equity = backtest_engine._account.equity
last_profit = backtest_engine._account.profit
await backtest_engine.wrap_up()
tdata = GetData.load_data(name=config.backtest_dir / f"{backtest_engine.name}.pkl")
new_bte = BackTestEngine(
data=tdata, restart=False, assign_to_config=False, preload=False
tests/live/integration/test_bot_sync.py
-1
View File
@@ -22,4 +22,3 @@ def test_bot_sync():
assert len(bot.executor.strategy_runners) == 3
assert len(bot.executor.coroutines) == 1
assert len(bot.executor.coroutine_threads) == 1
assert bot.config.shutdown is True
tests/live/unit/test_backtest_engine.py
+6
View File
@@ -144,6 +144,12 @@ class TestBackTestEngine:
assert acc.margin_free == 62.5
assert acc.margin_level == 2600
def test_account_sync(self):
balance = 200
self.bte.setup_account_sync(balance=balance)
acc = self.bte.get_account_info()
assert acc.balance == balance
async def test_bte2_init(self, bte2):
assert bte2._data.fully_loaded is True
assert bte2.span == self.bte.span
tests/live/unit/test_positions.py
+1 -1
View File
@@ -25,6 +25,6 @@ class TestPositions:
async def test_get_position_by_symbol(self):
symbol = self.positions.positions[0].symbol
positions = await self.positions.get_position_by_symbol(symbol=symbol)
positions = await self.positions.get_positions_by_symbol(symbol=symbol)
assert len(positions) >= 0
assert positions[0].symbol == symbol
trade_records/Chaos.csv
+177
View File
@@ -0,0 +1,177 @@
name,win,slow_ema,ask,htf,actual_profit,order,expected_profit,ltf,lcc,hcc,fast_ema,price,volume,bid,closed,date,deal,symbol
Chaos,False,20,213158.32,TIMEFRAME_M2,0,878350736,0,TIMEFRAME_M1,100,100,8,213106.78,0.001,213106.78,False,2024-05-01 00:00:00.000000,103158006,Volatility 75 Index
Chaos,False,20,1530.17,TIMEFRAME_M2,0,801551760,0,TIMEFRAME_M1,100,100,8,1530.17,0.5,1529.72,False,2024-05-01 00:00:00.000000,162874674,Volatility 100 Index
Chaos,False,20,6262.652,TIMEFRAME_M2,0,851604968,0,TIMEFRAME_M1,100,100,8,6262.478,0.5,6262.478,False,2024-05-01 00:00:00.000000,135164162,Volatility 10 Index
Chaos,False,20,2223.324,TIMEFRAME_M2,0,810694221,0,TIMEFRAME_M1,100,100,8,2223.172,0.5,2223.172,False,2024-05-01 00:00:00.000000,121070859,Volatility 25 Index
Chaos,False,20,2223.324,TIMEFRAME_M2,0,833616949,0,TIMEFRAME_M1,100,100,8,2223.172,0.5,2223.172,False,2024-05-01 01:00:00.000000,125289226,Volatility 25 Index
Chaos,False,20,1530.17,TIMEFRAME_M2,0,871792218,0,TIMEFRAME_M1,100,100,8,1530.17,0.5,1529.72,False,2024-05-01 01:00:00.000000,161532936,Volatility 100 Index
Chaos,False,20,6274.875,TIMEFRAME_M2,0,877219427,0,TIMEFRAME_M1,100,100,8,6274.701,0.5,6274.701,False,2024-05-01 01:00:00.000000,123593949,Volatility 10 Index
Chaos,False,20,213252.53,TIMEFRAME_M2,0,830942668,0,TIMEFRAME_M1,100,100,8,213252.53,0.001,213200.99,False,2024-05-01 01:00:00.000000,142981254,Volatility 75 Index
Chaos,False,20,1554.67,TIMEFRAME_M2,0,847316898,0,TIMEFRAME_M1,100,100,8,1554.67,0.5,1554.22,False,2024-05-01 02:00:00.000000,191230468,Volatility 100 Index
Chaos,False,20,213252.53,TIMEFRAME_M2,0,839692427,0,TIMEFRAME_M1,100,100,8,213200.99,0.001,213200.99,False,2024-05-01 02:00:00.000000,169216508,Volatility 75 Index
Chaos,False,20,2211.736,TIMEFRAME_M2,0,890538270,0,TIMEFRAME_M1,100,100,8,2211.736,0.5,2211.584,False,2024-05-01 02:00:00.000000,122356467,Volatility 25 Index
Chaos,False,20,6275.654,TIMEFRAME_M2,0,835972740,0,TIMEFRAME_M1,100,100,8,6275.48,0.5,6275.48,False,2024-05-01 02:00:00.000000,151119257,Volatility 10 Index
Chaos,False,20,6275.654,TIMEFRAME_M2,0,816903676,0,TIMEFRAME_M1,100,100,8,6275.654,0.5,6275.48,False,2024-05-01 02:00:00.000000,129721880,Volatility 10 Index
Chaos,False,20,214422.41,TIMEFRAME_M2,0,844736060,0,TIMEFRAME_M1,100,100,8,214370.87,0.001,214370.87,False,2024-05-01 02:00:00.000000,164906038,Volatility 75 Index
Chaos,False,20,1530.52,TIMEFRAME_M2,0,852510195,0,TIMEFRAME_M1,100,100,8,1530.52,0.5,1530.07,False,2024-05-01 03:00:00.000000,151783118,Volatility 100 Index
Chaos,False,20,2212.057,TIMEFRAME_M2,0,847363912,0,TIMEFRAME_M1,100,100,8,2211.905,0.5,2211.905,False,2024-05-01 03:00:00.000000,138362396,Volatility 25 Index
Chaos,False,20,6266.259,TIMEFRAME_M2,0,820156416,0,TIMEFRAME_M1,100,100,8,6266.259,0.5,6266.085,False,2024-05-01 03:00:00.000000,164940319,Volatility 10 Index
Chaos,False,20,2212.057,TIMEFRAME_M2,0,858925801,0,TIMEFRAME_M1,100,100,8,2212.057,0.5,2211.905,False,2024-05-01 03:00:00.000000,116888736,Volatility 25 Index
Chaos,False,20,1541.23,TIMEFRAME_M2,0,866849933,0,TIMEFRAME_M1,100,100,8,1540.78,0.5,1540.78,False,2024-05-01 03:00:00.000000,144159935,Volatility 100 Index
Chaos,False,20,214248.02,TIMEFRAME_M2,0,853614811,0,TIMEFRAME_M1,100,100,8,214248.02,0.001,214196.48,False,2024-05-01 03:00:00.000000,184486804,Volatility 75 Index
Chaos,False,20,2212.057,TIMEFRAME_M2,0,864445967,0,TIMEFRAME_M1,100,100,8,2211.905,0.5,2211.905,False,2024-05-01 03:00:00.000000,193861841,Volatility 25 Index
Chaos,False,20,214248.02,TIMEFRAME_M2,0,873343446,0,TIMEFRAME_M1,100,100,8,214248.02,0.001,214196.48,False,2024-05-01 03:00:00.000000,112619278,Volatility 75 Index
Chaos,False,20,6266.259,TIMEFRAME_M2,0,836486112,0,TIMEFRAME_M1,100,100,8,6266.085,0.5,6266.085,False,2024-05-01 04:00:00.000000,154892406,Volatility 10 Index
Chaos,False,20,1541.23,TIMEFRAME_M2,0,871161343,0,TIMEFRAME_M1,100,100,8,1540.78,0.5,1540.78,False,2024-05-01 04:00:00.000000,174449452,Volatility 100 Index
Chaos,False,20,2204.2,TIMEFRAME_M2,0,813203733,0,TIMEFRAME_M1,100,100,8,2204.048,0.5,2204.048,False,2024-05-01 04:00:00.000000,179122485,Volatility 25 Index
Chaos,False,20,6258.229,TIMEFRAME_M2,0,855824654,0,TIMEFRAME_M1,100,100,8,6258.229,0.5,6258.055,False,2024-05-01 04:00:00.000000,127729398,Volatility 10 Index
Chaos,False,20,214393.69,TIMEFRAME_M2,0,870424059,0,TIMEFRAME_M1,100,100,8,214393.69,0.001,214342.15,False,2024-05-01 04:00:00.000000,163872308,Volatility 75 Index
Chaos,False,20,1532.57,TIMEFRAME_M2,0,836080689,0,TIMEFRAME_M1,100,100,8,1532.12,0.5,1532.12,False,2024-05-01 04:00:00.000000,148053187,Volatility 100 Index
Chaos,False,20,1532.57,TIMEFRAME_M2,0,844757802,0,TIMEFRAME_M1,100,100,8,1532.12,0.5,1532.12,False,2024-05-01 04:00:00.000000,164739883,Volatility 100 Index
Chaos,False,20,214393.69,TIMEFRAME_M2,0,844907343,0,TIMEFRAME_M1,100,100,8,214393.69,0.001,214342.15,False,2024-05-01 04:00:00.000000,128393904,Volatility 75 Index
Chaos,False,20,2204.2,TIMEFRAME_M2,0,889174320,0,TIMEFRAME_M1,100,100,8,2204.048,0.5,2204.048,False,2024-05-01 04:00:00.000000,114266815,Volatility 25 Index
Chaos,False,20,6258.229,TIMEFRAME_M2,0,851849681,0,TIMEFRAME_M1,100,100,8,6258.055,0.5,6258.055,False,2024-05-01 04:00:00.000000,176764971,Volatility 10 Index
Chaos,False,20,2199.649,TIMEFRAME_M2,0,843785198,0,TIMEFRAME_M1,100,100,8,2199.649,0.5,2199.497,False,2024-05-01 05:00:00.000000,185687277,Volatility 25 Index
Chaos,False,20,1533.0,TIMEFRAME_M2,0,806097447,0,TIMEFRAME_M1,100,100,8,1533.0,0.5,1532.55,False,2024-05-01 05:00:00.000000,180410065,Volatility 100 Index
Chaos,False,20,214234.49,TIMEFRAME_M2,0,867650998,0,TIMEFRAME_M1,100,100,8,214234.49,0.001,214182.95,False,2024-05-01 05:00:00.000000,156476267,Volatility 75 Index
Chaos,False,20,6264.311,TIMEFRAME_M2,0,822654546,0,TIMEFRAME_M1,100,100,8,6264.311,0.5,6264.137,False,2024-05-01 05:00:00.000000,161222099,Volatility 10 Index
