### Run Live Tutorial App

Source: https://pypi.org/project/eptr2

Start the live tutorial Streamlit app for eptr2. Requires Streamlit to be installed. Provide your username and password.

```python
from eptr2.tutorials import run_demo_app

run_demo_app(username="YOUR_USERNAME",password="YOUR_PASSWORD")
```

--------------------------------

### Install eptr2 with uv

Source: https://pypi.org/project/eptr2

Install the base eptr2 package using the 'uv' package installer.

```bash
uv pip install eptr2
```

--------------------------------

### Install eptr2 with uv and extras

Source: https://pypi.org/project/eptr2

Install the eptr2 package with extras using the 'uv' package installer.

```bash
uv pip install "eptr2[allextras]"
```

--------------------------------

### Install eptr2 from PyPI

Source: https://pypi.org/project/eptr2

Install the base eptr2 package from the Python Package Index.

```bash
pip install eptr2
```

--------------------------------

### Install eptr2 with all extras

Source: https://pypi.org/project/eptr2

Install the eptr2 package including additional features like pandas and streamlit support, as well as MCP server capabilities for AI integration.

```bash
pip install "eptr2[allextras]"
```

--------------------------------

### Example .env file content

Source: https://pypi.org/project/eptr2

A sample .env file format for storing EPIAS Transparency Platform credentials. Place this file in the same directory as your script.

```dotenv
EPTR_USERNAME=youremail@something.com
EPTR_PASSWORD=yourpassword

```

--------------------------------

### Configure .env for MCP Server

Source: https://pypi.org/project/eptr2

Example of a .env file for configuring eptr2 MCP server credentials.

```dotenv
EPTR_USERNAME=your.email@example.com
EPTR_PASSWORD=yourpassword
```

--------------------------------

### Run eptr2 MCP Server

Source: https://pypi.org/project/eptr2

Start the Model Context Protocol (MCP) server for AI agent integration using the command-line interface.

```bash
eptr2-mcp-server
```

--------------------------------

### Call Service Using Alias

Source: https://pypi.org/project/eptr2

Use predefined aliases to call services. 'ptf' is an example alias for 'mcp'.

```python
res = eptr.call("ptf", start_date="2024-07-29", end_date="2024-07-29")
```

--------------------------------

### Run eptr2 MCP Server Programmatically

Source: https://pypi.org/project/eptr2

Programmatically start the eptr2 MCP server using asyncio. Supports loading credentials from environment variables and recycling TGT.

```python
from eptr2.mcp import run_mcp_server
import asyncio

asyncio.run(run_mcp_server(use_dotenv=True, recycle_tgt=True))
```

--------------------------------

### Get Aliases and Available Calls

Source: https://pypi.org/project/eptr2

Retrieve all available aliases, optionally including custom ones, and list available calls, optionally including aliases.

```python
eptr.get_aliases(include_custom_aliases = True)
```

```python
eptr.get_available_calls(include_aliases = True)
```

--------------------------------

### Get Hourly Price and Cost Data

Source: https://pypi.org/project/eptr2

Retrieve a dataframe combining MCP, SMP, and optionally WAP, along with associated imbalance and KUPST costs.

```python
from eptr2 import EPTR2
from eptr2.composite import get_hourly_price_and_cost_data, get_imbalance_data

eptr = EPTR2(username="YOUR_USERNAME",password="YOUR_PASSWORD")
df_cost = get_hourly_price_and_cost_data(eptr, start_date="2024-07-29", end_date="2024-07-29")
print(df_cost)
df_imbalance = get_imbalance_data(eptr, start_date="2024-07-29", end_date="2024-07-29")
print(df_imbalance)
```

