diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml index 085cdb3..e58db8f 100644 --- a/.github/workflows/build-test.yml +++ b/.github/workflows/build-test.yml @@ -17,7 +17,7 @@ jobs: - uses: actions/checkout@v4 - uses: psf/black@stable with: - options: "--check --verbose" + options: "--check --verbose --diff" build-and-test: diff --git a/README.md b/README.md index 914d793..09bafb8 100644 --- a/README.md +++ b/README.md @@ -13,7 +13,7 @@ A python library to create **meaningful** OHLCV datasets for financial instrumen `market_prices` provides for enhanced querying and post-processing of financial price data. -Works out-the-box with prices from the Yahoo Finance API via [yahooquery][yahooquery] (see [Disclaimers](https://github.com/maread99/market_prices#disclaimers)). +Works out-the-box with prices from the Yahoo Finance API via [yahooquery][yahooquery] (see [Disclaimers](https://github.com/maread99/market_prices#disclaimers)) or from locally stored .csv files. ## Installation @@ -206,6 +206,9 @@ symbol MSFT 9988.HK BTC-USD The [quickstart.ipynb](https://github.com/maread99/market_prices/blob/master/docs/tutorials/quickstart.ipynb) tutorial offers a fuller introduction. [Here](https://github.com/maread99/market_prices/blob/master/docs/tutorials_docs.md) you'll find links to all the tutorials which collectively cover all that `market_prices` offers. ## Features include: +* Get price data out-the-box: + * `PricesYahoo` to get live and historic prices from the Yahoo Finance API via [yahooquery][yahooquery] (see [Disclaimers](https://github.com/maread99/market_prices#disclaimers)). + * `PricesCsv` to get price data from locally stored .csv files. * Include **securities trading on different exchanges** with differing opening hours across different time zones. * Request the **period** covered by a dataset in terms of either: * trading time (minutes and hours). diff --git a/docs/developers/other_internals.md b/docs/developers/other_internals.md index fe741c4..8fd4f83 100644 --- a/docs/developers/other_internals.md +++ b/docs/developers/other_internals.md @@ -134,3 +134,6 @@ NB: A daterange end that is a session close that is aligned against the base int ## `daterange.GetterIntraday.daterange_tight` The `daterange.GetterIntraday.daterange_tight` tightens the end (first item) so that the difference between the end and the accuracy is less than one base interval. When the downsample interval (ds_interval) is high relative to the base interval this has the benefit of preventing 'partial requests' for data that cover just the end of the daterange over which no symbol trades (and hence no data would be expected to be returned). See the property documentation for an example. + +## Right Limits +Right limits were introduced January 2024 to support sourcing historic price data from locally stored .csv files (`PricesCsv`). To minimise changes and maintain much of the existing implementation (and hence tests and tutorials) a new `BASE_LIMITS_RIGHT` class attribute was introduced rather than altering the existing `BASE_LIMITS` which could have been amended to take a tuple defining both the left and right limit. Similarly, a 'limit_right' parameter was added to the `daterange._Getter` constructor rather than redefining