Chaos,False,20,6264.311,TIMEFRAME_M2,0,822027320,0,TIMEFRAME_M1,100,100,8,6264.311,0.5,6264.137,False,2024-05-01 06:00:00.000000,159342582,Volatility 10 Index
Chaos,False,20,214234.49,TIMEFRAME_M2,0,800079192,0,TIMEFRAME_M1,100,100,8,214234.49,0.001,214182.95,False,2024-05-01 06:00:00.000000,126684464,Volatility 75 Index
Chaos,False,20,1551.9,TIMEFRAME_M2,0,871338447,0,TIMEFRAME_M1,100,100,8,1551.9,0.5,1551.45,False,2024-05-01 06:00:00.000000,193824236,Volatility 100 Index
Chaos,False,20,2197.204,TIMEFRAME_M2,0,885139336,0,TIMEFRAME_M1,100,100,8,2197.052,0.5,2197.052,False,2024-05-01 06:00:00.000000,167682497,Volatility 25 Index
Chaos,False,20,6260.308,TIMEFRAME_M2,0,877620534,0,TIMEFRAME_M1,100,100,8,6260.134,0.5,6260.134,False,2024-05-01 06:00:00.000000,108058780,Volatility 10 Index
Chaos,False,20,1551.9,TIMEFRAME_M2,0,873706466,0,TIMEFRAME_M1,100,100,8,1551.9,0.5,1551.45,False,2024-05-01 07:00:00.000000,171070574,Volatility 100 Index
Chaos,False,20,213020.43,TIMEFRAME_M2,0,855445602,0,TIMEFRAME_M1,100,100,8,212968.89,0.001,212968.89,False,2024-05-01 07:00:00.000000,191065557,Volatility 75 Index
Chaos,False,20,2190.008,TIMEFRAME_M2,0,899388418,0,TIMEFRAME_M1,100,100,8,2189.856,0.5,2189.856,False,2024-05-01 07:00:00.000000,189449030,Volatility 25 Index
Chaos,False,20,6259.793,TIMEFRAME_M2,0,869073467,0,TIMEFRAME_M1,100,100,8,6259.619,0.5,6259.619,False,2024-05-01 07:00:00.000000,173296439,Volatility 10 Index
Chaos,False,20,2190.008,TIMEFRAME_M2,0,887146622,0,TIMEFRAME_M1,100,100,8,2189.856,0.5,2189.856,False,2024-05-01 07:00:00.000000,199610850,Volatility 25 Index
Chaos,False,20,214214.09,TIMEFRAME_M2,0,811967805,0,TIMEFRAME_M1,100,100,8,214162.55,0.001,214162.55,False,2024-05-01 07:00:00.000000,170460203,Volatility 75 Index
Chaos,False,20,1570.68,TIMEFRAME_M2,0,817816770,0,TIMEFRAME_M1,100,100,8,1570.23,0.5,1570.23,False,2024-05-01 07:00:00.000000,154212076,Volatility 100 Index
Chaos,False,20,214214.09,TIMEFRAME_M2,0,884148623,0,TIMEFRAME_M1,100,100,8,214214.09,0.001,214162.55,False,2024-05-01 07:00:00.000000,100971853,Volatility 75 Index
Chaos,False,20,1570.68,TIMEFRAME_M2,0,861937441,0,TIMEFRAME_M1,100,100,8,1570.23,0.5,1570.23,False,2024-05-01 07:00:00.000000,140379711,Volatility 100 Index
Chaos,False,20,6259.793,TIMEFRAME_M2,0,851780777,0,TIMEFRAME_M1,100,100,8,6259.619,0.5,6259.619,False,2024-05-01 08:00:00.000000,104321399,Volatility 10 Index
Chaos,False,20,2190.008,TIMEFRAME_M2,0,865554473,0,TIMEFRAME_M1,100,100,8,2190.008,0.5,2189.856,False,2024-05-01 08:00:00.000000,113071616,Volatility 25 Index
Chaos,False,20,2195.456,TIMEFRAME_M2,0,882065437,0,TIMEFRAME_M1,100,100,8,2195.456,0.5,2195.304,False,2024-05-01 08:00:00.000000,175555279,Volatility 25 Index
Chaos,False,20,213829.91,TIMEFRAME_M2,0,822701548,0,TIMEFRAME_M1,100,100,8,213829.91,0.001,213778.37,False,2024-05-01 08:00:00.000000,163660466,Volatility 75 Index
Chaos,False,20,1551.23,TIMEFRAME_M2,0,837493772,0,TIMEFRAME_M1,100,100,8,1551.23,0.5,1550.78,False,2024-05-01 08:00:00.000000,184177483,Volatility 100 Index
Chaos,False,20,6264.7,TIMEFRAME_M2,0,848384485,0,TIMEFRAME_M1,100,100,8,6264.526,0.5,6264.526,False,2024-05-01 08:00:00.000000,109838346,Volatility 10 Index
Chaos,False,20,6264.7,TIMEFRAME_M2,0,872386905,0,TIMEFRAME_M1,100,100,8,6264.526,0.5,6264.526,False,2024-05-01 08:00:00.000000,170607941,Volatility 10 Index
Chaos,False,20,2195.456,TIMEFRAME_M2,0,805883016,0,TIMEFRAME_M1,100,100,8,2195.304,0.5,2195.304,False,2024-05-01 09:00:00.000000,146304663,Volatility 25 Index
Chaos,False,20,1551.23,TIMEFRAME_M2,0,805013163,0,TIMEFRAME_M1,100,100,8,1551.23,0.5,1550.78,False,2024-05-01 09:00:00.000000,163150971,Volatility 100 Index
Chaos,False,20,213482.63,TIMEFRAME_M2,0,856110839,0,TIMEFRAME_M1,100,100,8,213482.63,0.001,213431.09,False,2024-05-01 09:00:00.000000,197625059,Volatility 75 Index
Chaos,False,20,2197.637,TIMEFRAME_M2,0,856826096,0,TIMEFRAME_M1,100,100,8,2197.637,0.5,2197.485,False,2024-05-01 09:00:00.000000,121012840,Volatility 25 Index
Chaos,False,20,1556.55,TIMEFRAME_M2,0,858513739,0,TIMEFRAME_M1,100,100,8,1556.55,0.5,1556.1,False,2024-05-01 09:00:00.000000,171822038,Volatility 100 Index
Chaos,False,20,213482.63,TIMEFRAME_M2,0,871005991,0,TIMEFRAME_M1,100,100,8,213482.63,0.001,213431.09,False,2024-05-01 09:00:00.000000,164094613,Volatility 75 Index
Chaos,False,20,6264.3,TIMEFRAME_M2,0,828666719,0,TIMEFRAME_M1,100,100,8,6264.126,0.5,6264.126,False,2024-05-01 09:00:00.000000,189567334,Volatility 10 Index
Chaos,False,20,213482.63,TIMEFRAME_M2,0,842779615,0,TIMEFRAME_M1,100,100,8,213482.63,0.001,213431.09,False,2024-05-01 09:00:00.000000,180610889,Volatility 75 Index
Chaos,False,20,6264.3,TIMEFRAME_M2,0,879920558,0,TIMEFRAME_M1,100,100,8,6264.3,0.5,6264.126,False,2024-05-01 09:00:00.000000,118956851,Volatility 10 Index
Chaos,False,20,1556.55,TIMEFRAME_M2,0,889959635,0,TIMEFRAME_M1,100,100,8,1556.55,0.5,1556.1,False,2024-05-01 09:00:00.000000,133586157,Volatility 100 Index
Chaos,False,20,2197.637,TIMEFRAME_M2,0,897734980,0,TIMEFRAME_M1,100,100,8,2197.485,0.5,2197.485,False,2024-05-01 10:00:00.000000,197574097,Volatility 25 Index
Chaos,False,20,2186.164,TIMEFRAME_M2,0,819243808,0,TIMEFRAME_M1,100,100,8,2186.012,0.5,2186.012,False,2024-05-01 10:00:00.000000,134709849,Volatility 25 Index
Chaos,False,20,6265.107,TIMEFRAME_M2,0,884028760,0,TIMEFRAME_M1,100,100,8,6264.933,0.5,6264.933,False,2024-05-01 10:00:00.000000,132973006,Volatility 10 Index
Chaos,False,20,210894.16,TIMEFRAME_M2,0,819333305,0,TIMEFRAME_M1,100,100,8,210894.16,0.001,210842.62,False,2024-05-01 10:00:00.000000,198437136,Volatility 75 Index
Chaos,False,20,1548.61,TIMEFRAME_M2,0,892662359,0,TIMEFRAME_M1,100,100,8,1548.61,0.5,1548.16,False,2024-05-01 10:00:00.000000,181673758,Volatility 100 Index
Chaos,False,20,210894.16,TIMEFRAME_M2,0,821406374,0,TIMEFRAME_M1,100,100,8,210894.16,0.001,210842.62,False,2024-05-01 11:00:00.000000,136397781,Volatility 75 Index
Chaos,False,20,2186.164,TIMEFRAME_M2,0,824473751,0,TIMEFRAME_M1,100,100,8,2186.164,0.5,2186.012,False,2024-05-01 11:00:00.000000,187165393,Volatility 25 Index
Chaos,False,20,1571.51,TIMEFRAME_M2,0,849750456,0,TIMEFRAME_M1,100,100,8,1571.51,0.5,1571.06,False,2024-05-01 11:00:00.000000,146511016,Volatility 100 Index
Chaos,False,20,6261.79,TIMEFRAME_M2,0,871122005,0,TIMEFRAME_M1,100,100,8,6261.616,0.5,6261.616,False,2024-05-01 11:00:00.000000,170479206,Volatility 10 Index
Chaos,False,20,6261.79,TIMEFRAME_M2,0,878985962,0,TIMEFRAME_M1,100,100,8,6261.616,0.5,6261.616,False,2024-05-01 11:00:00.000000,111854922,Volatility 10 Index
Chaos,False,20,213342.62,TIMEFRAME_M2,0,808390587,0,TIMEFRAME_M1,100,100,8,213291.08,0.001,213291.08,False,2024-05-01 12:00:00.000000,187618552,Volatility 75 Index
Chaos,False,20,1571.51,TIMEFRAME_M2,0,859645359,0,TIMEFRAME_M1,100,100,8,1571.51,0.5,1571.06,False,2024-05-01 12:00:00.000000,174899942,Volatility 100 Index
Chaos,False,20,2184.36,TIMEFRAME_M2,0,889766108,0,TIMEFRAME_M1,100,100,8,2184.208,0.5,2184.208,False,2024-05-01 12:00:00.000000,181639229,Volatility 25 Index
Chaos,False,20,211308.28,TIMEFRAME_M2,0,895814254,0,TIMEFRAME_M1,100,100,8,211308.28,0.001,211256.74,False,2024-05-01 12:00:00.000000,147219970,Volatility 75 Index
Chaos,False,20,2184.36,TIMEFRAME_M2,0,826074130,0,TIMEFRAME_M1,100,100,8,2184.36,0.5,2184.208,False,2024-05-01 12:00:00.000000,173317554,Volatility 25 Index
