### Install pytickersymbols Library

Source: https://github.com/portfolioplus/pytickersymbols/blob/master/README.md

This command installs the pytickersymbols library using pip, making it available for use in Python projects. Ensure pip3 is available on your system.

```shell
pip3 install pytickersymbols
```

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

### Get All Countries

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieve a list of all countries represented in the stock database. This allows filtering stocks by their country of origin.

```APIDOC
## Get All Countries

### Description
Retrieve a list of all countries represented in the stock database. This allows filtering stocks by their country of origin.

### Method
GET

### Endpoint
N/A (Method call on PyTickerSymbols instance)

### Parameters
None

### Request Example
```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()
countries = stock_data.get_all_countries()

print("Countries with stocks:", countries)
# Output: ['Germany', 'United States', 'United Kingdom', 'France',
#          'Netherlands', 'Belgium', 'Spain', 'Finland', 'Sweden',
#          'Switzerland', 'Russia', 'Ireland', 'Israel', ...]
```

### Response
#### Success Response (200)
- **countries** (list of strings) - A list containing the names of all countries with stocks in the database.
```

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

### Get All Industries

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieve a list of all industry classifications used in the stock database. This enables filtering stocks by their industry.

```APIDOC
## Get All Industries

### Description
Retrieve a list of all industry classifications used in the stock database. This enables filtering stocks by their industry.

### Method
GET

### Endpoint
N/A (Method call on PyTickerSymbols instance)

### Parameters
None

### Request Example
```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()
industries = stock_data.get_all_industries()

print(f"Total industries: {len(industries)}")
# Output: Total industries: 50+

print("Sample industries:", industries[:10])
# Output: ['Computer Hardware', 'Gold', 'Banking Services', 'Footwear',
#          'Basic Materials', 'Pharmaceuticals', 'Oil & Gas', ...]
```

### Response
#### Success Response (200)
- **industries** (list of strings) - A list containing the names of all industry classifications.
```

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

### Get Stocks by Index

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieve all stocks belonging to a specific index, along with their complete metadata. Stocks can be filtered by index name.

```APIDOC
## Get Stocks by Index

### Description
Retrieve all stocks belonging to a specific index, along with their complete metadata. Stocks can be filtered by index name.

### Method
GET

### Endpoint
N/A (Method call on PyTickerSymbols instance)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get all DAX stocks
dax_stocks = list(stock_data.get_stocks_by_index('DAX'))
print(f"DAX has {len(dax_stocks)} stocks")
# Output: DAX has 40 stocks

# Access detailed stock information
for stock in dax_stocks[:2]:
    print(f"Name: {stock['name']}")
    print(f"Country: {stock['country']}")
    print(f"Industries: {stock['industries']}")
    print(f"Symbols: {stock['symbols']}")
    print(f"Metadata: {stock.get('metadata', {})}")
    print("---")

# Output example:
# Name: adidas AG
# Country: Germany
# Industries: ['Footwear']
# Symbols: [{'yahoo': 'ADS.F', 'google': 'FRA:ADS'}]
# Metadata: {'founded': 1949, 'employees': 57016}

# Get stocks from other indices
nasdaq_stocks = list(stock_data.get_stocks_by_index('NASDAQ 100'))
sp500_stocks = list(stock_data.get_stocks_by_index('S&P 500'))
ftse_stocks = list(stock_data.get_stocks_by_index('FTSE 100'))
```

### Response
#### Success Response (200)
- **stocks** (list of dictionaries) - A list where each dictionary represents a stock and contains fields like 'name', 'country', 'industries', 'symbols', and 'metadata'.
```

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

### Get All Countries, Indices, and Industries with pytickersymbols

Source: https://github.com/portfolioplus/pytickersymbols/blob/master/README.md

Demonstrates how to initialize the PyTickerSymbols class and retrieve lists of all available countries, stock indices, and industries supported by the library. This is a foundational step for further data retrieval.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()
countries = stock_data.get_all_countries()
indices = stock_data.get_all_indices()
industries = stock_data.get_all_industries()
```