the 'limit' parameter as 'limits' to take a tuple. On reflection, given the different treatment of each limit (with the right limit defaulting to 'now' if not defined, whereas the left limit for daily data has to be found) I think that defining left and right limits separately IS definitely the way to do. This way the right limit can be ignored for any service that provides for data to now (i.e. most of them). It's much clearer to have them left and right limits separately. Keep it this way. diff --git a/docs/tutorials/prices.ipynb b/docs/tutorials/prices.ipynb index dd50c04..768767c 100644 --- a/docs/tutorials/prices.ipynb +++ b/docs/tutorials/prices.ipynb @@ -12,12 +12,17 @@ "metadata": {}, "source": [ "#### Sections\n", - "* [PricesYahoo](#PricesYahoo)\n", - "* [Symbols](#Symbols)\n", - "* [Calendars](#Calendars)\n", + "* [Prices classes](#Prices-classes)\n", + " * [`symbols`](#Symbols)\n", + " * [Calendars](#Calendars)\n", " * [`lead_symbol`](#lead_symbol)\n", " * [`calendars`](#calendars)\n", - "* [`delays`](#delays)" + "* [`PricesYahoo`](#PricesYahoo)\n", + " * [`delays`](#delays)\n", + " * [`adj_close`](#adj_close)\n", + " * [`PricesYahoo` doc](#PricesYahoo-doc)\n", + "* [`PricesCsv`](#PricesCsv)\n", + " * [`PricesCsv` doc](#PricesCsv-doc)" ] }, { @@ -25,7 +30,7 @@ "metadata": {}, "source": [ "#### Notes\n", - "* The cell **outputs** shown in this tutorial are based on executing the cells at **2022-05-12 16:44 UTC**. Simply rerun the cells to bring any dynamic output up to date." + "* The cell **outputs** shown in this tutorial are based on executing the cells at **2024-01-30 21:11 UTC**. Simply rerun the cells to bring any dynamic output up to date." ] }, { @@ -33,12 +38,12 @@ "metadata": {}, "source": [ "### Setup\n", - "Run following cell to import tutorial dependencies" + "Execute the following cell to import tutorial dependencies." ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -46,45 +51,51 @@ ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "## PricesYahoo" + "## Prices classes\n", + "\n", + "`market_prices` uses Prices classes to access price data. There are currently two classes included with the library:\n", + "* `PricesYahoo` provides for getting live and historic price data 'out-the-box' from Yahoo APIs (see [disclaimers](../../README.md) section of README.md) via the `yahooquery` library.\n", + "* `PricesCsv` gets price data from locally saved .csv files containing historic price data." ] }, { - "cell_type": "markdown", + "cell_type": "code", + "execution_count": 2, "metadata": {}, + "outputs": [], "source": [ - "`market_prices` uses Prices classes to access price data. The default `PricesYahoo` class provides for getting price data 'out-the-box' from Yahoo APIs (see [disclaimers](../../README.md) section of README.md) via yahooquery." + "from market_prices import PricesYahoo\n", + "from market_prices import PricesCsv" ] }, { - "cell_type": "code", - "execution_count": 3, + "cell_type": "markdown", "metadata": {}, - "outputs": [], "source": [ - "from market_prices import PricesYahoo" + "The `symbols`, `calendars` and `lead_symbol` parameters are common to both classes..." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Symbols" + "### `symbols`" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "The `PricesYahoo` class requires a single argument to define the symbols for which price data is to be requested. The symbols can be defined as a list of strings or a single comma-delimited string." + "The `symbols` parameter defines the instruments for which price data is required. The symbols can be defined as a list of strings or a single comma-delimited or space-delimited string. For the `PricesYahoo` class `symbols` is the only required arugment." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -93,7 +104,7 @@ "['MSFT', 'GOOG']" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -108,12 +119,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Prices are available for any symbol for which price data is available on [yahoo finance](https://uk.finance.yahoo.com/), for example..." + "Using `PricesYahoo` prices are available for any symbol for which price data is available on [yahoo finance](https://uk.finance.yahoo.com/), for example..." ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -136,7 +147,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -193,76 +204,76 @@ " \n", " \n", " \n", - " [2022-05-12 07:30:00, 2022-05-12 07:40:00)\n", - " 80.000000\n", - " 80.300003\n", - " 79.900002\n", - " 80.199997\n", - " 2499259.0\n", - " 9801.0\n", - " 9821.0\n", - " 9785.0\n", - " 9799.0\n", - " 55810.0\n", + " [2024-01-30 07:30:00, 2024-01-30 07:40:00)\n", + " 70.949997\n", + " 71.250000\n", + " 70.900002\n", + " 71.199997\n", + " 976002.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " ...\n", " NaN\n", " NaN\n", " NaN\n", " NaN\n", " NaN\n", - " 7181.529785\n", - " 7194.009766\n", - " 7171.970215\n", - " 7191.529785\n", - " 0.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " [2022-05-12 07:40:00, 2022-05-12 07:50:00)\n", - " 80.300003\n", - " 80.349998\n", - " 79.949997\n", - " 80.000000\n", - " 2462802.0\n", - " 9862.0\n", - " 9862.0\n", - " 9794.0\n", - " 9799.0\n", - " 39472.0\n", + " [2024-01-30 07:40:00, 2024-01-30 07:50:00)\n", + " 71.099998\n", + " 71.150002\n", + " 70.849998\n", + " 70.900002\n", + " 2794300.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " ...\n", " NaN\n", " NaN\n", " NaN\n", " NaN\n", " NaN\n", - " 7220.209961\n", - " 7220.770020\n", - " 7176.339844\n", - " 7181.540039\n", - " 0.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", - " [2022-05-12 07:50:00, 2022-05-12 08:00:00)\n", - " 79.949997\n", - " 80.449997\n", - " 79.800003\n", - " 80.349998\n", - " 2616271.0\n", - " 9824.0\n", - " 9866.0\n", - " 9822.0\n", - " 9863.0\n", - " 39555.0\n", + " [2024-01-30 07:50:00, 2024-01-30 08:00:00)\n", + " 71.150002\n", + " 71.150002\n", + " 70.599998\n", + " 71.099998\n", + " 2218000.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " ...\n", " NaN\n", " NaN\n", " NaN\n", " NaN\n", " NaN\n", - " 7208.950195\n", - " 7221.839844\n", - " 7204.810059\n", - " 7220.169922\n", - " 0.