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    "info": {
        "author": "Dainis Gorbunovs",
        "author_email": "dgdev@protonmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# FreeTrade API\nThis is an attempt to make an unofficial Python package for [FreeTrade](https://freetrade.io).\nThere is no official API released, yet. FreeTrade is a zero-fee UK-regulated stockbroker.\n\n## What is supported\n* Find list of `tradable securities` with information on the asset class, market, currency, country.\n* Create a list of tickers for `Trading View`'s watch list. \n* `Historical prices`\n* Logging into Freetrade account and saving the session into `ft-session.json` file.\n\n## Install\nInstall through `pip` package manger:\n```bash\npip install freetrade\n```\n\nAlternatively, for developing this package:\n```bash\nconda create -n myenv python=3.7\nconda activate myenv\npip install -r requirements.txt\n```\n\n## Prerequisites\nBefore running this, it is necessary to set the API keys. Edit `ft-keys.json` to include the necessary API keys. \nThese keys can be found using a tool, which can extract StringCare secrets, e.g. [DeStringCare](https://github.com/DainisGorbunovs/DeStringCare).\n\n## API\n### Creating `ft` FreeTrade object\n#### Without authentication\n```python\nfrom freetrade import FreeTrade\n\nft = FreeTrade()\n```\nThe only thing which will work is `Index` class, i.e. getting the list of supported stock tickers.\n\n#### With authentication\n```python\nfrom freetrade import FreeTrade\n\nemail = '...'  # Email to use for the login\nft = FreeTrade(email)\n```\n\nBy default when creating the object, it will try to load an older authenticated session from `ft-session.json` file.\nOtherwise it logs in again, and requests a one time password (OTP), which is sent to the email.\n\nThe code parses OTP from the standard user input. Alternatively specify `otp_parser` parameter in `FreeTrade` object\n to a function which can fetch the email and parse the OTP itself.\n\n### `Index` - no authentication needed\n#### Ticker history\nAssuming `ft` object is created, here is how one month of historical price for a stock.\n```python\nprices = ft.index.get_ticker_history('TSLA', 'XNAS')\n\nfor history_date, price in prices.items():\n    print(f'{history_date}: ${price:.2f}')\n```\n\n#### Get assets\n```python\nassets = ft.index.get_assets()\n```\n\nReturns a dictionary of different categories, which have subcategories.\nThese subcategories contain a list of stock assets.\n* `currency`\n  * `GBP` / `USD`: list of assets\n* `exchange`\n  * `XLON` / `XNYS` / `XNAS`: list of assets\n* `asset_class`\n  * `ETF` / `EQUITY` / `ADR`: list of assets\n* `country_of_incorporation`\n  * `IE` / `GB` / `US` / `KY` / ... : list of assets\n* `all`: list of assets\n\nSample asset for an ETF `LSE:ERNU`:\n```json\n{\n    \"asset_class\": \"ETF\",\n    \"symbol\": \"ERNU\",\n    \"isin\": \"IE00BCRY6227\",\n    \"exchange\": \"XLON\",\n    \"currency\": \"GBP\",\n    \"country_of_incorporation\": \"IE\",\n    \"long_title\": \"iShares $ Ultrashort Bond UCITS ETF (Dist.)\",\n    \"short_title\": \"$ Ultrashort\",\n    \"subtitle\": \"Very short maturity $ debt\",\n    \"logo_4x\": \"//a.storyblok.com/f/41481/640x640/7ec0a292de/ishares-symbol-4x.png\",\n    \"isa_eligible\": true,\n    \"coming_soon\": false,\n    \"required_version\": \"1.0\",\n    \"objectID\": \"IE00BCRY6227\",\n    ...\n}\n```\n\n#### Get tickers\n```python\ntickers = ft.index.get_tickers()\n```\n\nReturns a dictionary, where:\n* key is an exchange symbol FreeTrade uses, and\n* value is a list of ticker symbols \n\n```python\ntickers = {\n    'XLON': ['ERNU', 'III', '3IN', ...],\n    'XNYS': ['MMM', 'ABBV', 'BABA', ...],\n    'XNAS': ['ATVI', 'ADBE', 'AMD', 'GOOGL', 'AMZN', ...]