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

### Get All Indices

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieve a list of all available stock market indices supported by the library. This includes major indices from Europe, North America, and Russia.

```APIDOC
## Get All Indices

### Description
Retrieve a list of all available stock market indices supported by the library. This includes major indices from Europe, North America, and Russia.

### Method
GET

### Endpoint
N/A (Method call on PyTickerSymbols instance)

### Parameters
None

### Request Example
```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()
indices = stock_data.get_all_indices()

print(f"Total indices: {len(indices)}")
# Output: Total indices: 17

print("Available indices:", indices)
# Output: ['DAX', 'SDAX', 'MDAX', 'TECDAX', 'DOW JONES', 'NASDAQ 100',
#          'S&P 100', 'S&P 500', 'FTSE 100', 'CAC 40', 'AEX', 'BEL 20',
#          'IBEX 35', 'OMX Helsinki 25', 'OMX Stockholm 30', 'Switzerland 20', 'MOEX']
```

### Response
#### Success Response (200)
- **indices** (list of strings) - A list containing the names of all available stock market indices.
```

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

### Get All Stocks and Analyze Metadata

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

This snippet shows how to retrieve the entire database of stocks, including their full metadata. It demonstrates iterating through stocks to gather information on countries, industries, and indices, and identifies stocks with multiple trading symbols. It also prints detailed information for a sample stock.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get all stocks
all_stocks = stock_data.get_all_stocks()
print(f"Total stocks in database: {len(all_stocks)}")
# Output: Total stocks in database: 900+

# Analyze stock data
countries = set()
industries = set()
indices = set()

for stock in all_stocks[:100]:  # Sample first 100
    countries.add(stock['country'])
    industries.update(stock['industries'])
    indices.update(stock['indices'])

print(f"Countries represented: {len(countries)}")
print(f"Industries covered: {len(industries)}")
print(f"Indices included: {len(indices)}")

# Find stocks with multiple symbols
multi_symbol_stocks = [
    stock for stock in all_stocks
    if len(stock['symbols']) > 1
]
print(f"Stocks with multiple symbols: {len(multi_symbol_stocks)}")

# Display a sample stock with full details
sample = all_stocks[0]
print(f"\nSample stock: {sample['name']}")
print(f"  Symbol: {sample['symbol']}")
print(f"  Country: {sample['country']}")
print(f"  Indices: {', '.join(sample['indices'])}")
print(f"  Industries: {', '.join(sample['industries'])}")
print(f"  Ticker symbols: {sample['symbols']}")
if 'metadata' in sample:
    print(f"  Founded: {sample['metadata'].get('founded', 'N/A')}")
    print(f"  Employees: {sample['metadata'].get('employees', 'N/A')}")
```

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

### Get Stock by Google Symbol using Python

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieves complete stock information using a Google Finance ticker symbol. Requires the pytickersymbols library. Takes a Google symbol string as input and returns a dictionary containing stock details or None if not found.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get stock by Google symbol
adidas = stock_data.get_stock_by_google_symbol('FRA:ADS')

if adidas:
    print(f"Name: {adidas['name']}")
    print(f"Country: {adidas['country']}")
    print(f"All symbols: {adidas['symbols']}")

# Output:
# Name: adidas AG
# Country: Germany
# All symbols: [{'yahoo': 'ADS.F', 'google': 'FRA:ADS'}]

# Check if symbol exists
symbol = 'NASDAQ:GOOGL'
stock = stock_data.get_stock_by_google_symbol(symbol)
if stock:
    print(f"{symbol} belongs to {stock['name']}")
else:
    print(f"{symbol} not found in database")

# Output: NASDAQ:GOOGL belongs to Alphabet Inc.
```

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

### Get All Countries with Represented Stocks

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieves a list of all countries that have stocks listed in the library's database. This can be used to filter or categorize stock data based on the country of origin.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()
countries = stock_data.get_all_countries()

print("Countries with stocks:", countries)
# Output: ['Germany', 'United States', 'United Kingdom', 'France',
#          'Netherlands', 'Belgium', 'Spain', 'Finland', 'Sweden',
#          'Switzerland', 'Russia', 'Ireland', 'Israel', ...]
```

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

### Get Stocks by Country

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Filter stocks by their country of origin. This function returns a list of stocks associated with a specified country.