Chaos,False,20,1551.57,TIMEFRAME_M2,0,874742078,0,TIMEFRAME_M1,100,100,8,1551.12,0.5,1551.12,False,2024-05-01 12:00:00.000000,110827018,Volatility 100 Index
Chaos,False,20,6262.48,TIMEFRAME_M2,0,835724910,0,TIMEFRAME_M1,100,100,8,6262.306,0.5,6262.306,False,2024-05-01 12:00:00.000000,133221773,Volatility 10 Index
Chaos,False,20,1551.57,TIMEFRAME_M2,0,866447363,0,TIMEFRAME_M1,100,100,8,1551.57,0.5,1551.12,False,2024-05-01 12:00:00.000000,131784787,Volatility 100 Index
Chaos,False,20,6262.48,TIMEFRAME_M2,0,874161936,0,TIMEFRAME_M1,100,100,8,6262.306,0.5,6262.306,False,2024-05-01 13:00:00.000000,116269068,Volatility 10 Index
Chaos,False,20,211308.28,TIMEFRAME_M2,0,803669555,0,TIMEFRAME_M1,100,100,8,211256.74,0.001,211256.74,False,2024-05-01 13:00:00.000000,196328190,Volatility 75 Index
Chaos,False,20,2175.088,TIMEFRAME_M2,0,815139691,0,TIMEFRAME_M1,100,100,8,2175.088,0.5,2174.936,False,2024-05-01 13:00:00.000000,163638333,Volatility 25 Index
Chaos,False,20,1565.71,TIMEFRAME_M2,0,867211000,0,TIMEFRAME_M1,100,100,8,1565.71,0.5,1565.26,False,2024-05-01 13:00:00.000000,144628636,Volatility 100 Index
Chaos,False,20,2175.088,TIMEFRAME_M2,0,806576041,0,TIMEFRAME_M1,100,100,8,2175.088,0.5,2174.936,False,2024-05-01 13:00:00.000000,107502192,Volatility 25 Index
Chaos,False,20,6261.929,TIMEFRAME_M2,0,868786283,0,TIMEFRAME_M1,100,100,8,6261.929,0.5,6261.755,False,2024-05-01 13:00:00.000000,185420943,Volatility 10 Index
Chaos,False,20,211384.64,TIMEFRAME_M2,0,867523434,0,TIMEFRAME_M1,100,100,8,211333.1,0.001,211333.1,False,2024-05-01 13:00:00.000000,125206956,Volatility 75 Index
Chaos,False,20,6261.929,TIMEFRAME_M2,0,816916727,0,TIMEFRAME_M1,100,100,8,6261.755,0.5,6261.755,False,2024-05-01 13:00:00.000000,173261037,Volatility 10 Index
Chaos,False,20,211384.64,TIMEFRAME_M2,0,863896740,0,TIMEFRAME_M1,100,100,8,211333.1,0.001,211333.1,False,2024-05-01 13:00:00.000000,128242877,Volatility 75 Index
Chaos,False,20,1565.71,TIMEFRAME_M2,0,819587790,0,TIMEFRAME_M1,100,100,8,1565.71,0.5,1565.26,False,2024-05-01 13:00:00.000000,134961525,Volatility 100 Index
Chaos,False,20,2175.088,TIMEFRAME_M2,0,834812760,0,TIMEFRAME_M1,100,100,8,2175.088,0.5,2174.936,False,2024-05-01 14:00:00.000000,145588819,Volatility 25 Index
Chaos,False,20,1578.53,TIMEFRAME_M2,0,837036352,0,TIMEFRAME_M1,100,100,8,1578.08,0.5,1578.08,False,2024-05-01 14:00:00.000000,192562003,Volatility 100 Index
Chaos,False,20,6258.246,TIMEFRAME_M2,0,868259743,0,TIMEFRAME_M1,100,100,8,6258.246,0.5,6258.072,False,2024-05-01 14:00:00.000000,160280327,Volatility 10 Index
Chaos,False,20,208866.34,TIMEFRAME_M2,0,871349145,0,TIMEFRAME_M1,100,100,8,208866.34,0.001,208814.8,False,2024-05-01 14:00:00.000000,101409495,Volatility 75 Index
Chaos,False,20,2179.785,TIMEFRAME_M2,0,844410053,0,TIMEFRAME_M1,100,100,8,2179.785,0.5,2179.633,False,2024-05-01 14:00:00.000000,137160060,Volatility 25 Index
Chaos,False,20,208866.34,TIMEFRAME_M2,0,851344138,0,TIMEFRAME_M1,100,100,8,208866.34,0.001,208814.8,False,2024-05-01 14:00:00.000000,123394571,Volatility 75 Index
Chaos,False,20,2179.785,TIMEFRAME_M2,0,804253642,0,TIMEFRAME_M1,100,100,8,2179.785,0.5,2179.633,False,2024-05-01 14:00:00.000000,118936559,Volatility 25 Index
Chaos,False,20,1578.53,TIMEFRAME_M2,0,894055545,0,TIMEFRAME_M1,100,100,8,1578.08,0.5,1578.08,False,2024-05-01 15:00:00.000000,102218061,Volatility 100 Index
Chaos,False,20,6254.581,TIMEFRAME_M2,0,880406162,0,TIMEFRAME_M1,100,100,8,6254.581,0.5,6254.407,False,2024-05-01 15:00:00.000000,173031416,Volatility 10 Index
Chaos,False,20,6254.581,TIMEFRAME_M2,0,871037679,0,TIMEFRAME_M1,100,100,8,6254.407,0.5,6254.407,False,2024-05-01 15:00:00.000000,161083029,Volatility 10 Index
Chaos,False,20,209468.3,TIMEFRAME_M2,0,821219140,0,TIMEFRAME_M1,100,100,8,209468.3,0.001,209416.76,False,2024-05-01 15:00:00.000000,110425855,Volatility 75 Index
Chaos,False,20,2174.784,TIMEFRAME_M2,0,812179023,0,TIMEFRAME_M1,100,100,8,2174.784,0.5,2174.632,False,2024-05-01 15:00:00.000000,158445464,Volatility 25 Index
Chaos,False,20,1598.74,TIMEFRAME_M2,0,832261318,0,TIMEFRAME_M1,100,100,8,1598.29,0.5,1598.29,False,2024-05-01 15:00:00.000000,158409954,Volatility 100 Index
Chaos,False,20,1598.74,TIMEFRAME_M2,0,842443741,0,TIMEFRAME_M1,100,100,8,1598.29,0.5,1598.29,False,2024-05-01 15:00:00.000000,148320657,Volatility 100 Index
Chaos,False,20,2174.784,TIMEFRAME_M2,0,821932525,0,TIMEFRAME_M1,100,100,8,2174.632,0.5,2174.632,False,2024-05-01 16:00:00.000000,191304440,Volatility 25 Index
Chaos,False,20,209090.97,TIMEFRAME_M2,0,899127463,0,TIMEFRAME_M1,100,100,8,209090.97,0.001,209039.43,False,2024-05-01 16:00:00.000000,169912394,Volatility 75 Index
Chaos,False,20,6254.581,TIMEFRAME_M2,0,818220824,0,TIMEFRAME_M1,100,100,8,6254.581,0.5,6254.407,False,2024-05-01 16:00:00.000000,118836168,Volatility 10 Index
Chaos,False,20,6256.754,TIMEFRAME_M2,0,802488375,0,TIMEFRAME_M1,100,100,8,6256.754,0.5,6256.58,False,2024-05-01 16:00:00.000000,136615413,Volatility 10 Index
Chaos,False,20,209090.97,TIMEFRAME_M2,0,849928315,0,TIMEFRAME_M1,100,100,8,209039.43,0.001,209039.43,False,2024-05-01 16:00:00.000000,102706032,Volatility 75 Index
Chaos,False,20,2175.301,TIMEFRAME_M2,0,815034759,0,TIMEFRAME_M1,100,100,8,2175.149,0.5,2175.149,False,2024-05-01 16:00:00.000000,144107545,Volatility 25 Index
Chaos,False,20,1630.55,TIMEFRAME_M2,0,888911969,0,TIMEFRAME_M1,100,100,8,1630.55,0.5,1630.1,False,2024-05-01 16:00:00.000000,109934193,Volatility 100 Index
Chaos,False,20,209090.97,TIMEFRAME_M2,0,812325147,0,TIMEFRAME_M1,100,100,8,209090.97,0.001,209039.43,False,2024-05-01 16:00:00.000000,140455541,Volatility 75 Index
Chaos,False,20,2175.301,TIMEFRAME_M2,0,866260404,0,TIMEFRAME_M1,100,100,8,2175.149,0.5,2175.149,False,2024-05-01 16:00:00.000000,125635890,Volatility 25 Index
Chaos,False,20,1630.55,TIMEFRAME_M2,0,825464245,0,TIMEFRAME_M1,100,100,8,1630.1,0.5,1630.1,False,2024-05-01 17:00:00.000000,171464512,Volatility 100 Index
Chaos,False,20,6256.754,TIMEFRAME_M2,0,841026179,0,TIMEFRAME_M1,100,100,8,6256.754,0.5,6256.58,False,2024-05-01 17:00:00.000000,120742885,Volatility 10 Index
Chaos,False,20,1632.52,TIMEFRAME_M2,0,846497225,0,TIMEFRAME_M1,100,100,8,1632.52,0.5,1632.07,False,2024-05-01 17:00:00.000000,128876527,Volatility 100 Index
Chaos,False,20,211423.72,TIMEFRAME_M2,0,837311963,0,TIMEFRAME_M1,100,100,8,211423.72,0.001,211372.18,False,2024-05-01 17:00:00.000000,126408106,Volatility 75 Index
Chaos,False,20,6260.409,TIMEFRAME_M2,0,860730063,0,TIMEFRAME_M1,100,100,8,6260.235,0.5,6260.235,False,2024-05-01 17:00:00.000000,138339666,Volatility 10 Index
Chaos,False,20,2177.192,TIMEFRAME_M2,0,889145564,0,TIMEFRAME_M1,100,100,8,2177.192,0.5,2177.04,False,2024-05-01 17:00:00.000000,140414322,Volatility 25 Index
Chaos,False,20,2177.192,TIMEFRAME_M2,0,836307418,0,TIMEFRAME_M1,100,100,8,2177.192,0.5,2177.04,False,2024-05-01 17:00:00.000000,184179294,Volatility 25 Index
Chaos,False,20,1632.52,TIMEFRAME_M2,0,811365730,0,TIMEFRAME_M1,100,100,8,1632.07,0.5,1632.07,False,2024-05-01 17:00:00.000000,164537415,Volatility 100 Index
Chaos,False,20,6260.409,TIMEFRAME_M2,0,802703670,0,TIMEFRAME_M1,100,100,8,6260.235,0.5,6260.235,False,2024-05-01 17:00:00.000000,122381127,Volatility 10 Index
Chaos,False,20,211423.72,TIMEFRAME_M2,0,875174652,0,TIMEFRAME_M1,100,100,8,211423.72,0.001,211372.18,False,2024-05-01 17:00:00.000000,129015696,Volatility 75 Index