\n}\n```\n\n#### Get list of tickers for Trading View watch list\n```python\ntickers_union = ft.index.get_tradingview_tickers(join_exchanges=True)\n```\n\nReturns a string formatted for importing into Trading View watch list.\n\nWith `join_exchanges = True`:\n```python\ntickers_union = 'LSE:ERNU,LSE:III,LSE:3IN,LSE:ABF,LSE:ACA,LSE:ADM,...'\n```\n\nDefault (when `join_exchanges = False`):\n```python\ntickers_union = {\n    'XLON': 'LSE:ERNU,LSE:III,LSE:3IN,LSE:ABF,LSE:ACA,LSE:ADM,...',\n    'XNYS': 'NYSE:MMM,NYSE:ABBV,NYSE:BABA,NYSE:AXP,NYSE:APA,NYSE:T,...',\n    'XNAS': 'NASDAQ:ATVI,NASDAQ:ADBE,NASDAQ:AMD,NASDAQ:GOOGL,NASDAQ:AMZN,...'\n}\n```\n\n### `API` - requires authentication\n#### Finding the address for a post code\n```python\npostcode = 'E15JL'\naddress = ft.api.get_address_by_postcode(postcode)\n```\n\nReturns a list of addresses, e.g. sample address:\n```json\n[{\n    \"summaryline\": \"Freetrade, 68-80 Hanbury Street, London, Greater London, E1 5JL\",\n    \"organisation\": \"Freetrade\",\n    \"number\": \"68-80\",\n    \"premise\": \"68-80\",\n    \"street\": \"Hanbury Street\",\n    \"posttown\": \"London\",\n    \"county\": \"Greater London\",\n    \"postcode\": \"E1 5JL\"\n}]\n```\n\n#### Verifying bank number\n```python\nbank = ft.api.validate_bank('308012', '15887060')\n```\n\nReturns a lot of information on the account number, e.g. sample values:\n```json\n{\n    \"result\": \"VALID\",\n    \"sortcode\": \"308012\",\n    \"bicbank\": \"LOYDGB21\",\n    \"bankname\": \"CITY OFFICE (308012)\",\n    \"owningbank\": \"LLOYDS BANK PLC\",\n    \"chapssrbicbank\": \"LOYDGB2L\",\n    \"chapssrbicbr\": \"XXX\",\n    ...\n}\n```\n\n### Get price history\n```python\ntesla = ft.api.get_ticker_history('TSLA', 'XNAS', duration='1m')\nnational_grid = ft.api.get_ticker_history('NG.', 'XLON', duration='1m')\n```\n\nThe possible duration values, where `1m` is default: \n* `5y`, `2y`, `1y`, `ytd`, `6m`, `3m`, `1m`, `1d`\n\nReturns an `OrderedDict` of data points `(date, adjusted closing price)` sorted by date in ascending order.\n\nSample output:\n```python\ntesla = OrderedDict([\n    ('2019-04-04', 267.78),\n    ('2019-04-05', 274.96),\n    ('2019-04-08', 273.2),\n    ('2019-04-09', 272.31),\n    ('2019-04-10', 276.06),\n    ...\n])\n``` \n\nNotes:\n* use `Quandl` for UK securities;\n* uses `IEXTrading` for other securities.\n\n### `DataStore` - requires authentication\n#### Download or update historical prices\n```python\nft.datastore.update_historical_prices()\n```\n\nSaves the adjusted historical closing prices for the assets into `history` directory. If it does not exist, it is created.\n\nThe file name is the ticker's symbol, and each the prices are saved in ascending order.\n\nSample in `history/TSLA.csv`:\n```csv\n2014-05-05,216.61\n2014-05-06,207.28\n2014-05-07,201.35\n2014-05-08,178.59\n2014-05-09,182.26\n2014-05-12,184.67\n2014-05-13,190.16\n...\n```\n\n#### Load the historical data as `pd.DataFrame`\nThis function loads the historical data from `history` directory.\n\nNote that some assets have missing prices as they were not traded during that day, thus they show up as `nan`.\n\n```python\ndf = ft.datastore.load_historical_data_as_dataframe()\nprint(df.head(), df.shape)\n```\n\n\nSample output:\n```text\n               CSCO          SVT  ...          WTB          NXT\nDate                              ...                          \n2014-05-05  19.5875  1486.452691  ...  3650.414898  5184.507159\n2014-05-06  19.3870  1489.696450  ...  3659.383977  5137.446580\n2014-05-07  19.5150  1509.159006  ...  3645.033451  5094.307715\n2014-05-08  19.6413  1510.780885  ...  3677.322133  5082.542570\n2014-05-09  19.6430  1512.402765  ...  3676.425226  5070.777425\n\n[5 rows x 341 columns] (1305, 341)\n```\n\n## Anything else?\n* Feel free to make a `GitHub issue`, if you find any issues or have enhancement ideas.\n\n* `Pull requests` are welcome, if you have made improvements to this code.\n\n\n",
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