--------------------------------

### Get Hourly Consumption and Forecast Data

Source: https://pypi.org/project/eptr2

Retrieve a combined dataframe of Load Plan, UECM, and Real Time Consumption data for a specified date range.

```python
from eptr2 import EPTR2
from eptr2.composite import get_hourly_consumption_and_forecast_data

eptr = EPTR2(username="YOUR_USERNAME",password="YOUR_PASSWORD")
df = get_hourly_consumption_and_forecast_data(eptr, start_date="2024-07-29", end_date="2024-07-29")
print(df)
```

--------------------------------

### Get Hourly Production Data

Source: https://pypi.org/project/eptr2

Retrieve actual production data (real time, UEVM) for specific production plant IDs or totals if IDs are omitted. Includes verbose logging.

```python
from eptr2 import EPTR2
from eptr2.composite import wrapper_hourly_production_plan_and_realized, get_hourly_production_data, get_hourly_production_plan_data

eptr = EPTR2(username="YOUR_USERNAME",password="YOUR_PASSWORD")

actual_df = get_hourly_production_data(
    eptr=eptr,
    start_date="2024-11-01",
    end_date="2024-11-01",
    rt_pp_id=641,  ## ATATÜRK HES
    uevm_pp_id=142,  ## ATATÜRK HES
    verbose=True,
)


plan_df = get_hourly_production_plan_data(
    eptr=eptr,
    start_date="2024-11-01",
    end_date="2024-11-01",
    org_id=195, ## EÜAŞ
    uevcb_id=3525325, ## ATATÜRK HES
    verbose=True,
)

wrap_df = wrapper_hourly_production_plan_and_realized(
        eptr=eptr, start_date="2024-11-01", end_date="2024-11-01", verbose=True
    )
```

--------------------------------

### Get Intraday Market (IDM) Logs

Source: https://pypi.org/project/eptr2

Retrieve Intraday Market (IDM) logs and their details for a specified period. Uses a credentials file for authentication.

```python
from eptr2 import EPTR2
from eptr2.composite import idm_log_longer, idm_log_period

eptr = EPTR2(credentials_file_path="creds/eptr_credentials.json")

idm_log_longer(eptr=eptr, start_date="2023-01-01", end_date="2023-01-31", verbose=True)
idm_log_period(eptr=eptr, period="2023-01-01", verbose=True)
```

--------------------------------

### Get Day Ahead and Bilateral Trade Data

Source: https://pypi.org/project/eptr2

Retrieves combined data for day-ahead and bilateral trades within a specified date range. Includes contract symbol information.

```python
from eptr2 import EPTR2
from eptr2.composite import get_day_ahead_and_bilateral_matches, get_day_ahead_detail_info

eptr = EPTR2(credentials_file_path="creds/eptr_credentials.json")

df = get_day_ahead_and_bilateral_matches(eptr=eptr,start_date="2023-01-01", end_date="2023-01-31", verbose=True, include_contract_symbol=True)

df2 = get_day_ahead_detail_info(
    eptr=eptr, start_date="2023-01-01", end_date="2023-01-31", verbose=True
)
```

--------------------------------

### Get Balancing Power Market Data

Source: https://pypi.org/project/eptr2

Fetches data for the Balancing Power Market, supporting both range queries and specific period lookups. Requires specifying the EPTR2 client and date parameters.

```python
from eptr2 import EPTR2
from eptr2.composite import get_bpm_period, get_bpm_range

eptr = EPTR2(credentials_file_path="creds/eptr_credentials.json")
start_date = "2025-05-01"
end_date = "2025-05-31"
df1 = get_bpm_range(
    eptr=eptr, start_date=start_date, end_date=end_date, verbose=True
)

period = "2025-05-01"  # Example period
df2 = get_bpm_period(
    period=period, eptr=eptr, max_lives=2, verbose=True, strict=True
)
```

--------------------------------

### Run Calculator Tutorial App

Source: https://pypi.org/project/eptr2

Launch the calculator tutorial app to estimate imbalance and KÜPST costs. Accepts custom actual and forecast values for any date and hour.

```python
from eptr2.tutorials import run_calc_app

run_calc_app(username="YOUR_USERNAME",password="YOUR_PASSWORD")
```