Chaos,False,20,209131.24,TIMEFRAME_M2,0,894281854,0,TIMEFRAME_M1,100,100,8,209079.7,0.001,209079.7,False,2024-05-01 18:00:00.000000,199099609,Volatility 75 Index
Chaos,False,20,1628.45,TIMEFRAME_M2,0,821822575,0,TIMEFRAME_M1,100,100,8,1628.45,0.5,1628.0,False,2024-05-01 18:00:00.000000,167835857,Volatility 100 Index
Chaos,False,20,2178.522,TIMEFRAME_M2,0,804685075,0,TIMEFRAME_M1,100,100,8,2178.522,0.5,2178.37,False,2024-05-01 18:00:00.000000,104150461,Volatility 25 Index
Chaos,False,20,6260.906,TIMEFRAME_M2,0,878169391,0,TIMEFRAME_M1,100,100,8,6260.906,0.5,6260.732,False,2024-05-01 18:00:00.000000,170084390,Volatility 10 Index
Chaos,False,20,6260.906,TIMEFRAME_M2,0,897710204,0,TIMEFRAME_M1,100,100,8,6260.906,0.5,6260.732,False,2024-05-01 18:00:00.000000,109393349,Volatility 10 Index
Chaos,False,20,2178.522,TIMEFRAME_M2,0,829288385,0,TIMEFRAME_M1,100,100,8,2178.522,0.5,2178.37,False,2024-05-01 18:00:00.000000,199032948,Volatility 25 Index
Chaos,False,20,1628.45,TIMEFRAME_M2,0,820316612,0,TIMEFRAME_M1,100,100,8,1628.0,0.5,1628.0,False,2024-05-01 18:00:00.000000,137320254,Volatility 100 Index
Chaos,False,20,209131.24,TIMEFRAME_M2,0,845210213,0,TIMEFRAME_M1,100,100,8,209079.7,0.001,209079.7,False,2024-05-01 18:00:00.000000,103274434,Volatility 75 Index
Chaos,False,20,1673.81,TIMEFRAME_M2,0,830286560,0,TIMEFRAME_M1,100,100,8,1673.81,0.5,1673.36,False,2024-05-01 19:00:00.000000,187664511,Volatility 100 Index
Chaos,False,20,6254.249,TIMEFRAME_M2,0,855390499,0,TIMEFRAME_M1,100,100,8,6254.075,0.5,6254.075,False,2024-05-01 19:00:00.000000,193728725,Volatility 10 Index
Chaos,False,20,208042.57,TIMEFRAME_M2,0,894231567,0,TIMEFRAME_M1,100,100,8,207991.03,0.001,207991.03,False,2024-05-01 19:00:00.000000,194060391,Volatility 75 Index
Chaos,False,20,2182.66,TIMEFRAME_M2,0,870875379,0,TIMEFRAME_M1,100,100,8,2182.66,0.5,2182.508,False,2024-05-01 19:00:00.000000,116811669,Volatility 25 Index
Chaos,False,20,6254.249,TIMEFRAME_M2,0,891086013,0,TIMEFRAME_M1,100,100,8,6254.075,0.5,6254.075,False,2024-05-01 19:00:00.000000,105095312,Volatility 10 Index
Chaos,False,20,2182.66,TIMEFRAME_M2,0,871825138,0,TIMEFRAME_M1,100,100,8,2182.508,0.5,2182.508,False,2024-05-01 19:00:00.000000,111189903,Volatility 25 Index
Chaos,False,20,1673.81,TIMEFRAME_M2,0,887017267,0,TIMEFRAME_M1,100,100,8,1673.81,0.5,1673.36,False,2024-05-01 19:00:00.000000,153037981,Volatility 100 Index
Chaos,False,20,208042.57,TIMEFRAME_M2,0,839045519,0,TIMEFRAME_M1,100,100,8,207991.03,0.001,207991.03,False,2024-05-01 20:00:00.000000,150923912,Volatility 75 Index
Chaos,False,20,208681.37,TIMEFRAME_M2,0,819583624,0,TIMEFRAME_M1,100,100,8,208681.37,0.001,208629.83,False,2024-05-01 20:00:00.000000,188630765,Volatility 75 Index
Chaos,False,20,6254.646,TIMEFRAME_M2,0,899250913,0,TIMEFRAME_M1,100,100,8,6254.472,0.5,6254.472,False,2024-05-01 20:00:00.000000,192999506,Volatility 10 Index
Chaos,False,20,2185.591,TIMEFRAME_M2,0,863278517,0,TIMEFRAME_M1,100,100,8,2185.591,0.5,2185.439,False,2024-05-01 20:00:00.000000,130503742,Volatility 25 Index
Chaos,False,20,1656.13,TIMEFRAME_M2,0,820517786,0,TIMEFRAME_M1,100,100,8,1656.13,0.5,1655.68,False,2024-05-01 20:00:00.000000,188068169,Volatility 100 Index
Chaos,False,20,1656.13,TIMEFRAME_M2,0,879739555,0,TIMEFRAME_M1,100,100,8,1656.13,0.5,1655.68,False,2024-05-01 20:00:00.000000,111597550,Volatility 100 Index
Chaos,False,20,2185.591,TIMEFRAME_M2,0,895888927,0,TIMEFRAME_M1,100,100,8,2185.591,0.5,2185.439,False,2024-05-01 20:00:00.000000,147283128,Volatility 25 Index
Chaos,False,20,208681.37,TIMEFRAME_M2,0,849703279,0,TIMEFRAME_M1,100,100,8,208681.37,0.001,208629.83,False,2024-05-01 20:00:00.000000,198155528,Volatility 75 Index
Chaos,False,20,6254.646,TIMEFRAME_M2,0,857450318,0,TIMEFRAME_M1,100,100,8,6254.472,0.5,6254.472,False,2024-05-01 20:00:00.000000,116520943,Volatility 10 Index
Chaos,False,20,6254.884,TIMEFRAME_M2,0,878367571,0,TIMEFRAME_M1,100,100,8,6254.884,0.5,6254.71,False,2024-05-01 21:00:00.000000,104370218,Volatility 10 Index
Chaos,False,20,2185.689,TIMEFRAME_M2,0,891681576,0,TIMEFRAME_M1,100,100,8,2185.537,0.5,2185.537,False,2024-05-01 21:00:00.000000,160283629,Volatility 25 Index
Chaos,False,20,206845.33,TIMEFRAME_M2,0,878880656,0,TIMEFRAME_M1,100,100,8,206845.33,0.001,206793.79,False,2024-05-01 21:00:00.000000,157239642,Volatility 75 Index
Chaos,False,20,1659.26,TIMEFRAME_M2,0,843249470,0,TIMEFRAME_M1,100,100,8,1659.26,0.5,1658.81,False,2024-05-01 21:00:00.000000,195888645,Volatility 100 Index
Chaos,False,20,1659.26,TIMEFRAME_M2,0,837798992,0,TIMEFRAME_M1,100,100,8,1659.26,0.5,1658.81,False,2024-05-01 21:00:00.000000,183262809,Volatility 100 Index
Chaos,False,20,2185.689,TIMEFRAME_M2,0,873559425,0,TIMEFRAME_M1,100,100,8,2185.689,0.5,2185.537,False,2024-05-01 21:00:00.000000,114878546,Volatility 25 Index
Chaos,False,20,206845.33,TIMEFRAME_M2,0,803373551,0,TIMEFRAME_M1,100,100,8,206845.33,0.001,206793.79,False,2024-05-01 21:00:00.000000,140922469,Volatility 75 Index
Chaos,False,20,6254.884,TIMEFRAME_M2,0,893174131,0,TIMEFRAME_M1,100,100,8,6254.71,0.5,6254.71,False,2024-05-01 22:00:00.000000,198319737,Volatility 10 Index
Chaos,False,20,6251.351,TIMEFRAME_M2,0,807893174,0,TIMEFRAME_M1,100,100,8,6251.351,0.5,6251.177,False,2024-05-01 22:00:00.000000,135875687,Volatility 10 Index
Chaos,False,20,2189.993,TIMEFRAME_M2,0,829178053,0,TIMEFRAME_M1,100,100,8,2189.993,0.5,2189.841,False,2024-05-01 22:00:00.000000,151482337,Volatility 25 Index
Chaos,False,20,206447.56,TIMEFRAME_M2,0,876904701,0,TIMEFRAME_M1,100,100,8,206396.02,0.001,206396.02,False,2024-05-01 22:00:00.000000,157587894,Volatility 75 Index
Chaos,False,20,1626.37,TIMEFRAME_M2,0,843626687,0,TIMEFRAME_M1,100,100,8,1625.92,0.5,1625.92,False,2024-05-01 22:00:00.000000,195164579,Volatility 100 Index
Chaos,False,20,206447.56,TIMEFRAME_M2,0,879242952,0,TIMEFRAME_M1,100,100,8,206396.02,0.001,206396.02,False,2024-05-01 22:00:00.000000,156081780,Volatility 75 Index
Chaos,False,20,1626.37,TIMEFRAME_M2,0,860168201,0,TIMEFRAME_M1,100,100,8,1625.92,0.5,1625.92,False,2024-05-01 22:00:00.000000,149723319,Volatility 100 Index
Chaos,False,20,6251.351,TIMEFRAME_M2,0,875897222,0,TIMEFRAME_M1,100,100,8,6251.351,0.5,6251.177,False,2024-05-01 22:00:00.000000,181975920,Volatility 10 Index
Chaos,False,20,2189.993,TIMEFRAME_M2,0,843022095,0,TIMEFRAME_M1,100,100,8,2189.841,0.5,2189.841,False,2024-05-01 22:00:00.000000,176917055,Volatility 25 Index
Chaos,False,20,1635.15,TIMEFRAME_M2,0,839471806,0,TIMEFRAME_M1,100,100,8,1635.15,0.5,1634.7,False,2024-05-01 23:00:00.000000,139746036,Volatility 100 Index
Chaos,False,20,205355.18,TIMEFRAME_M2,0,899076458,0,TIMEFRAME_M1,100,100,8,205303.64,0.001,205303.64,False,2024-05-01 23:00:00.000000,194980537,Volatility 75 Index
Chaos,False,20,2183.635,TIMEFRAME_M2,0,848731357,0,TIMEFRAME_M1,100,100,8,2183.483,0.5,2183.483,False,2024-05-01 23:00:00.000000,199898987,Volatility 25 Index
Chaos,False,20,6254.688,TIMEFRAME_M2,0,896618061,0,TIMEFRAME_M1,100,100,8,6254.514,0.5,6254.514,False,2024-05-01 23:00:00.000000,157000097,Volatility 10 Index
Chaos,False,20,6254.688,TIMEFRAME_M2,0,884931917,0,TIMEFRAME_M1,100,100,8,6254.688,0.5,6254.514,False,2024-05-01 23:00:00.000000,137085470,Volatility 10 Index
Chaos,False,20,1635.15,TIMEFRAME_M2,0,878294418,0,TIMEFRAME_M1,100,100,8,1635.15,0.5,1634.7,False,2024-05-01 23:00:00.000000,130821199,Volatility 100 Index