```APIDOC
## Get Stocks by Country

### Description
Filter stocks by their country of origin. This function returns a list of stocks associated with a specified country.

### Method
GET

### Endpoint
N/A (Method call on PyTickerSymbols instance)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get all German stocks
german_stocks = list(stock_data.get_stocks_by_country('Germany'))
print(f"German stocks: {len(german_stocks)}")

# Get US stocks
us_stocks = list(stock_data.get_stocks_by_country('United States'))
print(f"US stocks: {len(us_stocks)}")

# Access stock details
for stock in list(german_stocks)[:3]:
    print(f"{stock['name']} - {stock['indices']}")

# Output example:
# adidas AG - ['DAX']
# Allianz SE - ['DAX', 'EURO STOXX 50']
# BASF SE - ['DAX']
```

### Response
#### Success Response (200)
- **stocks** (list of dictionaries) - A list where each dictionary represents a stock and contains fields like 'name', 'country', 'industries', and 'symbols'.
```

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

### Get Stocks by Industry

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Filter stocks by industry classification. This function returns a list of stocks that belong to a specified industry.

```APIDOC
## Get Stocks by Industry

### Description
Filter stocks by industry classification. This function returns a list of stocks that belong to a specified industry.

### Method
GET

### Endpoint
N/A (Method call on PyTickerSymbols instance)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get all banking stocks
banking_stocks = list(stock_data.get_stocks_by_industry('Banking Services'))
print(f"Banking stocks: {len(banking_stocks)}")
```

### Response
#### Success Response (200)
- **stocks** (list of dictionaries) - A list where each dictionary represents a stock and contains fields like 'name', 'country', 'industries', and 'symbols'.
```

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

### Get Stocks by Specific Stock Market Index

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieves a list of all stocks belonging to a specified stock market index. Each returned stock object contains comprehensive metadata including name, country, industries, ticker symbols (Yahoo & Google), and additional company details.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get all DAX stocks
dax_stocks = list(stock_data.get_stocks_by_index('DAX'))
print(f"DAX has {len(dax_stocks)} stocks")
# Output: DAX has 40 stocks

# Access detailed stock information
for stock in dax_stocks[:2]:
    print(f"Name: {stock['name']}")
    print(f"Country: {stock['country']}")
    print(f"Industries: {stock['industries']}")
    print(f"Symbols: {stock['symbols']}")
    print(f"Metadata: {stock.get('metadata', {})}")
    print("---")

# Output example:
# Name: adidas AG
# Country: Germany
# Industries: ['Footwear']
# Symbols: [{'yahoo': 'ADS.F', 'google': 'FRA:ADS'}]
# Metadata: {'founded': 1949, 'employees': 57016}

# Get stocks from other indices
nasdaq_stocks = list(stock_data.get_stocks_by_index('NASDAQ 100'))
sp500_stocks = list(stock_data.get_stocks_by_index('S&P 500'))
ftse_stocks = list(stock_data.get_stocks_by_index('FTSE 100'))
```

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

### Get Stocks Filtered by Country of Origin

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Filters and retrieves a list of stocks based on their country of origin. This allows users to focus on companies from specific geographical regions and access their associated metadata.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get all German stocks
german_stocks = list(stock_data.get_stocks_by_country('Germany'))
print(f"German stocks: {len(german_stocks)}")

# Get US stocks
us_stocks = list(stock_data.get_stocks_by_country('United States'))
print(f"US stocks: {len(us_stocks)}")