--------------------------------

### Initialize EPTR2 with TGT Wrapper

Source: https://pypi.org/project/eptr2

Create an EPTR2 object using the new login method that automatically handles TGT management. The credentials path can be specified.

```python
from eptr2 import eptr_w_tgt_wrapper

eptr = eptr_w_tgt_wrapper()
```

--------------------------------

### Calculate Plant Costs

Source: https://pypi.org/project/eptr2

Gathers and calculates plant costs, requiring specific plant, organization, and UEVBC IDs along with plant type and data sources for forecasts and actuals. Ensure credentials are set up.

```python
from eptr2 import EPTR2
from eptr2.composite import gather_and_calculate_plant_costs

eptr = EPTR2(credentials_file_path="creds/eptr_credentials.json")

df = gather_and_calculate_plant_costs(
    eptr=eptr,
    start_date="2023-01-01",
    end_date="2023-01-31",
    pp_id=120,  ## BOZCAADA RES
    org_id=195,  ## EÜAŞ
    uevcb_id=3204384,  ## BOZCAADA RES
    plant_type="wind",
    verbose=True,
    forecast_source = "kgup",
    actual_source = "uevm"
)
```

--------------------------------

### Create and Use Custom Aliases

Source: https://pypi.org/project/eptr2

Define custom aliases for service calls by preparing an alias dictionary and passing it during EPTR2 object initialization.

```python
custom_aliases = {"market-clearing-price": "mcp", "system-marginal-price": "smp"}

eptr = EPTR2(username="YOUR_USERNAME",password="YOUR_PASSWORD", custom_aliases=custom_aliases)
```

--------------------------------

### Bulk Function Calls for Daily Operations

Source: https://pypi.org/project/eptr2

Performs bulk data retrieval for Daily Production Plan (DPP/KGÜP), Real Time Generation, and UEVBC lists for a specified date. Requires the EPTR2 client and relevant IDs.

```python
### DPP / KGÜP bulk
dpp_df = eptr.call("dpp-bulk", date="2025-08-31", uevcb_ids=[3208611, 723724, 335505, 106710, 4094])
### Real Time Generation bulk
rt_gen_df = eptr.call("rt-gen-bulk", date="2025-08-31", pp_ids=[11162, 17889, 605, 5005121, 20764])
### UEVCB list bulk
uevcb_df = eptr.call("uevcb-list-bulk", date="2025-08-31", org_ids=[166, 12297, 648, 19880, 162])
```

--------------------------------

### Bulk Function Calls

Source: https://pypi.org/project/eptr2

Provides three bulk API endpoints for daily operations: DPP/KGÜP, Real Time Generation, and UEVCB list. These functions allow for efficient retrieval of multiple data points for a given date.

```APIDOC
## Bulk Function Calls

### Description
Provides three bulk API endpoints for daily operations: DPP/KGÜP, Real Time Generation, and UEVCB list. These functions allow for efficient retrieval of multiple data points for a given date.

### Endpoints
- `dpp-bulk`: Retrieves daily production plan data.
- `rt-gen-bulk`: Retrieves real-time generation data.
- `uevcb-list-bulk`: Retrieves a list of UEVCB information.

### Parameters
- `date` (str): The date for which to retrieve data (YYYY-MM-DD).
- `uevcb_ids` (list[int], optional): A list of UEVCEB IDs for filtering.
- `pp_ids` (list[int], optional): A list of plant power IDs for filtering.
- `org_ids` (list[int], optional): A list of organization IDs for filtering.

### Example Usage
```python
# Assuming 'eptr' is an initialized EPTR2 object

# DPP / KGÜP bulk
dpp_df = eptr.call("dpp-bulk", date="2025-08-31", uevcb_ids=[3208611, 723724, 335505, 106710, 4094])

# Real Time Generation bulk
rt_gen_df = eptr.call("rt-gen-bulk", date="2025-08-31", pp_ids=[11162, 17889, 605, 5005121, 20764])