Chaos,False,20,205355.18,TIMEFRAME_M2,0,822383277,0,TIMEFRAME_M1,100,100,8,205355.18,0.001,205303.64,False,2024-05-01 23:00:00.000000,107811481,Volatility 75 Index
Chaos,False,20,2183.635,TIMEFRAME_M2,0,886310952,0,TIMEFRAME_M1,100,100,8,2183.635,0.5,2183.483,False,2024-05-01 23:00:00.000000,137929296,Volatility 25 Index
1 name win slow_ema ask htf actual_profit order expected_profit ltf lcc hcc fast_ema price volume bid closed date deal symbol
1 name win slow_ema ask htf actual_profit order expected_profit ltf lcc hcc fast_ema price volume bid closed date deal symbol
2 Chaos False 20 213158.32 TIMEFRAME_M2 0 878350736 0 TIMEFRAME_M1 100 100 8 213106.78 0.001 213106.78 False 2024-05-01 00:00:00.000000 103158006 Volatility 75 Index
3 Chaos False 20 1530.17 TIMEFRAME_M2 0 801551760 0 TIMEFRAME_M1 100 100 8 1530.17 0.5 1529.72 False 2024-05-01 00:00:00.000000 162874674 Volatility 100 Index
4 Chaos False 20 6262.652 TIMEFRAME_M2 0 851604968 0 TIMEFRAME_M1 100 100 8 6262.478 0.5 6262.478 False 2024-05-01 00:00:00.000000 135164162 Volatility 10 Index
5 Chaos False 20 2223.324 TIMEFRAME_M2 0 810694221 0 TIMEFRAME_M1 100 100 8 2223.172 0.5 2223.172 False 2024-05-01 00:00:00.000000 121070859 Volatility 25 Index
6 Chaos False 20 2223.324 TIMEFRAME_M2 0 833616949 0 TIMEFRAME_M1 100 100 8 2223.172 0.5 2223.172 False 2024-05-01 01:00:00.000000 125289226 Volatility 25 Index
7 Chaos False 20 1530.17 TIMEFRAME_M2 0 871792218 0 TIMEFRAME_M1 100 100 8 1530.17 0.5 1529.72 False 2024-05-01 01:00:00.000000 161532936 Volatility 100 Index
8 Chaos False 20 6274.875 TIMEFRAME_M2 0 877219427 0 TIMEFRAME_M1 100 100 8 6274.701 0.5 6274.701 False 2024-05-01 01:00:00.000000 123593949 Volatility 10 Index
9 Chaos False 20 213252.53 TIMEFRAME_M2 0 830942668 0 TIMEFRAME_M1 100 100 8 213252.53 0.001 213200.99 False 2024-05-01 01:00:00.000000 142981254 Volatility 75 Index
10 Chaos False 20 1554.67 TIMEFRAME_M2 0 847316898 0 TIMEFRAME_M1 100 100 8 1554.67 0.5 1554.22 False 2024-05-01 02:00:00.000000 191230468 Volatility 100 Index
11 Chaos False 20 213252.53 TIMEFRAME_M2 0 839692427 0 TIMEFRAME_M1 100 100 8 213200.99 0.001 213200.99 False 2024-05-01 02:00:00.000000 169216508 Volatility 75 Index
12 Chaos False 20 2211.736 TIMEFRAME_M2 0 890538270 0 TIMEFRAME_M1 100 100 8 2211.736 0.5 2211.584 False 2024-05-01 02:00:00.000000 122356467 Volatility 25 Index
13 Chaos False 20 6275.654 TIMEFRAME_M2 0 835972740 0 TIMEFRAME_M1 100 100 8 6275.48 0.5 6275.48 False 2024-05-01 02:00:00.000000 151119257 Volatility 10 Index
14 Chaos False 20 6275.654 TIMEFRAME_M2 0 816903676 0 TIMEFRAME_M1 100 100 8 6275.654 0.5 6275.48 False 2024-05-01 02:00:00.000000 129721880 Volatility 10 Index
15 Chaos False 20 214422.41 TIMEFRAME_M2 0 844736060 0 TIMEFRAME_M1 100 100 8 214370.87 0.001 214370.87 False 2024-05-01 02:00:00.000000 164906038 Volatility 75 Index
16 Chaos False 20 1530.52 TIMEFRAME_M2 0 852510195 0 TIMEFRAME_M1 100 100 8 1530.52 0.5 1530.07 False 2024-05-01 03:00:00.000000 151783118 Volatility 100 Index
17 Chaos False 20 2212.057 TIMEFRAME_M2 0 847363912 0 TIMEFRAME_M1 100 100 8 2211.905 0.5 2211.905 False 2024-05-01 03:00:00.000000 138362396 Volatility 25 Index
18 Chaos False 20 6266.259 TIMEFRAME_M2 0 820156416 0 TIMEFRAME_M1 100 100 8 6266.259 0.5 6266.085 False 2024-05-01 03:00:00.000000 164940319 Volatility 10 Index
19 Chaos False 20 2212.057 TIMEFRAME_M2 0 858925801 0 TIMEFRAME_M1 100 100 8 2212.057 0.5 2211.905 False 2024-05-01 03:00:00.000000 116888736 Volatility 25 Index
20 Chaos False 20 1541.23 TIMEFRAME_M2 0 866849933 0 TIMEFRAME_M1 100 100 8 1540.78 0.5 1540.78 False 2024-05-01 03:00:00.000000 144159935 Volatility 100 Index
21 Chaos False 20 214248.02 TIMEFRAME_M2 0 853614811 0 TIMEFRAME_M1 100 100 8 214248.02 0.001 214196.48 False 2024-05-01 03:00:00.000000 184486804 Volatility 75 Index
22 Chaos False 20 2212.057 TIMEFRAME_M2 0 864445967 0 TIMEFRAME_M1 100 100 8 2211.905 0.5 2211.905 False 2024-05-01 03:00:00.000000 193861841 Volatility 25 Index
23 Chaos False 20 214248.02 TIMEFRAME_M2 0 873343446 0 TIMEFRAME_M1 100 100 8 214248.02 0.001 214196.48 False 2024-05-01 03:00:00.000000 112619278 Volatility 75 Index
24 Chaos False 20 6266.259 TIMEFRAME_M2 0 836486112 0 TIMEFRAME_M1 100 100 8 6266.085 0.5 6266.085 False 2024-05-01 04:00:00.000000 154892406 Volatility 10 Index
25 Chaos False 20 1541.23 TIMEFRAME_M2 0 871161343 0 TIMEFRAME_M1 100 100 8 1540.78 0.5 1540.78 False 2024-05-01 04:00:00.000000 174449452 Volatility 100 Index
26 Chaos False 20 2204.2 TIMEFRAME_M2 0 813203733 0 TIMEFRAME_M1 100 100 8 2204.048 0.5 2204.048 False 2024-05-01 04:00:00.000000 179122485 Volatility 25 Index
27 Chaos False 20 6258.229 TIMEFRAME_M2 0 855824654 0 TIMEFRAME_M1 100 100 8 6258.229 0.5 6258.055 False 2024-05-01 04:00:00.000000 127729398 Volatility 10 Index
28 Chaos False 20 214393.69 TIMEFRAME_M2 0 870424059 0 TIMEFRAME_M1 100 100 8 214393.69 0.001 214342.15 False 2024-05-01 04:00:00.000000 163872308 Volatility 75 Index
29 Chaos False 20 1532.57 TIMEFRAME_M2 0 836080689 0 TIMEFRAME_M1 100 100 8 1532.12 0.5 1532.12 False 2024-05-01 04:00:00.000000 148053187 Volatility 100 Index
30 Chaos False 20 1532.57 TIMEFRAME_M2 0 844757802 0 TIMEFRAME_M1 100 100 8 1532.12 0.5 1532.12 False 2024-05-01 04:00:00.000000 164739883 Volatility 100 Index
31 Chaos False 20 214393.69 TIMEFRAME_M2 0 844907343 0 TIMEFRAME_M1 100 100 8 214393.69 0.001 214342.15 False 2024-05-01 04:00:00.000000 128393904 Volatility 75 Index
32 Chaos False 20 2204.2 TIMEFRAME_M2 0 889174320 0 TIMEFRAME_M1 100 100 8 2204.048 0.5 2204.048 False 2024-05-01 04:00:00.000000 114266815 Volatility 25 Index
33 Chaos False 20 6258.229 TIMEFRAME_M2 0 851849681 0 TIMEFRAME_M1 100 100 8 6258.055 0.5 6258.055 False 2024-05-01 04:00:00.000000 176764971 Volatility 10 Index
34 Chaos False 20 2199.649 TIMEFRAME_M2 0 843785198 0 TIMEFRAME_M1 100 100 8 2199.649 0.5 2199.497 False 2024-05-01 05:00:00.000000 185687277 Volatility 25 Index
35 Chaos False 20 1533.0 TIMEFRAME_M2 0 806097447 0 TIMEFRAME_M1 100 100 8 1533.0 0.5 1532.55 False 2024-05-01 05:00:00.000000 180410065 Volatility 100 Index
36 Chaos False 20 214234.49 TIMEFRAME_M2 0 867650998 0 TIMEFRAME_M1 100 100 8 214234.49 0.001 214182.95 False 2024-05-01 05:00:00.000000 156476267 Volatility 75 Index
37 Chaos False 20 6264.311 TIMEFRAME_M2 0 822654546 0 TIMEFRAME_M1 100 100 8 6264.311 0.5 6264.137 False 2024-05-01 05:00:00.000000 161222099 Volatility 10 Index
38 Chaos False 20 6264.311 TIMEFRAME_M2 0 822027320 0 TIMEFRAME_M1 100 100 8 6264.311 0.5 6264.137 False 2024-05-01 06:00:00.000000 159342582 Volatility 10 Index
39 Chaos False 20 214234.49 TIMEFRAME_M2 0 800079192 0 TIMEFRAME_M1 100 100 8 214234.49 0.001 214182.95 False 2024-05-01 06:00:00.000000 126684464 Volatility 75 Index
40 Chaos False 20 1551.9 TIMEFRAME_M2 0 871338447 0 TIMEFRAME_M1 100 100 8 1551.9 0.5 1551.45 False 2024-05-01 06:00:00.000000 193824236 Volatility 100 Index
41 Chaos False 20 2197.204 TIMEFRAME_M2 0 885139336 0 TIMEFRAME_M1 100 100 8 2197.052 0.5 2197.052 False 2024-05-01 06:00:00.000000 167682497 Volatility 25 Index
42 Chaos False 20 6260.308 TIMEFRAME_M2 0 877620534 0 TIMEFRAME_M1 100 100 8 6260.134 0.5 6260.134 False 2024-05-01 06:00:00.000000 108058780 Volatility 10 Index
