# PMM Scripts (DEPRECATED)¶

Snippets of Python code that let users customize the Pure Market Making strategy.

Warning

PMM Scripts were an early experiment to let users customize Hummingbot, but it can only be used with the PMM strategy. In the 1.4.0 release, we introduced a generalized form of Scripts

## How it works¶

After configured, the PMMScript will start automatically once the Pure Market Making strategy starts and stops when the strategy stops. A PMMScript is run on a new dedicated process, in case where the script fails or has a bug, your main Hummingbot application can still function.

1. Create a new script file, you can see examples in the Examples section below, and save it into the /pmm_scripts folder

• Inside Hummingbot run command config pmm_script_mode and/or config pmm_script_mode.pmm_script_file_path.
• Editing the conf_client.yml file located inside the hummingbot_conf folder using a text editor.

pmm_script_enabled: true

3. Start running a strategy

Note

In past versions of Hummingbot (1.5.0 and below), the conf_client.yml file is named conf_global.yml

## Examples¶

The following examples can be found in the /pmm_scripts folder:

### hello_world_script.py¶

The most basic example only a few lines of code.

### ping_pong_script.py¶

Replicates our current ping pong strategy using script.

### price_band_script.py¶

Replicates our current price band strategy using script.

### dynamic_price_band_script.py¶

Demonstrates how to set the band around mid price moving average, the band moves as the average moves.

### script_template.py¶

Provides you a base template to start using the scripts functions.

## PMMScriptBase class¶

PMMScriptBase is the base class for PMM Scripts.

At every tick, the script gets current market price (mid_price), strategy configuration (pmm_parameters) and total balances (all_total_balances). The mid_price is stored in a list (mid_prices) where a new mid_price is added to the end of the list, whereas strategy configuration and total balances are replaced every time.

### pmm_parameters¶

To set a pure market making strategy parameter to a new value, simply assign a new value to it.

Usage Example: self.pmm_parameters.bid_spread = Decimal("0.03") - to update bid spread to 3%

These below are configurable parameters:

• buy_levels (a number of buy orders to place, initially set to order_levels when the strategy starts)
• sell_levels (a number of sell orders to place, initially set to order_levels when the strategy starts)
• order_levels
• order_amount
• order_level_amount
• order_refresh_time
• order_refresh_tolerance_pct
• filled_order_delay
• hanging_orders_enabled
• hanging_orders_cancel_pct

### Events¶

#### on_tick¶

The code here will be executed on every tick which is every second on a default Hummingbot configuration.

#### on_buy_order_completed¶

The script will be notified every time a buy order of yours is fully filled. Put in your code logic here to handle such situation if needed.

#### on_sell_order_completed¶

The script will be notified every time a sell order of yours is fully filled. Put in your code logic here to handle such situation if needed.

#### on_status¶

This is called upon status command issued on the Hummingbot application. You can provide your custom status message here.

### Functions¶

#### notify¶

Notifies the user, the message will appear on top left panel of HB application. If Telegram integration enabled, the message will also be sent to the telegram user.

Usage Example: self.notify("Hello world")

#### log¶

Logs message to the strategy log file and display it on Running Logs section of HB.

Usage Example: self.log("Hello world")

#### avg_mid_price¶

Calculates average (mean) of the stored mid prices.

Usage Example: avg_value = self.avg_mid_price(60, 30) - to calculate average mid price at a minute interval for the last 30 minutes

#### avg_price_volatility¶

Calculates average (mean) price volatility, volatility is a price change compared to the previous cycle regardless of its direction, e.g. if price changes -3% (or 3%), the volatility is 3%.

Usage Example: avg_value = self.avg_price_volatility(60, 30) - to calculate average price volatility at a minute interval for the last 30 minutes

#### median_price_volatility¶

Calculates median (middle value) price volatility.

Usage Example: median_value = self.median_price_volatility(60, 30) - to calculate median price volatility at a minute interval for the last 30 minutes

#### locate_central_price_volatility¶

Calculates central located price volatility based on a given mean function. The mean function can be one that is supported by statistics library e.g. mean, median, geometric_mean and many more.

Usage Example: median_value = self.locate_central_price_volatility(60, 30, median) - to calculate median price volatility at a minute interval for the last 30 minutes

##### round_by_step¶

Rounds a given number down by a given step size.

Usage Example: rounded_value = self.round_by_step(1.8, 0.25) will give you 1.75

##### take_samples¶

Takes samples out of a given list where the last item is the most recent. Example List a_list = [1, 2, 3, 4, 5, 6, 7]

Usage Example: samples = self.take_samples(a_list, 3, 2) will give you [4, 7]