# UEVCB list bulk
uevcb_df = eptr.call("uevcb-list-bulk", date="2025-08-31", org_ids=[166, 12297, 648, 19880, 162])
```
```

--------------------------------

### Configure Claude Desktop for eptr2 MCP Server

Source: https://pypi.org/project/eptr2

Add this configuration to your Claude Desktop config file to integrate with the eptr2 MCP server.

```json
{
  "mcpServers": {
    "eptr2": {
      "command": "eptr2-mcp-server",
      "env": {
        "EPTR_USERNAME": "your.email@example.com",
        "EPTR_PASSWORD": "yourpassword"
      }
    }
  }
}
```

--------------------------------

### Use .env file for credentials and TGT recycling

Source: https://pypi.org/project/eptr2

Configure the EPTR2 client to use a .env file for credentials and enable Ticket Granting Ticket (TGT) recycling for automatic TGT management. This avoids manual credential handling and potential throttling from frequent TGT creation.

```python
from eptr2 import EPTR2

eptr = EPTR2(
    use_dotenv=True,  ## Default: True
    recycle_tgt=True, ## Default: False
    dotenv_path=".env" ## Default: ".env"
    tgt_path="." ## Default: ".", included as a kwarg
    )

df = eptr.call("mcp", start_date="2025-08-01",end_date="2025-08-31")

```

--------------------------------

### Generate eptr2 Credentials File

Source: https://pypi.org/project/eptr2

Use this function to create a credentials file for eptr2. The default path is 'creds/eptr_credentials.json', but it can be customized.

```python
from eptr2 import generate_eptr2_credentials_file

generate_eptr2_credentials_file(
    username="YOUR_USERNAME",
    password="YOUR_PASSWORD"
)
```

--------------------------------

### Day Ahead and Bilateral Trade Data

Source: https://pypi.org/project/eptr2

Retrieves day-ahead and bilateral trade data for a specified date range. The `get_day_ahead_detail_info` function provides detailed information, while `get_day_ahead_and_bilateral_matches` offers matched data, with an option to include contract symbols.

```APIDOC
## Day Ahead and Bilateral Trade Data

### Description
Retrieves day-ahead and bilateral trade data for a specified date range. The `get_day_ahead_detail_info` function provides detailed information, while `get_day_ahead_and_bilateral_matches` offers matched data, with an option to include contract symbols.

### Functions
- `get_day_ahead_and_bilateral_matches(eptr, start_date, end_date, verbose=False, include_contract_symbol=False)`
- `get_day_ahead_detail_info(eptr, start_date, end_date, verbose=False)`

### Parameters
- `eptr`: An initialized EPTR2 object.
- `start_date` (str): The start date for the data retrieval (YYYY-MM-DD).
- `end_date` (str): The end date for the data retrieval (YYYY-MM-DD).
- `verbose` (bool, optional): If True, prints progress information. Defaults to False.
- `include_contract_symbol` (bool, optional): If True, includes contract symbols in the output. Defaults to False.

### Example Usage
```python
from eptr2 import EPTR2
from eptr2.composite import get_day_ahead_and_bilateral_matches, get_day_ahead_detail_info

eptr = EPTR2(credentials_file_path="creds/eptr_credentials.json")

df = get_day_ahead_and_bilateral_matches(eptr=eptr, start_date="2023-01-01", end_date="2023-01-31", verbose=True, include_contract_symbol=True)

df2 = get_day_ahead_detail_info(eptr=eptr, start_date="2023-01-01", end_date="2023-01-31", verbose=True)
```
```