# Access stock details
for stock in list(german_stocks)[:3]:
    print(f"{stock['name']} - {stock['indices']}")

# Output example:
# adidas AG - ['DAX']
# Allianz SE - ['DAX', 'EURO STOXX 50']
# BASF SE - ['DAX']
```

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

### Get All Available Industry Classifications

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieves a list of all industry classifications available in the stock database. This function is useful for analyzing the industry distribution of companies or for filtering stocks by sector.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()
industries = stock_data.get_all_industries()

print(f"Total industries: {len(industries)}")
# Output: Total industries: 50+

print("Sample industries:", industries[:10])
# Output: ['Computer Hardware', 'Gold', 'Banking Services', 'Footwear',
#          'Basic Materials', 'Pharmaceuticals', 'Oil & Gas', ...]
```

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

### Get Google Ticker Symbols by Index (Python)

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieves Google Finance ticker symbols for a specified stock index. The output includes exchange prefixes (e.g., 'FRA:') for Google's format. This function is useful for accessing stock data compatible with Google Finance.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get Google tickers for DAX
dax_google_tickers = stock_data.get_google_ticker_symbols_by_index('DAX')

# Display Google format tickers (include exchange prefix)
for tickers in dax_google_tickers[:5]:
    print(tickers)

# Get Google tickers for NASDAQ
nasdaq_google = stock_data.get_google_ticker_symbols_by_index('NASDAQ 100')
for tickers in list(nasdaq_google)[:3]:
    print(tickers)
```

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

### Get All Available Stock Market Indices

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieves a list of all stock market indices supported by the library. This function is useful for understanding the breadth of coverage and for subsequent filtering of stock data by index.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()
indices = stock_data.get_all_indices()

print(f"Total indices: {len(indices)}")
# Output: Total indices: 17

print("Available indices:", indices)
# Output: ['DAX', 'SDAX', 'MDAX', 'TECDAX', 'DOW JONES', 'NASDAQ 100',
#          'S&P 100', 'S&P 500', 'FTSE 100', 'CAC 40', 'AEX', 'BEL 20',
#          'IBEX 35', 'OMX Helsinki 25', 'OMX Stockholm 30', 'Switzerland 20', 'MOEX']
```

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

### Get Stocks Filtered by Industry Classification

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Filters and retrieves a list of stocks based on their industry classification. This enables users to target companies within specific sectors, such as 'Banking Services', and access their details.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get all banking stocks
banking_stocks = list(stock_data.get_stocks_by_industry('Banking Services'))
print(f"Banking stocks: {len(banking_stocks)}")
```

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

### Get Stocks by Industry (Python)

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieves lists of stocks categorized by industry. This function is useful for filtering stocks from specific sectors like 'Computer Hardware' or 'Pharmaceuticals'. It returns a list of stock data dictionaries.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get technology stocks
tech_stocks = list(stock_data.get_stocks_by_industry('Computer Hardware'))

# Get pharmaceutical stocks
pharma_stocks = list(stock_data.get_stocks_by_industry('Pharmaceuticals'))

# Display stocks with their indices
for stock in banking_stocks[:5]:
    symbols = [s['yahoo'] for s in stock['symbols']]
    print(f"{stock['name']} ({stock['country']}): {symbols}")
```

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

### Get Stock Name by Ticker Symbol using Python

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Quickly retrieves only the company name associated with a given ticker symbol. Requires the pytickersymbols library. Supports Yahoo and Google symbols as input, returning the company name as a string or None if not found. Can also perform batch lookups.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get name by Yahoo symbol
name_yahoo = stock_data.get_stock_name_by_yahoo_symbol('ADS.F')
print(f"Yahoo ADS.F: {name_yahoo}")
# Output: Yahoo ADS.F: adidas AG

# Get name by Google symbol
name_google = stock_data.get_stock_name_by_google_symbol('FRA:ADS')
print(f"Google FRA:ADS: {name_google}")
# Output: Google FRA:ADS: adidas AG

# Batch lookup
yahoo_symbols = ['AAPL', 'GOOGL', 'MSFT', 'TSLA']
for symbol in yahoo_symbols:
    name = stock_data.get_stock_name_by_yahoo_symbol(symbol)
    print(f"{symbol}: {name or 'Not found'}")

