Metadata-Version: 2.1
Name: tradinghours
Version: 0.1.0
Summary: TradingHours Library
Author-email: TradingHours <developer@tradinghours.com>
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Topic :: Office/Business :: Financial
Classifier: Topic :: Software Development :: Libraries
Requires-Dist: pytz
Requires-Dist: flit ; extra == "dev"
Requires-Dist: isort ; extra == "dev"
Requires-Dist: flake8 ; extra == "dev"
Requires-Dist: flake8-pyproject ; extra == "dev"
Requires-Dist: black ; extra == "dev"
Requires-Dist: coverage[toml] ; extra == "dev"
Requires-Dist: sqlalchemy ; extra == "sql"
Project-URL: Bug Tracker, https://github.com/tradinghours/tradinghours-python/issues
Project-URL: Homepage, https://github.com/tradinghours/tradinghours-python
Provides-Extra: dev
Provides-Extra: sql

<div align="center">
<img src="https://www.tradinghours.com/img/logo-512x512.png" alt="TradingHours API Docs" height="100">
<h1>TradingHours.com Python Library</h1>
</div>

[TradingHours.com](https://www.tradinghours.com) licenses **Market Holidays and Trading Hours data** for over 900 exchanges and trading venues around the world.
This library allows clients to easily integrate our market holidays and trading hours data into existing applications.
This packages downlods all available data from TradingHours.com and then allows you to work with the data locally.

**A paid subscription is required to use this package**

[Learn more »](https://www.tradinghours.com/data)

## About the Data

### Market coverage

We supports over 900 exchanges and trading venues, including all major currencies.
[See all supported markets](https://www.tradinghours.com/coverage).

Our comprehensive data covers:

- Market holidays
- Trading hours
- Half-days / Irregular schedules
- Non-settlement dates
- Currency holidays
- Detailed trading phases

### How is data collected?

Our global research team collects and verifies trading hours and market holidays using exclusively primary sources.
Manual and automated checks ensure the highest degree of accuracy and reliability.

Once data is collected, we then continually monitor for changes to ensure the data is always up-to-date.
Data is updated daily.

## Installation

```console
pip install tradinghours
```

## Basic Configuration

```console
export TRADINGHOURS_TOKEN=<your-token-goes-here>
```

If you have an active subscription, [click here to get your API key](https://www.tradinghours.com/user/api-tokens).

See [advanced configuration options](#optional-advanced-configuration). 

## Usage

### Importing Data

You just need to run the following command to download and import official data. Remember that you need to have a valid **TRADINGHOURS_TOKEN** environment variable.

```console
$ tradinghours import
Downloading..... (0.824s)
Ingesting.......................... (12.066s)
```

You can then check current data status with the following subcommand:

```console
$ tradinghours status --extended
Collecting timestamps.... (0.213s)
TradingHours Data Status:
  Remote Timestamp:   Thu Oct 26 02:08:17 2023
  Local Timestamp:    Thu Oct 26 03:12:40 2023

Reading local data.... (0.426s)
Extended Information:
  Currencies count:   30
  Markets count:      1012
```

### List Markets

```python
from tradinghours.market import Market

for market in Market.list_all():
    print(market)
```

### Get Market

```python
from tradinghours.market import Market

# Get by either FinID or MIC
market = Market.get('US.NYSE')
market = Market.get('XNYS')
```

If a market is marked "permanently closed" it may be replaced or superseded by another market. 
By default, the newer market will be returned automatically. You can still retrieve the 
older market object for historical analysis by using the `follow=False` parameter.

```python
from tradinghours.market import Market

# AR.BCBA is permanently closed and replaced by AR.BYMA
market = Market.get('AR.BCBA')
original = Market.get('AR.BCBA', follow=False)

print (market.fin_id) # AR.BYMA
print (original.fin_id) # AR.BCBA
```

### Market Holidays

```python
from tradinghours.market import Market

market = Market.get('US.NYSE')
for holiday in market.list_holidays("2023-06-01", "2023-12-31"):
    print(holiday)
```

### Trading Hours

```python
from tradinghours.market imort Market

market = Market.get('XNYS')
for concrete_phase in market.generate_schedules("2023-09-01", "2023-09-30"):
    print(concrete_phase)
```

### List Currencies

```python
from tradinghours.currency import Currency

for currency in Currency.list_all():
    print(currency)
```

### Currency Holidays

```python
from tradinghours.currency import Currency

currency = Currency.get('AUD')
for holiday in currency.list_holidays("2023-06-01", "2023-12-31"):
    print(currency)
```

## Optional Advanced Configuration

By default, the library uses local file storage. Optionally you can 
configure the library to use an SQL store. You can adjust settings
using a **tradinghours.ini** file on the current working directory.

Here is a sample configuration file using file system storage:

```ini
[api]
token = YOUR-TOKEN-HERE

[data]
use_db = False
local_dir = /srv/tradinghours/local
remote_dir = /srv/tradinghours/remote
```

And here you can see one using a local SQL Alchemy database. Note that
you can use any valid [Database URL](https://docs.sqlalchemy.org/en/20/core/engines.html#database-urls):

```ini
[api]
token = YOUR-TOKEN-HERE

[data]
use_db = True
db_url = sqlite:///tradinghours.db
```

### Database Schema

In case you would like to directly access the tables for the SQL mode, you
can see that they all follow a very simple structure with keys for stored data
and the data with actual JSON. The library uses this simple structure that
should be compatible with nearly all database engines around.

Here is the DDL for the tables currently in use:

```sql
CREATE TABLE thstore_currencies (id INTEGER NOT NULL, slug VARCHAR, "key" VARCHAR, data JSON, PRIMARY KEY (id));
CREATE TABLE thstore_currency_holidays (id INTEGER NOT NULL, slug VARCHAR, "key" VARCHAR, data JSON, PRIMARY KEY (id));
CREATE TABLE thstore_holidays (id INTEGER NOT NULL, slug VARCHAR, "key" VARCHAR, data JSON, PRIMARY KEY (id));
CREATE TABLE thstore_markets (id INTEGER NOT NULL, slug VARCHAR, "key" VARCHAR, data JSON, PRIMARY KEY (id));
CREATE TABLE thstore_mic_mapping (id INTEGER NOT NULL, slug VARCHAR, "key" VARCHAR, data JSON, PRIMARY KEY (id));
CREATE TABLE thstore_schedules (id INTEGER NOT NULL, slug VARCHAR, "key" VARCHAR, data JSON, PRIMARY KEY (id));
CREATE TABLE thstore_season_definitions (id INTEGER NOT NULL, slug VARCHAR, "key" VARCHAR, data JSON, PRIMARY KEY (id));
```