--------------------------------

### Plant Costs Calculation

Source: https://pypi.org/project/eptr2

Gathers and calculates plant costs based on provided parameters including date range, plant ID, organization ID, UEVCEB ID, plant type, and forecast/actual data sources.

```APIDOC
## Plant Costs Calculation

### Description
Gathers and calculates plant costs based on provided parameters including date range, plant ID, organization ID, UEVCEB ID, plant type, and forecast/actual data sources.

### Function
- `gather_and_calculate_plant_costs(eptr, start_date, end_date, pp_id, org_id, uevcb_id, plant_type, verbose=False, forecast_source=None, actual_source=None)`

### Parameters
- `eptr`: An initialized EPTR2 object.
- `start_date` (str): The start date for the calculation (YYYY-MM-DD).
- `end_date` (str): The end date for the calculation (YYYY-MM-DD).
- `pp_id` (int): The plant power ID.
- `org_id` (int): The organization ID.
- `uevcb_id` (int): The UEVCEB ID.
- `plant_type` (str): The type of the plant (e.g., "wind").
- `verbose` (bool, optional): If True, prints progress information. Defaults to False.
- `forecast_source` (str, optional): The source for forecast data (e.g., "kgup"). Defaults to None.
- `actual_source` (str, optional): The source for actual data (e.g., "uevm"). Defaults to None.

### Example Usage
```python
from eptr2 import EPTR2
from eptr2.composite import gather_and_calculate_plant_costs

eptr = EPTR2(credentials_file_path="creds/eptr_credentials.json")

df = gather_and_calculate_plant_costs(
    eptr=eptr,
    start_date="2023-01-01",
    end_date="2023-01-31",
    pp_id=120,  ## BOZCAADA RES
    org_id=195,  ## EÜAŞ
    uevcb_id=3204384,  ## BOZCAADA RES
    plant_type="wind",
    verbose=True,
    forecast_source = "kgup",
    actual_source = "uevm"
)
```
```

--------------------------------

### Balancing Power Market Data

Source: https://pypi.org/project/eptr2

Fetches data from the Balancing Power Market. `get_bpm_range` retrieves data over a date range, while `get_bpm_period` fetches data for a specific period with options for maximum lives and strictness.

```APIDOC
## Balancing Power Market Data

### Description
Fetches data from the Balancing Power Market. `get_bpm_range` retrieves data over a date range, while `get_bpm_period` fetches data for a specific period with options for maximum lives and strictness.

### Functions
- `get_bpm_range(eptr, start_date, end_date, verbose=False)`
- `get_bpm_period(period, eptr, max_lives=None, verbose=False, strict=False)`

### Parameters
- `eptr`: An initialized EPTR2 object.
- `start_date` (str): The start date for the data retrieval (YYYY-MM-DD).
- `end_date` (str): The end date for the data retrieval (YYYY-MM-DD).
- `period` (str): The specific period for data retrieval (YYYY-MM-DD).
- `max_lives` (int, optional): Maximum number of lives to consider. Defaults to None.
- `verbose` (bool, optional): If True, prints progress information. Defaults to False.
- `strict` (bool, optional): If True, enforces strict data validation. Defaults to False.

### Example Usage
```python
from eptr2 import EPTR2
from eptr2.composite import get_bpm_period, get_bpm_range

eptr = EPTR2(credentials_file_path="creds/eptr_credentials.json")
start_date = "2025-05-01"
end_date = "2025-05-31"
df1 = get_bpm_range(eptr=eptr, start_date=start_date, end_date=end_date, verbose=True)

period = "2025-05-01"  # Example period
df2 = get_bpm_period(period=period, eptr=eptr, max_lives=2, verbose=True, strict=True)
```
```

--------------------------------

### Call Market Clearing Price (MCP) API

Source: https://pypi.org/project/eptr2

Instantiate the EPTR2 client with username and password, then call the 'mcp' service to retrieve Market Clearing Price data for a specific date.

```python
from eptr2 import EPTR2

eptr = EPTR2(
    username="YOUR_USERNAME", password="YOUR_PASSWORD"
)

res = eptr.call("mcp", start_date="2024-07-29", end_date="2024-07-29")

```

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