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " \n", " \n", "\n", @@ -272,44 +283,38 @@ "text/plain": [ "symbol 9988.HK \\\n", " close high low \n", - "[2022-05-12 07:30:00, 2022-05-12 07:40:00) 80.000000 80.300003 79.900002 \n", - "[2022-05-12 07:40:00, 2022-05-12 07:50:00) 80.300003 80.349998 79.949997 \n", - "[2022-05-12 07:50:00, 2022-05-12 08:00:00) 79.949997 80.449997 79.800003 \n", + "[2024-01-30 07:30:00, 2024-01-30 07:40:00) 70.949997 71.250000 70.900002 \n", + "[2024-01-30 07:40:00, 2024-01-30 07:50:00) 71.099998 71.150002 70.849998 \n", + "[2024-01-30 07:50:00, 2024-01-30 08:00:00) 71.150002 71.150002 70.599998 \n", "\n", - "symbol AZN.L \\\n", - " open volume close \n", - "[2022-05-12 07:30:00, 2022-05-12 07:40:00) 80.199997 2499259.0 9801.0 \n", - "[2022-05-12 07:40:00, 2022-05-12 07:50:00) 80.000000 2462802.0 9862.0 \n", - "[2022-05-12 07:50:00, 2022-05-12 08:00:00) 80.349998 2616271.0 9824.0 \n", + "symbol AZN.L \\\n", + " open volume close high \n", + "[2024-01-30 07:30:00, 2024-01-30 07:40:00) 71.199997 976002.0 NaN NaN \n", + "[2024-01-30 07:40:00, 2024-01-30 07:50:00) 70.900002 2794300.0 NaN NaN \n", + "[2024-01-30 07:50:00, 2024-01-30 08:00:00) 71.099998 2218000.0 NaN NaN \n", "\n", - "symbol \\\n", - " high low open volume \n", - "[2022-05-12 07:30:00, 2022-05-12 07:40:00) 9821.0 9785.0 9799.0 55810.0 \n", - "[2022-05-12 07:40:00, 2022-05-12 07:50:00) 9862.0 9794.0 9799.0 39472.0 \n", - "[2022-05-12 07:50:00, 2022-05-12 08:00:00) 9866.0 9822.0 9863.0 39555.0 \n", + "symbol ... PETR3.SA \\\n", + " low open volume ... close high \n", + "[2024-01-30 07:30:00, 2024-01-30 07:40:00) NaN NaN NaN ... NaN NaN \n", + "[2024-01-30 07:40:00, 2024-01-30 07:50:00) NaN NaN NaN ... NaN NaN \n", + "[2024-01-30 07:50:00, 2024-01-30 08:00:00) NaN NaN NaN ... NaN NaN \n", "\n", - "symbol ... PETR3.SA \\\n", - " ... close high low open volume \n", - "[2022-05-12 07:30:00, 2022-05-12 07:40:00) ... NaN NaN NaN NaN NaN \n", - "[2022-05-12 07:40:00, 2022-05-12 07:50:00) ... NaN NaN NaN NaN NaN \n", - "[2022-05-12 07:50:00, 2022-05-12 08:00:00) ... NaN NaN NaN NaN NaN \n", + "symbol ^FTSE \\\n", + " low open volume close high low \n", + "[2024-01-30 07:30:00, 2024-01-30 07:40:00) NaN NaN NaN NaN NaN NaN \n", + "[2024-01-30 07:40:00, 2024-01-30 07:50:00) NaN NaN NaN NaN NaN NaN \n", + "[2024-01-30 07:50:00, 2024-01-30 08:00:00) NaN NaN NaN NaN NaN NaN \n", "\n", - "symbol ^FTSE \\\n", - " close high \n", - "[2022-05-12 07:30:00, 2022-05-12 07:40:00) 7181.529785 7194.009766 \n", - "[2022-05-12 07:40:00, 2022-05-12 07:50:00) 7220.209961 7220.770020 \n", - "[2022-05-12 07:50:00, 2022-05-12 08:00:00) 7208.950195 7221.839844 \n", - "\n", - "symbol \n", - " low open volume \n", - "[2022-05-12 07:30:00, 2022-05-12 07:40:00) 7171.970215 7191.529785 0.0 \n", - "[2022-05-12 07:40:00, 2022-05-12 07:50:00) 7176.339844 7181.540039 0.0 \n", - "[2022-05-12 07:50:00, 2022-05-12 08:00:00) 7204.810059 7220.169922 0.0 \n", + "symbol \n", + " open volume \n", + "[2024-01-30 07:30:00, 2024-01-30 07:40:00) NaN NaN \n", + "[2024-01-30 07:40:00, 2024-01-30 07:50:00) NaN NaN \n", + "[2024-01-30 07:50:00, 2024-01-30 08:00:00) NaN NaN \n", "\n", "[3 rows x 50 columns]" ] }, - "execution_count": 7, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -323,14 +328,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Note that prices will show as missing for any instruments not trading over the requested period." + "Note that prices will show as not available for any instrument not trading over an index interval." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "## Calendars" + "### Calendars" ] }, { @@ -344,25 +349,25 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "{'MSFT': ,\n", - " 'AZN.L': ,\n", - " '9988.HK': ,\n", - " 'PETR3.SA': ,\n", - " '^FTSE': ,\n", - " 'ES=F': ,\n", - " 'CL=F': ,\n", - " 'GC=F': ,\n", - " 'GBPEUR=X': ,\n", - " 'BTC-USD': }" + "{'MSFT': ,\n", + " 'PETR3.SA': ,\n", + " 'BTC-USD': ,\n", + " '^FTSE': ,\n", + " 'GC=F': ,\n", + " '9988.HK': ,\n", + " 'ES=F': ,\n", + " 'AZN.L': ,\n", + " 'CL=F': ,\n", + " 'GBPEUR=X': }" ] }, - "execution_count": 8, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -375,25 +380,25 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "By default, requested periods are evaluated against the most common calendar (or if there is no single most common calendar then the calendar associated with the first symbol passed that's associated with one of the most common calendars).\n", + "By default, requested periods are evaluated against the most common calendar.\n", "\n", - "### `lead_symbol`\n", + "#### `lead_symbol`\n", "\n", "Alternatively, the default calendar can be set by passing the `lead_symbol` option to the Prices class. This will set the default calendar to the calendar associated with the passed symbol. In the example above `lead_symbol` was passed as '9988.HK', which is the symbol for Alibaba's Hong Kong listing." ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 9, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -413,7 +418,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -470,7 +475,7 @@ " \n", " \n", " \n", - " [2022-05-12 16:20:00, 2022-05-12 16:30:00)\n", + " [2024-01-30 20:50:00, 2024-01-30 21:00:00)\n", " NaN\n", " NaN\n", " NaN\n", @@ -482,11 +487,11 @@ " NaN\n", " NaN\n", " ...\n", - " 36.419998\n", - " 36.450001\n", - " 36.250000\n", - " 36.270000\n", - " 220200.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " NaN\n", " NaN\n", " NaN\n", @@ -494,7 +499,7 @@ " NaN\n", " \n", " \n", - " [2022-05-12 16:30:00, 2022-05-12 16:40:00)\n", + " [2024-01-30 21:00:00, 2024-01-30 21:10:00)\n", " NaN\n", " NaN\n", " NaN\n", @@ -506,11 +511,11 @@ " NaN\n", " NaN\n", " ...\n", - " 36.419998\n", - " 36.419998\n", - " 36.419998\n", - " 36.419998\n", - " 0.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " NaN\n", " NaN\n", " NaN\n", @@ -518,7 +523,7 @@ " NaN\n", " \n", " \n", - " [2022-05-12 16:40:00, 2022-05-12 16:50:00)\n", + " [2024-01-30 21:10:00, 2024-01-30 21:20:00)\n", " NaN\n", " NaN\n", " NaN\n", @@ -530,11 +535,11 @@ " NaN\n", " NaN\n", " ...\n", - " 36.419998\n", - " 36.419998\n", - " 36.419998\n", - " 36.419998\n", - " 0.0\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", + " NaN\n", " NaN\n", " NaN\n", " NaN\n", @@ -549,38 +554,32 @@ "text/plain": [ "symbol 9988.HK AZN.L \\\n", " close high low open volume close \n", - "[2022-05-12 16:20:00, 2022-05-12 16:30:00) NaN NaN NaN NaN NaN NaN \n", - "[2022-05-12 16:30:00, 2022-05-12 16:40:00) NaN NaN NaN NaN NaN NaN \n", - "[2022-05-12 16:40:00, 2022-05-12 16:50:00) NaN NaN NaN NaN NaN NaN \n", + "[2024-01-30 20:50:00, 2024-01-30 21:00:00) NaN NaN NaN NaN NaN NaN \n", + "[2024-01-30 21:00:00, 2024-01-30 21:10:00) NaN NaN NaN NaN NaN NaN \n", + "[2024-01-30 21:10:00, 2024-01-30 21:20:00) NaN NaN NaN NaN NaN NaN \n", "\n", - "symbol ... \\\n", - " high