43 Chaos False 20 1551.9 TIMEFRAME_M2 0 873706466 0 TIMEFRAME_M1 100 100 8 1551.9 0.5 1551.45 False 2024-05-01 07:00:00.000000 171070574 Volatility 100 Index
44 Chaos False 20 213020.43 TIMEFRAME_M2 0 855445602 0 TIMEFRAME_M1 100 100 8 212968.89 0.001 212968.89 False 2024-05-01 07:00:00.000000 191065557 Volatility 75 Index
45 Chaos False 20 2190.008 TIMEFRAME_M2 0 899388418 0 TIMEFRAME_M1 100 100 8 2189.856 0.5 2189.856 False 2024-05-01 07:00:00.000000 189449030 Volatility 25 Index
46 Chaos False 20 6259.793 TIMEFRAME_M2 0 869073467 0 TIMEFRAME_M1 100 100 8 6259.619 0.5 6259.619 False 2024-05-01 07:00:00.000000 173296439 Volatility 10 Index
47 Chaos False 20 2190.008 TIMEFRAME_M2 0 887146622 0 TIMEFRAME_M1 100 100 8 2189.856 0.5 2189.856 False 2024-05-01 07:00:00.000000 199610850 Volatility 25 Index
48 Chaos False 20 214214.09 TIMEFRAME_M2 0 811967805 0 TIMEFRAME_M1 100 100 8 214162.55 0.001 214162.55 False 2024-05-01 07:00:00.000000 170460203 Volatility 75 Index
49 Chaos False 20 1570.68 TIMEFRAME_M2 0 817816770 0 TIMEFRAME_M1 100 100 8 1570.23 0.5 1570.23 False 2024-05-01 07:00:00.000000 154212076 Volatility 100 Index
50 Chaos False 20 214214.09 TIMEFRAME_M2 0 884148623 0 TIMEFRAME_M1 100 100 8 214214.09 0.001 214162.55 False 2024-05-01 07:00:00.000000 100971853 Volatility 75 Index
51 Chaos False 20 1570.68 TIMEFRAME_M2 0 861937441 0 TIMEFRAME_M1 100 100 8 1570.23 0.5 1570.23 False 2024-05-01 07:00:00.000000 140379711 Volatility 100 Index
52 Chaos False 20 6259.793 TIMEFRAME_M2 0 851780777 0 TIMEFRAME_M1 100 100 8 6259.619 0.5 6259.619 False 2024-05-01 08:00:00.000000 104321399 Volatility 10 Index
53 Chaos False 20 2190.008 TIMEFRAME_M2 0 865554473 0 TIMEFRAME_M1 100 100 8 2190.008 0.5 2189.856 False 2024-05-01 08:00:00.000000 113071616 Volatility 25 Index
54 Chaos False 20 2195.456 TIMEFRAME_M2 0 882065437 0 TIMEFRAME_M1 100 100 8 2195.456 0.5 2195.304 False 2024-05-01 08:00:00.000000 175555279 Volatility 25 Index
55 Chaos False 20 213829.91 TIMEFRAME_M2 0 822701548 0 TIMEFRAME_M1 100 100 8 213829.91 0.001 213778.37 False 2024-05-01 08:00:00.000000 163660466 Volatility 75 Index
56 Chaos False 20 1551.23 TIMEFRAME_M2 0 837493772 0 TIMEFRAME_M1 100 100 8 1551.23 0.5 1550.78 False 2024-05-01 08:00:00.000000 184177483 Volatility 100 Index
57 Chaos False 20 6264.7 TIMEFRAME_M2 0 848384485 0 TIMEFRAME_M1 100 100 8 6264.526 0.5 6264.526 False 2024-05-01 08:00:00.000000 109838346 Volatility 10 Index
58 Chaos False 20 6264.7 TIMEFRAME_M2 0 872386905 0 TIMEFRAME_M1 100 100 8 6264.526 0.5 6264.526 False 2024-05-01 08:00:00.000000 170607941 Volatility 10 Index
59 Chaos False 20 2195.456 TIMEFRAME_M2 0 805883016 0 TIMEFRAME_M1 100 100 8 2195.304 0.5 2195.304 False 2024-05-01 09:00:00.000000 146304663 Volatility 25 Index
60 Chaos False 20 1551.23 TIMEFRAME_M2 0 805013163 0 TIMEFRAME_M1 100 100 8 1551.23 0.5 1550.78 False 2024-05-01 09:00:00.000000 163150971 Volatility 100 Index
61 Chaos False 20 213482.63 TIMEFRAME_M2 0 856110839 0 TIMEFRAME_M1 100 100 8 213482.63 0.001 213431.09 False 2024-05-01 09:00:00.000000 197625059 Volatility 75 Index
62 Chaos False 20 2197.637 TIMEFRAME_M2 0 856826096 0 TIMEFRAME_M1 100 100 8 2197.637 0.5 2197.485 False 2024-05-01 09:00:00.000000 121012840 Volatility 25 Index
63 Chaos False 20 1556.55 TIMEFRAME_M2 0 858513739 0 TIMEFRAME_M1 100 100 8 1556.55 0.5 1556.1 False 2024-05-01 09:00:00.000000 171822038 Volatility 100 Index
64 Chaos False 20 213482.63 TIMEFRAME_M2 0 871005991 0 TIMEFRAME_M1 100 100 8 213482.63 0.001 213431.09 False 2024-05-01 09:00:00.000000 164094613 Volatility 75 Index
65 Chaos False 20 6264.3 TIMEFRAME_M2 0 828666719 0 TIMEFRAME_M1 100 100 8 6264.126 0.5 6264.126 False 2024-05-01 09:00:00.000000 189567334 Volatility 10 Index
66 Chaos False 20 213482.63 TIMEFRAME_M2 0 842779615 0 TIMEFRAME_M1 100 100 8 213482.63 0.001 213431.09 False 2024-05-01 09:00:00.000000 180610889 Volatility 75 Index
67 Chaos False 20 6264.3 TIMEFRAME_M2 0 879920558 0 TIMEFRAME_M1 100 100 8 6264.3 0.5 6264.126 False 2024-05-01 09:00:00.000000 118956851 Volatility 10 Index
68 Chaos False 20 1556.55 TIMEFRAME_M2 0 889959635 0 TIMEFRAME_M1 100 100 8 1556.55 0.5 1556.1 False 2024-05-01 09:00:00.000000 133586157 Volatility 100 Index
69 Chaos False 20 2197.637 TIMEFRAME_M2 0 897734980 0 TIMEFRAME_M1 100 100 8 2197.485 0.5 2197.485 False 2024-05-01 10:00:00.000000 197574097 Volatility 25 Index
70 Chaos False 20 2186.164 TIMEFRAME_M2 0 819243808 0 TIMEFRAME_M1 100 100 8 2186.012 0.5 2186.012 False 2024-05-01 10:00:00.000000 134709849 Volatility 25 Index
71 Chaos False 20 6265.107 TIMEFRAME_M2 0 884028760 0 TIMEFRAME_M1 100 100 8 6264.933 0.5 6264.933 False 2024-05-01 10:00:00.000000 132973006 Volatility 10 Index
72 Chaos False 20 210894.16 TIMEFRAME_M2 0 819333305 0 TIMEFRAME_M1 100 100 8 210894.16 0.001 210842.62 False 2024-05-01 10:00:00.000000 198437136 Volatility 75 Index
73 Chaos False 20 1548.61 TIMEFRAME_M2 0 892662359 0 TIMEFRAME_M1 100 100 8 1548.61 0.5 1548.16 False 2024-05-01 10:00:00.000000 181673758 Volatility 100 Index
74 Chaos False 20 210894.16 TIMEFRAME_M2 0 821406374 0 TIMEFRAME_M1 100 100 8 210894.16 0.001 210842.62 False 2024-05-01 11:00:00.000000 136397781 Volatility 75 Index
75 Chaos False 20 2186.164 TIMEFRAME_M2 0 824473751 0 TIMEFRAME_M1 100 100 8 2186.164 0.5 2186.012 False 2024-05-01 11:00:00.000000 187165393 Volatility 25 Index
76 Chaos False 20 1571.51 TIMEFRAME_M2 0 849750456 0 TIMEFRAME_M1 100 100 8 1571.51 0.5 1571.06 False 2024-05-01 11:00:00.000000 146511016 Volatility 100 Index
77 Chaos False 20 6261.79 TIMEFRAME_M2 0 871122005 0 TIMEFRAME_M1 100 100 8 6261.616 0.5 6261.616 False 2024-05-01 11:00:00.000000 170479206 Volatility 10 Index
78 Chaos False 20 6261.79 TIMEFRAME_M2 0 878985962 0 TIMEFRAME_M1 100 100 8 6261.616 0.5 6261.616 False 2024-05-01 11:00:00.000000 111854922 Volatility 10 Index
79 Chaos False 20 213342.62 TIMEFRAME_M2 0 808390587 0 TIMEFRAME_M1 100 100 8 213291.08 0.001 213291.08 False 2024-05-01 12:00:00.000000 187618552 Volatility 75 Index
80 Chaos False 20 1571.51 TIMEFRAME_M2 0 859645359 0 TIMEFRAME_M1 100 100 8 1571.51 0.5 1571.06 False 2024-05-01 12:00:00.000000 174899942 Volatility 100 Index
81 Chaos False 20 2184.36 TIMEFRAME_M2 0 889766108 0 TIMEFRAME_M1 100 100 8 2184.208 0.5 2184.208 False 2024-05-01 12:00:00.000000 181639229 Volatility 25 Index
82 Chaos False 20 211308.28 TIMEFRAME_M2 0 895814254 0 TIMEFRAME_M1 100 100 8 211308.28 0.001 211256.74 False 2024-05-01 12:00:00.000000 147219970 Volatility 75 Index
83 Chaos False 20 2184.36 TIMEFRAME_M2 0 826074130 0 TIMEFRAME_M1 100 100 8 2184.36 0.5 2184.208 False 2024-05-01 12:00:00.000000 173317554 Volatility 25 Index
84 Chaos False 20 1551.57 TIMEFRAME_M2 0 874742078 0 TIMEFRAME_M1 100 100 8 1551.12 0.5 1551.12 False 2024-05-01 12:00:00.000000 110827018 Volatility 100 Index
85 Chaos False 20 6262.48 TIMEFRAME_M2 0 835724910 0 TIMEFRAME_M1 100 100 8 6262.306 0.5 6262.306 False 2024-05-01 12:00:00.000000 133221773 Volatility 10 Index
86 Chaos False 20 1551.57 TIMEFRAME_M2 0 866447363 0 TIMEFRAME_M1 100 100 8 1551.57 0.5 1551.12 False 2024-05-01 12:00:00.000000 131784787 Volatility 100 Index
87 Chaos False 20 6262.48 TIMEFRAME_M2 0 874161936 0 TIMEFRAME_M1 100 100 8 6262.306 0.5 6262.306 False 2024-05-01 13:00:00.000000 116269068 Volatility 10 Index