# Output:
# AAPL: Apple Inc.
# GOOGL: Alphabet Inc.
# MSFT: Microsoft Corporation
# TSLA: Tesla, Inc.

# Handle missing symbols
unknown = stock_data.get_stock_name_by_yahoo_symbol('INVALID123')
print(f"Unknown symbol: {unknown}")
# Output: Unknown symbol: None
```

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

### Get Stock Information by Yahoo Symbol (Python)

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Retrieves detailed information for a specific stock using its Yahoo Finance ticker symbol. The function returns a dictionary containing the stock's name, country, associated indices and industries, and a list of its symbols (Yahoo and Google). It also includes optional metadata if available.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get stock by Yahoo symbol
adidas = stock_data.get_stock_by_yahoo_symbol('ADS.F')

if adidas:
    print(f"Name: {adidas['name']}")
    print(f"Symbol: {adidas['symbol']}")
    print(f"Country: {adidas['country']}")
    print(f"Indices: {adidas['indices']}")
    print(f"Industries: {adidas['industries']}")
    print(f"Symbols: {adidas['symbols']}")
    print(f"Metadata: {adidas.get('metadata', {})}")

# Try multiple symbols
symbols_to_check = ['AAPL', 'GOOGL', 'MSFT', 'INVALID']
for symbol in symbols_to_check:
    stock = stock_data.get_stock_by_yahoo_symbol(symbol)
    if stock:
        print(f"{symbol}: {stock['name']}")
    else:
        print(f"{symbol}: Not found")
```

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

### Get Index Yahoo Symbol using Python

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Converts common index names into their corresponding Yahoo Finance index symbols. This function is part of the pytickersymbols library. It takes an index name string (e.g., 'DAX', 'S&P 500') and returns the Yahoo symbol string or None.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# Get Yahoo symbols for indices
dax_symbol = stock_data.index_to_yahoo_symbol('DAX')
print(f"DAX index symbol: {dax_symbol}")
# Output: DAX index symbol: ^GDAXI

sdax_symbol = stock_data.index_to_yahoo_symbol('SDAX')
print(f"SDAX index symbol: {sdax_symbol}")
# Output: SDAX index symbol: ^SDAXI

# Get symbols for major US indices
sp500_symbol = stock_data.index_to_yahoo_symbol('S&P 500')
dow_symbol = stock_data.index_to_yahoo_symbol('DOW JONES')
nasdaq_symbol = stock_data.index_to_yahoo_symbol('NASDAQ 100')

print(f"S&P 500: {sp500_symbol}")
print(f"DOW JONES: {dow_symbol}")
print(f"NASDAQ 100: {nasdaq_symbol}")
# Output:
# S&P 500: ^GSPC
# DOW JONES: ^DJI
# NASDAQ 100: ^NDX

# Get European indices
swiss_symbol = stock_data.index_to_yahoo_symbol('Switzerland 20')
print(f"Switzerland 20: {swiss_symbol}")
# Output: Switzerland 20: ^SSMI
```

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

### Get Yahoo Ticker Symbols by Index (Python)

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Fetches Yahoo Finance ticker symbols for a given stock index. The function returns a list of lists, where each inner list contains tickers for a single stock, allowing for multiple symbols per stock. These can be flattened into a single list for easier processing.

```python
from pytickersymbols import PyTickerSymbols
import itertools

stock_data = PyTickerSymbols()

# Get Yahoo tickers for DAX
dax_yahoo_tickers = stock_data.get_yahoo_ticker_symbols_by_index('DAX')
print(f"DAX Yahoo tickers: {len(dax_yahoo_tickers)} stocks")

# Each stock can have multiple symbols (returns list of lists)
for tickers in dax_yahoo_tickers[:3]:
    print(tickers)

# Flatten to single list
all_dax_yahoo = list(itertools.chain.from_iterable(dax_yahoo_tickers))
print(all_dax_yahoo[:10])

# Get tickers for other indices
nasdaq_yahoo = stock_data.get_yahoo_ticker_symbols_by_index('NASDAQ 100')
sp500_yahoo = stock_data.get_yahoo_ticker_symbols_by_index('S&P 500')
```

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

### PyTickerSymbols Initialization

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Demonstrates how to create a singleton instance of the PyTickerSymbols class to access stock data. The library uses a singleton pattern to ensure efficient memory usage.