low open volume ... \n", - "[2022-05-12 16:20:00, 2022-05-12 16:30:00) NaN NaN NaN NaN ... \n", - "[2022-05-12 16:30:00, 2022-05-12 16:40:00) NaN NaN NaN NaN ... \n", - "[2022-05-12 16:40:00, 2022-05-12 16:50:00) NaN NaN NaN NaN ... \n", - "\n", - "symbol PETR3.SA \\\n", - " close high low \n", - "[2022-05-12 16:20:00, 2022-05-12 16:30:00) 36.419998 36.450001 36.250000 \n", - "[2022-05-12 16:30:00, 2022-05-12 16:40:00) 36.419998 36.419998 36.419998 \n", - "[2022-05-12 16:40:00, 2022-05-12 16:50:00) 36.419998 36.419998 36.419998 \n", + "symbol ... PETR3.SA \\\n", + " high low open volume ... close \n", + "[2024-01-30 20:50:00, 2024-01-30 21:00:00) NaN NaN NaN NaN ... NaN \n", + "[2024-01-30 21:00:00, 2024-01-30 21:10:00) NaN NaN NaN NaN ... NaN \n", + "[2024-01-30 21:10:00, 2024-01-30 21:20:00) NaN NaN NaN NaN ... NaN \n", "\n", "symbol ^FTSE \\\n", - " open volume close high \n", - "[2022-05-12 16:20:00, 2022-05-12 16:30:00) 36.270000 220200.0 NaN NaN \n", - "[2022-05-12 16:30:00, 2022-05-12 16:40:00) 36.419998 0.0 NaN NaN \n", - "[2022-05-12 16:40:00, 2022-05-12 16:50:00) 36.419998 0.0 NaN NaN \n", + " high low open volume close high \n", + "[2024-01-30 20:50:00, 2024-01-30 21:00:00) NaN NaN NaN NaN NaN NaN \n", + "[2024-01-30 21:00:00, 2024-01-30 21:10:00) NaN NaN NaN NaN NaN NaN \n", + "[2024-01-30 21:10:00, 2024-01-30 21:20:00) NaN NaN NaN NaN NaN NaN \n", "\n", "symbol \n", " low open volume \n", - "[2022-05-12 16:20:00, 2022-05-12 16:30:00) NaN NaN NaN \n", - "[2022-05-12 16:30:00, 2022-05-12 16:40:00) NaN NaN NaN \n", - "[2022-05-12 16:40:00, 2022-05-12 16:50:00) NaN NaN NaN \n", + "[2024-01-30 20:50:00, 2024-01-30 21:00:00) NaN NaN NaN \n", + "[2024-01-30 21:00:00, 2024-01-30 21:10:00) NaN NaN NaN \n", + "[2024-01-30 21:10:00, 2024-01-30 21:20:00) NaN NaN NaN \n", "\n", "[3 rows x 50 columns]" ] }, - "execution_count": 10, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -592,7 +591,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -625,28 +624,28 @@ " \n", " \n", " \n", - " [2022-05-12 16:20:00, 2022-05-12 16:30:00)\n", - " 29590.166016\n", - " 29590.166016\n", - " 29187.529297\n", - " 29187.529297\n", - " 673996800.0\n", + " [2024-01-30 20:50:00, 2024-01-30 21:00:00)\n", + " 43641.152344\n", + " 43651.898438\n", + " 43596.343750\n", + " 43617.265625\n", + " 101537792.0\n", " \n", " \n", - " [2022-05-12 16:30:00, 2022-05-12 16:40:00)\n", - " 29686.349609\n", - " 29761.673828\n", - " 29546.121094\n", - " 29546.121094\n", - " 777789440.0\n", + " [2024-01-30 21:00:00, 2024-01-30 21:10:00)\n", + " 43522.578125\n", + " 43604.261719\n", + " 43522.578125\n", + " 43571.070312\n", + " 53286912.0\n", " \n", " \n", - " [2022-05-12 16:40:00, 2022-05-12 16:50:00)\n", - " 29537.708984\n", - " 29617.484375\n", - " 29537.708984\n", - " 29617.484375\n", - " 0.0\n", + " [2024-01-30 21:10:00, 2024-01-30 21:20:00)\n", + " 43500.671875\n", + " 43500.671875\n", + " 43500.671875\n", + " 43500.671875\n", + " 11606016.0\n", " \n", " \n", "\n", @@ -654,22 +653,22 @@ ], "text/plain": [ " close high \\\n", - "[2022-05-12 16:20:00, 2022-05-12 16:30:00) 29590.166016 29590.166016 \n", - "[2022-05-12 16:30:00, 2022-05-12 16:40:00) 29686.349609 29761.673828 \n", - "[2022-05-12 16:40:00, 2022-05-12 16:50:00) 29537.708984 