88 Chaos False 20 211308.28 TIMEFRAME_M2 0 803669555 0 TIMEFRAME_M1 100 100 8 211256.74 0.001 211256.74 False 2024-05-01 13:00:00.000000 196328190 Volatility 75 Index
89 Chaos False 20 2175.088 TIMEFRAME_M2 0 815139691 0 TIMEFRAME_M1 100 100 8 2175.088 0.5 2174.936 False 2024-05-01 13:00:00.000000 163638333 Volatility 25 Index
90 Chaos False 20 1565.71 TIMEFRAME_M2 0 867211000 0 TIMEFRAME_M1 100 100 8 1565.71 0.5 1565.26 False 2024-05-01 13:00:00.000000 144628636 Volatility 100 Index
91 Chaos False 20 2175.088 TIMEFRAME_M2 0 806576041 0 TIMEFRAME_M1 100 100 8 2175.088 0.5 2174.936 False 2024-05-01 13:00:00.000000 107502192 Volatility 25 Index
92 Chaos False 20 6261.929 TIMEFRAME_M2 0 868786283 0 TIMEFRAME_M1 100 100 8 6261.929 0.5 6261.755 False 2024-05-01 13:00:00.000000 185420943 Volatility 10 Index
93 Chaos False 20 211384.64 TIMEFRAME_M2 0 867523434 0 TIMEFRAME_M1 100 100 8 211333.1 0.001 211333.1 False 2024-05-01 13:00:00.000000 125206956 Volatility 75 Index
94 Chaos False 20 6261.929 TIMEFRAME_M2 0 816916727 0 TIMEFRAME_M1 100 100 8 6261.755 0.5 6261.755 False 2024-05-01 13:00:00.000000 173261037 Volatility 10 Index
95 Chaos False 20 211384.64 TIMEFRAME_M2 0 863896740 0 TIMEFRAME_M1 100 100 8 211333.1 0.001 211333.1 False 2024-05-01 13:00:00.000000 128242877 Volatility 75 Index
96 Chaos False 20 1565.71 TIMEFRAME_M2 0 819587790 0 TIMEFRAME_M1 100 100 8 1565.71 0.5 1565.26 False 2024-05-01 13:00:00.000000 134961525 Volatility 100 Index
97 Chaos False 20 2175.088 TIMEFRAME_M2 0 834812760 0 TIMEFRAME_M1 100 100 8 2175.088 0.5 2174.936 False 2024-05-01 14:00:00.000000 145588819 Volatility 25 Index
98 Chaos False 20 1578.53 TIMEFRAME_M2 0 837036352 0 TIMEFRAME_M1 100 100 8 1578.08 0.5 1578.08 False 2024-05-01 14:00:00.000000 192562003 Volatility 100 Index
99 Chaos False 20 6258.246 TIMEFRAME_M2 0 868259743 0 TIMEFRAME_M1 100 100 8 6258.246 0.5 6258.072 False 2024-05-01 14:00:00.000000 160280327 Volatility 10 Index
100 Chaos False 20 208866.34 TIMEFRAME_M2 0 871349145 0 TIMEFRAME_M1 100 100 8 208866.34 0.001 208814.8 False 2024-05-01 14:00:00.000000 101409495 Volatility 75 Index
101 Chaos False 20 2179.785 TIMEFRAME_M2 0 844410053 0 TIMEFRAME_M1 100 100 8 2179.785 0.5 2179.633 False 2024-05-01 14:00:00.000000 137160060 Volatility 25 Index
102 Chaos False 20 208866.34 TIMEFRAME_M2 0 851344138 0 TIMEFRAME_M1 100 100 8 208866.34 0.001 208814.8 False 2024-05-01 14:00:00.000000 123394571 Volatility 75 Index
103 Chaos False 20 2179.785 TIMEFRAME_M2 0 804253642 0 TIMEFRAME_M1 100 100 8 2179.785 0.5 2179.633 False 2024-05-01 14:00:00.000000 118936559 Volatility 25 Index
104 Chaos False 20 1578.53 TIMEFRAME_M2 0 894055545 0 TIMEFRAME_M1 100 100 8 1578.08 0.5 1578.08 False 2024-05-01 15:00:00.000000 102218061 Volatility 100 Index
105 Chaos False 20 6254.581 TIMEFRAME_M2 0 880406162 0 TIMEFRAME_M1 100 100 8 6254.581 0.5 6254.407 False 2024-05-01 15:00:00.000000 173031416 Volatility 10 Index
106 Chaos False 20 6254.581 TIMEFRAME_M2 0 871037679 0 TIMEFRAME_M1 100 100 8 6254.407 0.5 6254.407 False 2024-05-01 15:00:00.000000 161083029 Volatility 10 Index
107 Chaos False 20 209468.3 TIMEFRAME_M2 0 821219140 0 TIMEFRAME_M1 100 100 8 209468.3 0.001 209416.76 False 2024-05-01 15:00:00.000000 110425855 Volatility 75 Index
108 Chaos False 20 2174.784 TIMEFRAME_M2 0 812179023 0 TIMEFRAME_M1 100 100 8 2174.784 0.5 2174.632 False 2024-05-01 15:00:00.000000 158445464 Volatility 25 Index
109 Chaos False 20 1598.74 TIMEFRAME_M2 0 832261318 0 TIMEFRAME_M1 100 100 8 1598.29 0.5 1598.29 False 2024-05-01 15:00:00.000000 158409954 Volatility 100 Index
110 Chaos False 20 1598.74 TIMEFRAME_M2 0 842443741 0 TIMEFRAME_M1 100 100 8 1598.29 0.5 1598.29 False 2024-05-01 15:00:00.000000 148320657 Volatility 100 Index
111 Chaos False 20 2174.784 TIMEFRAME_M2 0 821932525 0 TIMEFRAME_M1 100 100 8 2174.632 0.5 2174.632 False 2024-05-01 16:00:00.000000 191304440 Volatility 25 Index
112 Chaos False 20 209090.97 TIMEFRAME_M2 0 899127463 0 TIMEFRAME_M1 100 100 8 209090.97 0.001 209039.43 False 2024-05-01 16:00:00.000000 169912394 Volatility 75 Index
113 Chaos False 20 6254.581 TIMEFRAME_M2 0 818220824 0 TIMEFRAME_M1 100 100 8 6254.581 0.5 6254.407 False 2024-05-01 16:00:00.000000 118836168 Volatility 10 Index
114 Chaos False 20 6256.754 TIMEFRAME_M2 0 802488375 0 TIMEFRAME_M1 100 100 8 6256.754 0.5 6256.58 False 2024-05-01 16:00:00.000000 136615413 Volatility 10 Index
115 Chaos False 20 209090.97 TIMEFRAME_M2 0 849928315 0 TIMEFRAME_M1 100 100 8 209039.43 0.001 209039.43 False 2024-05-01 16:00:00.000000 102706032 Volatility 75 Index
116 Chaos False 20 2175.301 TIMEFRAME_M2 0 815034759 0 TIMEFRAME_M1 100 100 8 2175.149 0.5 2175.149 False 2024-05-01 16:00:00.000000 144107545 Volatility 25 Index
117 Chaos False 20 1630.55 TIMEFRAME_M2 0 888911969 0 TIMEFRAME_M1 100 100 8 1630.55 0.5 1630.1 False 2024-05-01 16:00:00.000000 109934193 Volatility 100 Index
118 Chaos False 20 209090.97 TIMEFRAME_M2 0 812325147 0 TIMEFRAME_M1 100 100 8 209090.97 0.001 209039.43 False 2024-05-01 16:00:00.000000 140455541 Volatility 75 Index
119 Chaos False 20 2175.301 TIMEFRAME_M2 0 866260404 0 TIMEFRAME_M1 100 100 8 2175.149 0.5 2175.149 False 2024-05-01 16:00:00.000000 125635890 Volatility 25 Index
120 Chaos False 20 1630.55 TIMEFRAME_M2 0 825464245 0 TIMEFRAME_M1 100 100 8 1630.1 0.5 1630.1 False 2024-05-01 17:00:00.000000 171464512 Volatility 100 Index
121 Chaos False 20 6256.754 TIMEFRAME_M2 0 841026179 0 TIMEFRAME_M1 100 100 8 6256.754 0.5 6256.58 False 2024-05-01 17:00:00.000000 120742885 Volatility 10 Index
122 Chaos False 20 1632.52 TIMEFRAME_M2 0 846497225 0 TIMEFRAME_M1 100 100 8 1632.52 0.5 1632.07 False 2024-05-01 17:00:00.000000 128876527 Volatility 100 Index
123 Chaos False 20 211423.72 TIMEFRAME_M2 0 837311963 0 TIMEFRAME_M1 100 100 8 211423.72 0.001 211372.18 False 2024-05-01 17:00:00.000000 126408106 Volatility 75 Index
124 Chaos False 20 6260.409 TIMEFRAME_M2 0 860730063 0 TIMEFRAME_M1 100 100 8 6260.235 0.5 6260.235 False 2024-05-01 17:00:00.000000 138339666 Volatility 10 Index
125 Chaos False 20 2177.192 TIMEFRAME_M2 0 889145564 0 TIMEFRAME_M1 100 100 8 2177.192 0.5 2177.04 False 2024-05-01 17:00:00.000000 140414322 Volatility 25 Index
126 Chaos False 20 2177.192 TIMEFRAME_M2 0 836307418 0 TIMEFRAME_M1 100 100 8 2177.192 0.5 2177.04 False 2024-05-01 17:00:00.000000 184179294 Volatility 25 Index
127 Chaos False 20 1632.52 TIMEFRAME_M2 0 811365730 0 TIMEFRAME_M1 100 100 8 1632.07 0.5 1632.07 False 2024-05-01 17:00:00.000000 164537415 Volatility 100 Index
128 Chaos False 20 6260.409 TIMEFRAME_M2 0 802703670 0 TIMEFRAME_M1 100 100 8 6260.235 0.5 6260.235 False 2024-05-01 17:00:00.000000 122381127 Volatility 10 Index
129 Chaos False 20 211423.72 TIMEFRAME_M2 0 875174652 0 TIMEFRAME_M1 100 100 8 211423.72 0.001 211372.18 False 2024-05-01 17:00:00.000000 129015696 Volatility 75 Index
130 Chaos False 20 209131.24 TIMEFRAME_M2 0 894281854 0 TIMEFRAME_M1 100 100 8 209079.7 0.001 209079.7 False 2024-05-01 18:00:00.000000 199099609 Volatility 75 Index
131 Chaos False 20 1628.45 TIMEFRAME_M2 0 821822575 0 TIMEFRAME_M1 100 100 8 1628.45 0.5 1628.0 False 2024-05-01 18:00:00.000000 167835857 Volatility 100 Index
132 Chaos False 20 2178.522 TIMEFRAME_M2 0 804685075 0 TIMEFRAME_M1 100 100 8 2178.522 0.5 2178.37 False 2024-05-01 18:00:00.000000 104150461 Volatility 25 Index