```APIDOC
## PyTickerSymbols Initialization

### Description
Create a singleton instance of PyTickerSymbols to access stock data. The library implements a singleton pattern to ensure efficient memory usage and provides both static and dynamically-generated methods for retrieving ticker symbols.

### Method
Instantiate the class.

### Endpoint
N/A (Class instantiation)

### Parameters
None

### Request Example
```python
from pytickersymbols import PyTickerSymbols

# Create instance (singleton pattern - always returns same instance)
stock_data = PyTickerSymbols()

# Verify singleton behavior
stock_data2 = PyTickerSymbols()
assert stock_data is stock_data2  # True - same instance
```

### Response
#### Success Response (200)
An instance of the PyTickerSymbols class is returned.

#### Response Example
`stock_data` (PyTickerSymbols instance)
```

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

### Load and Query Stock Data from Temporary YAML

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

This snippet demonstrates how to write custom YAML data to a temporary file, load it using PyTickerSymbols, and then query for stocks by index. It shows how to access stock details like name, country, and Yahoo symbol. Includes cleanup of the temporary file.

```python
import tempfile
import os
from pytickersymbols import PyTickerSymbols

custom_yaml = "..."

# Write to temporary YAML file
with tempfile.NamedTemporaryFile(mode='w', suffix='.yaml', delete=False) as f:
    f.write(custom_yaml)
    temp_path = f.name

# Load YAML data
stock_data = PyTickerSymbols()
stock_data.load_yaml(temp_path)

# Query loaded data
indices = stock_data.get_all_indices()
print(f"Available indices: {indices}")
# Output: Available indices: ['TECH 10']

tech_stocks = list(stock_data.get_stocks_by_index('TECH 10'))
for stock in tech_stocks:
    print(f"Name: {stock['name']}")
    print(f"Country: {stock['country']}")
    print(f"Yahoo symbol: {stock['symbols'][0]['yahoo']}")

# Output:
# Name: TechCorp Ltd
# Country: United Kingdom
# Yahoo symbol: TECH.L

# Clean up
os.unlink(temp_path)
```

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

### Initialize PyTickerSymbols Singleton Instance

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Creates a singleton instance of the PyTickerSymbols class. This ensures that only one instance of the class is ever created, optimizing memory usage. Subsequent calls to the constructor will return the same instance.

```python
from pytickersymbols import PyTickerSymbols

# Create instance (singleton pattern - always returns same instance)
stock_data = PyTickerSymbols()

# Verify singleton behavior
stock_data2 = PyTickerSymbols()
assert stock_data is stock_data2  # True - same instance
```

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

### Use Static Index Constants for Stock Queries

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

This snippet demonstrates using predefined static constants from `pytickersymbols.Statics` to specify stock indices, which helps prevent typos and ensures accuracy when querying specific market indices. It retrieves and prints the number of stocks for several major indices.

```python
from pytickersymbols import PyTickerSymbols
from pytickersymbols import Statics

stock_data = PyTickerSymbols()

# Use constants instead of strings
dax_stocks = list(stock_data.get_stocks_by_index(Statics.Indices.DE_DAX))
sp500_stocks = list(stock_data.get_stocks_by_index(Statics.Indices.US_SP_500))
nasdaq_stocks = list(stock_data.get_stocks_by_index(Statics.Indices.US_NASDAQ))
ftse_stocks = list(stock_data.get_stocks_by_index(Statics.Indices.GB_FTSE))

print(f"DAX: {len(dax_stocks)} stocks")
print(f"S&P 500: {len(sp500_stocks)} stocks")
print(f"NASDAQ 100: {len(nasdaq_stocks)} stocks")
print(f"FTSE 100: {len(ftse_stocks)} stocks")