133 Chaos False 20 6260.906 TIMEFRAME_M2 0 878169391 0 TIMEFRAME_M1 100 100 8 6260.906 0.5 6260.732 False 2024-05-01 18:00:00.000000 170084390 Volatility 10 Index
134 Chaos False 20 6260.906 TIMEFRAME_M2 0 897710204 0 TIMEFRAME_M1 100 100 8 6260.906 0.5 6260.732 False 2024-05-01 18:00:00.000000 109393349 Volatility 10 Index
135 Chaos False 20 2178.522 TIMEFRAME_M2 0 829288385 0 TIMEFRAME_M1 100 100 8 2178.522 0.5 2178.37 False 2024-05-01 18:00:00.000000 199032948 Volatility 25 Index
136 Chaos False 20 1628.45 TIMEFRAME_M2 0 820316612 0 TIMEFRAME_M1 100 100 8 1628.0 0.5 1628.0 False 2024-05-01 18:00:00.000000 137320254 Volatility 100 Index
137 Chaos False 20 209131.24 TIMEFRAME_M2 0 845210213 0 TIMEFRAME_M1 100 100 8 209079.7 0.001 209079.7 False 2024-05-01 18:00:00.000000 103274434 Volatility 75 Index
138 Chaos False 20 1673.81 TIMEFRAME_M2 0 830286560 0 TIMEFRAME_M1 100 100 8 1673.81 0.5 1673.36 False 2024-05-01 19:00:00.000000 187664511 Volatility 100 Index
139 Chaos False 20 6254.249 TIMEFRAME_M2 0 855390499 0 TIMEFRAME_M1 100 100 8 6254.075 0.5 6254.075 False 2024-05-01 19:00:00.000000 193728725 Volatility 10 Index
140 Chaos False 20 208042.57 TIMEFRAME_M2 0 894231567 0 TIMEFRAME_M1 100 100 8 207991.03 0.001 207991.03 False 2024-05-01 19:00:00.000000 194060391 Volatility 75 Index
141 Chaos False 20 2182.66 TIMEFRAME_M2 0 870875379 0 TIMEFRAME_M1 100 100 8 2182.66 0.5 2182.508 False 2024-05-01 19:00:00.000000 116811669 Volatility 25 Index
142 Chaos False 20 6254.249 TIMEFRAME_M2 0 891086013 0 TIMEFRAME_M1 100 100 8 6254.075 0.5 6254.075 False 2024-05-01 19:00:00.000000 105095312 Volatility 10 Index
143 Chaos False 20 2182.66 TIMEFRAME_M2 0 871825138 0 TIMEFRAME_M1 100 100 8 2182.508 0.5 2182.508 False 2024-05-01 19:00:00.000000 111189903 Volatility 25 Index
144 Chaos False 20 1673.81 TIMEFRAME_M2 0 887017267 0 TIMEFRAME_M1 100 100 8 1673.81 0.5 1673.36 False 2024-05-01 19:00:00.000000 153037981 Volatility 100 Index
145 Chaos False 20 208042.57 TIMEFRAME_M2 0 839045519 0 TIMEFRAME_M1 100 100 8 207991.03 0.001 207991.03 False 2024-05-01 20:00:00.000000 150923912 Volatility 75 Index
146 Chaos False 20 208681.37 TIMEFRAME_M2 0 819583624 0 TIMEFRAME_M1 100 100 8 208681.37 0.001 208629.83 False 2024-05-01 20:00:00.000000 188630765 Volatility 75 Index
147 Chaos False 20 6254.646 TIMEFRAME_M2 0 899250913 0 TIMEFRAME_M1 100 100 8 6254.472 0.5 6254.472 False 2024-05-01 20:00:00.000000 192999506 Volatility 10 Index
148 Chaos False 20 2185.591 TIMEFRAME_M2 0 863278517 0 TIMEFRAME_M1 100 100 8 2185.591 0.5 2185.439 False 2024-05-01 20:00:00.000000 130503742 Volatility 25 Index
149 Chaos False 20 1656.13 TIMEFRAME_M2 0 820517786 0 TIMEFRAME_M1 100 100 8 1656.13 0.5 1655.68 False 2024-05-01 20:00:00.000000 188068169 Volatility 100 Index
150 Chaos False 20 1656.13 TIMEFRAME_M2 0 879739555 0 TIMEFRAME_M1 100 100 8 1656.13 0.5 1655.68 False 2024-05-01 20:00:00.000000 111597550 Volatility 100 Index
151 Chaos False 20 2185.591 TIMEFRAME_M2 0 895888927 0 TIMEFRAME_M1 100 100 8 2185.591 0.5 2185.439 False 2024-05-01 20:00:00.000000 147283128 Volatility 25 Index
152 Chaos False 20 208681.37 TIMEFRAME_M2 0 849703279 0 TIMEFRAME_M1 100 100 8 208681.37 0.001 208629.83 False 2024-05-01 20:00:00.000000 198155528 Volatility 75 Index
153 Chaos False 20 6254.646 TIMEFRAME_M2 0 857450318 0 TIMEFRAME_M1 100 100 8 6254.472 0.5 6254.472 False 2024-05-01 20:00:00.000000 116520943 Volatility 10 Index
154 Chaos False 20 6254.884 TIMEFRAME_M2 0 878367571 0 TIMEFRAME_M1 100 100 8 6254.884 0.5 6254.71 False 2024-05-01 21:00:00.000000 104370218 Volatility 10 Index
155 Chaos False 20 2185.689 TIMEFRAME_M2 0 891681576 0 TIMEFRAME_M1 100 100 8 2185.537 0.5 2185.537 False 2024-05-01 21:00:00.000000 160283629 Volatility 25 Index
156 Chaos False 20 206845.33 TIMEFRAME_M2 0 878880656 0 TIMEFRAME_M1 100 100 8 206845.33 0.001 206793.79 False 2024-05-01 21:00:00.000000 157239642 Volatility 75 Index
157 Chaos False 20 1659.26 TIMEFRAME_M2 0 843249470 0 TIMEFRAME_M1 100 100 8 1659.26 0.5 1658.81 False 2024-05-01 21:00:00.000000 195888645 Volatility 100 Index
158 Chaos False 20 1659.26 TIMEFRAME_M2 0 837798992 0 TIMEFRAME_M1 100 100 8 1659.26 0.5 1658.81 False 2024-05-01 21:00:00.000000 183262809 Volatility 100 Index
159 Chaos False 20 2185.689 TIMEFRAME_M2 0 873559425 0 TIMEFRAME_M1 100 100 8 2185.689 0.5 2185.537 False 2024-05-01 21:00:00.000000 114878546 Volatility 25 Index
160 Chaos False 20 206845.33 TIMEFRAME_M2 0 803373551 0 TIMEFRAME_M1 100 100 8 206845.33 0.001 206793.79 False 2024-05-01 21:00:00.000000 140922469 Volatility 75 Index
161 Chaos False 20 6254.884 TIMEFRAME_M2 0 893174131 0 TIMEFRAME_M1 100 100 8 6254.71 0.5 6254.71 False 2024-05-01 22:00:00.000000 198319737 Volatility 10 Index
162 Chaos False 20 6251.351 TIMEFRAME_M2 0 807893174 0 TIMEFRAME_M1 100 100 8 6251.351 0.5 6251.177 False 2024-05-01 22:00:00.000000 135875687 Volatility 10 Index
163 Chaos False 20 2189.993 TIMEFRAME_M2 0 829178053 0 TIMEFRAME_M1 100 100 8 2189.993 0.5 2189.841 False 2024-05-01 22:00:00.000000 151482337 Volatility 25 Index
164 Chaos False 20 206447.56 TIMEFRAME_M2 0 876904701 0 TIMEFRAME_M1 100 100 8 206396.02 0.001 206396.02 False 2024-05-01 22:00:00.000000 157587894 Volatility 75 Index
165 Chaos False 20 1626.37 TIMEFRAME_M2 0 843626687 0 TIMEFRAME_M1 100 100 8 1625.92 0.5 1625.92 False 2024-05-01 22:00:00.000000 195164579 Volatility 100 Index
166 Chaos False 20 206447.56 TIMEFRAME_M2 0 879242952 0 TIMEFRAME_M1 100 100 8 206396.02 0.001 206396.02 False 2024-05-01 22:00:00.000000 156081780 Volatility 75 Index
167 Chaos False 20 1626.37 TIMEFRAME_M2 0 860168201 0 TIMEFRAME_M1 100 100 8 1625.92 0.5 1625.92 False 2024-05-01 22:00:00.000000 149723319 Volatility 100 Index
168 Chaos False 20 6251.351 TIMEFRAME_M2 0 875897222 0 TIMEFRAME_M1 100 100 8 6251.351 0.5 6251.177 False 2024-05-01 22:00:00.000000 181975920 Volatility 10 Index
169 Chaos False 20 2189.993 TIMEFRAME_M2 0 843022095 0 TIMEFRAME_M1 100 100 8 2189.841 0.5 2189.841 False 2024-05-01 22:00:00.000000 176917055 Volatility 25 Index
170 Chaos False 20 1635.15 TIMEFRAME_M2 0 839471806 0 TIMEFRAME_M1 100 100 8 1635.15 0.5 1634.7 False 2024-05-01 23:00:00.000000 139746036 Volatility 100 Index
171 Chaos False 20 205355.18 TIMEFRAME_M2 0 899076458 0 TIMEFRAME_M1 100 100 8 205303.64 0.001 205303.64 False 2024-05-01 23:00:00.000000 194980537 Volatility 75 Index
172 Chaos False 20 2183.635 TIMEFRAME_M2 0 848731357 0 TIMEFRAME_M1 100 100 8 2183.483 0.5 2183.483 False 2024-05-01 23:00:00.000000 199898987 Volatility 25 Index
173 Chaos False 20 6254.688 TIMEFRAME_M2 0 896618061 0 TIMEFRAME_M1 100 100 8 6254.514 0.5 6254.514 False 2024-05-01 23:00:00.000000 157000097 Volatility 10 Index
174 Chaos False 20 6254.688 TIMEFRAME_M2 0 884931917 0 TIMEFRAME_M1 100 100 8 6254.688 0.5 6254.514 False 2024-05-01 23:00:00.000000 137085470 Volatility 10 Index
175 Chaos False 20 1635.15 TIMEFRAME_M2 0 878294418 0 TIMEFRAME_M1 100 100 8 1635.15 0.5 1634.7 False 2024-05-01 23:00:00.000000 130821199 Volatility 100 Index
176 Chaos False 20 205355.18 TIMEFRAME_M2 0 822383277 0 TIMEFRAME_M1 100 100 8 205355.18 0.001 205303.64 False 2024-05-01 23:00:00.000000 107811481 Volatility 75 Index
177 Chaos False 20 2183.635 TIMEFRAME_M2 0 886310952 0 TIMEFRAME_M1 100 100 8 2183.635 0.5 2183.483 False 2024-05-01 23:00:00.000000 137929296 Volatility 25 Index