# Available index constants:
# Statics.Indices.DE_DAX - 'DAX'
# Statics.Indices.DE_MDAX - 'MDAX'
# Statics.Indices.DE_SDAX - 'SDAX'
# Statics.Indices.DE_TECDAX - 'TECDAX'
# Statics.Indices.US_DOW - 'DOW JONES'
# Statics.Indices.US_NASDAQ - 'NASDAQ 100'
# Statics.Indices.US_SP_100 - 'S&P 100'
# Statics.Indices.US_SP_500 - 'S&P 500'
# Statics.Indices.GB_FTSE - 'FTSE 100'
# Statics.Indices.FR_CAC_40 - 'CAC 40'
# Statics.Indices.NL_AEX - 'AEX'
# Statics.Indices.BE_20 - 'BEL 20'
# Statics.Indices.ES_IBEX_35 - 'IBEX 35'
# Statics.Indices.SE_OMX_30 - 'OMX Stockholm 30'
# Statics.Indices.FI_OMX_25 - 'OMX Helsinki 25'
# Statics.Indices.CH_20 - 'Switzerland 20'
# Statics.Indices.RU_MOEX - 'MOEX'
```

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

### Dynamic Ticker Getter Methods (Python)

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Utilizes dynamically generated methods to fetch ticker symbols. These methods follow a pattern like `get_{index}_{exchange}_{google|yahoo}_tickers` and support various exchanges such as Frankfurt, London, and NYC. The library provides a way to list all available dynamic methods.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()

# DAX stocks from Frankfurt exchange
dax_frankfurt_google = stock_data.get_dax_frankfurt_google_tickers()
dax_frankfurt_yahoo = stock_data.get_dax_frankfurt_yahoo_tickers()

print(f"DAX Google tickers: {len(dax_frankfurt_google)}")
print(f"Sample: {dax_frankfurt_google[:3]}")

print(f"DAX Yahoo tickers: {len(dax_frankfurt_yahoo)}")
print(f"Sample: {dax_frankfurt_yahoo[:3]}")

# S&P 500 from NYC
sp500_nyc_yahoo = stock_data.get_sp_500_nyc_yahoo_tickers()
sp500_nyc_google = stock_data.get_sp_500_nyc_google_tickers()

# NASDAQ 100 from NYC
nasdaq_nyc_yahoo = stock_data.get_nasdaq_100_nyc_yahoo_tickers()

# FTSE 100 from London
ftse_london_yahoo = stock_data.get_ftse_100_london_yahoo_tickers()

# List all available dynamic methods
all_ticker_methods = [
    method for method in dir(stock_data)
    if method.endswith('_google_tickers') or method.endswith('_yahoo_tickers')
]
print(f"Total dynamic methods: {len(all_ticker_methods)}")
print(f"Sample methods: {all_ticker_methods[:5]}")
```

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

### Load Custom Stock Data from YAML using Python

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Enables loading custom or updated stock data from an external YAML file into the PyTickerSymbols library. This requires pytickersymbols, yaml, and tempfile. It accepts a file path to a YAML file containing stock data and updates the library's internal data.

```python
from pytickersymbols import PyTickerSymbols
import yaml
import tempfile

# Create custom stock data in YAML format
custom_yaml = """
indices:
  - name: "TECH 10"
    yahoo: "^TECH10"

companies:
  - id: 1
    name: "TechCorp Ltd"
    symbol: "TECH"
    country: "United Kingdom"
    indices:
      - "TECH 10"
    industries:
      - "Software"
    symbols:
      - yahoo: "TECH.L"
        google: "LON:TECH"
    metadata:
      founded: 2015
      employees: 1200
"""

# Write custom YAML data to a temporary file
with tempfile.NamedTemporaryFile(mode='w', suffix='.yaml', delete=False) as f:
    f.write(custom_yaml)
    temp_yaml_path = f.name

# Initialize PyTickerSymbols and load custom data from YAML
stock_data_yaml = PyTickerSymbols()
stock_data_yaml.load_yaml(temp_yaml_path)

# Example: Retrieving data loaded from YAML
custom_indices = stock_data_yaml.get_all_indices()
print(f"Custom Indices from YAML: {custom_indices}")
# Expected Output: Custom Indices from YAML: ['TECH 10']

custom_stocks = list(stock_data_yaml.get_stocks_by_index('TECH 10'))
if custom_stocks:
    print(f"Company Name from YAML: {custom_stocks[0]['name']}")
    # Expected Output: Company Name from YAML: TechCorp Ltd

# Clean up the temporary file
import os
os.unlink(temp_yaml_path)
```

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

### Load Custom Stock Data from JSON using Python

Source: https://context7.com/portfolioplus/pytickersymbols/llms.txt

Allows loading custom or updated stock data from an external JSON file into the PyTickerSymbols library. Requires pytickersymbols, json, and tempfile. It takes a file path to a JSON file containing stock data in a specific format and updates the internal data structure.

```python
from pytickersymbols import PyTickerSymbols
import json
import tempfile

# Create custom stock data
custom_data = {
    "indices": [
        {
            "name": "CUSTOM INDEX",
            "yahoo": "^CUSTOM"
        }
    ],
    "companies": [
        {
            "id": 1,
            "name": "Custom Company Inc.",
            "symbol": "CUST",
            "country": "United States",
            "indices": ["CUSTOM INDEX"],
            "industries": ["Technology"],
            "symbols": [
                {
                    "yahoo": "CUST",
                    "google": "NASDAQ:CUST"
                }
            ],
            "metadata": {
                "founded": 2020,
                "employees": 500
            }
        }
    ]
}

# Write to temporary file
with tempfile.NamedTemporaryFile(mode='w', suffix='.json', delete=False) as f:
    json.dump(custom_data, f)
    temp_path = f.name

# Load custom data
stock_data = PyTickerSymbols()
stock_data.load_json(temp_path)

# Query custom data
indices = stock_data.get_all_indices()
print(f"Indices: {indices}")
# Output: Indices: ['CUSTOM INDEX']

stocks = list(stock_data.get_stocks_by_index('CUSTOM INDEX'))
print(f"Custom stocks: {stocks[0]['name']}")
# Output: Custom stocks: Custom Company Inc.

# Clean up
import os
os.unlink(temp_path)
```

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

### Fetch Specific Index Ticker Symbols (Google/Yahoo) with pytickersymbols

Source: https://github.com/portfolioplus/pytickersymbols/blob/master/README.md

Illustrates fetching ticker symbols for specific indices from either Google or Yahoo, using methods named according to a convention like `get_{index_name}_{exchange_city}_{yahoo or google}_tickers`. It also shows how to dynamically list all available getter methods.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()
# the naming conversation is get_{index_name}_{exchange_city}_{yahoo or google}_tickers
dax_google = stock_data.get_dax_frankfurt_google_tickers()
dax_yahoo = stock_data.get_dax_frankfurt_yahoo_tickers()
sp100_yahoo = stock_data.get_sp_100_nyc_yahoo_tickers()
sp500_google = stock_data.get_sp_500_nyc_google_tickers()
dow_yahoo = stock_data.get_dow_jones_nyc_yahoo_tickers()
# there are too many combination. Here is a complete list of all getters
all_ticker_getter_names = list(filter(
   lambda x: (
         x.endswith('_google_tickers') or x.endswith('_yahoo_tickers')
   ),
   dir(stock_data),
))
print(all_ticker_getter_names)
```

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

### Retrieve Stocks by Index using pytickersymbols

Source: https://github.com/portfolioplus/pytickersymbols/blob/master/README.md

Shows how to fetch all ticker symbols associated with a specific stock index, such as 'DAX' or 'FTSE 100'. The result is a dictionary-like object containing stock information. The output is then printed as a list.

```python
from pytickersymbols import PyTickerSymbols

stock_data = PyTickerSymbols()
 german_stocks = stock_data.get_stocks_by_index('DAX')
uk_stocks = stock_data.get_stocks_by_index('FTSE 100')

print(list(uk_stocks))
```

=== COMPLETE CONTENT === This response contains all available snippets from this library. No additional content exists. Do not make further requests.