29617.484375 \n", + "[2024-01-30 20:50:00, 2024-01-30 21:00:00) 43641.152344 43651.898438 \n", + "[2024-01-30 21:00:00, 2024-01-30 21:10:00) 43522.578125 43604.261719 \n", + "[2024-01-30 21:10:00, 2024-01-30 21:20:00) 43500.671875 43500.671875 \n", "\n", " low open \\\n", - "[2022-05-12 16:20:00, 2022-05-12 16:30:00) 29187.529297 29187.529297 \n", - "[2022-05-12 16:30:00, 2022-05-12 16:40:00) 29546.121094 29546.121094 \n", - "[2022-05-12 16:40:00, 2022-05-12 16:50:00) 29537.708984 29617.484375 \n", + "[2024-01-30 20:50:00, 2024-01-30 21:00:00) 43596.343750 43617.265625 \n", + "[2024-01-30 21:00:00, 2024-01-30 21:10:00) 43522.578125 43571.070312 \n", + "[2024-01-30 21:10:00, 2024-01-30 21:20:00) 43500.671875 43500.671875 \n", "\n", " volume \n", - "[2022-05-12 16:20:00, 2022-05-12 16:30:00) 673996800.0 \n", - "[2022-05-12 16:30:00, 2022-05-12 16:40:00) 777789440.0 \n", - "[2022-05-12 16:40:00, 2022-05-12 16:50:00) 0.0 " + "[2024-01-30 20:50:00, 2024-01-30 21:00:00) 101537792.0 \n", + "[2024-01-30 21:00:00, 2024-01-30 21:10:00) 53286912.0 \n", + "[2024-01-30 21:10:00, 2024-01-30 21:20:00) 11606016.0 " ] }, - "execution_count": 11, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -689,31 +688,140 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### `calendars`\n", + "#### `calendars`\n", + "\n", + "A `CalendarError` is raised if `PricesYahoo` is unable to match a symbol with a calendar. In this case it's necessary to manually assign calendars to those symbols for which a calendar cannot be ascertained. This is done by passing the `calendars` option. The `calendars` option can also be passed to override, for any symbol(s), the default calendar(s) that would otherwise be assigned.\n", "\n", - "If a calendar cannot be ascertained for a symbol then a `CalendarError` is raised. In this case it's necessary to manually assign calendars to those symbols for which a calendar cannot be ascertained. This is done by passing the `calendars` option to the Prices class. The `calendars` option can also be passed to override, for any symbol(s), the default calendar(s) that would otherwise be assigned.\n", + "For the `PricesCsv` class `calendars` is a required argument in order that each symbol can be mapped to a corresponding calendar.\n", "\n", - "`calendars` can take an `ExchangeCalendar`, a `list` or a `dict`, as described by the `PricesYahoo` class documentation (see final cell of this tutorial)." + "`calendars` can take an `ExchangeCalendar`, a `list` or a `dict`, as described by the class documentation (see final cell of the `PricesYahoo` and `PricesCsv` sections of this tutorial)." ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "## `delays`" + "## `PricesYahoo`\n", + "\n", + "`PricesYahoo` has a couple of further optional arguments...\n", + "\n", + "### `delays`\n", + "\n", + "If a prices class can request 'live' prices then `market_prices` also requires knowledge of any real-time delay in the price data (this is in order to evaluate periods to 'now').\n", + "\n", + "By default, `PricesYahoo` attempts to evaluate the delay for each symbol via fields made available by the Yahoo API and some hardcoded mappings. A `ValueError` is raised if a delay cannot be ascertained for a symbol. In this case it's necessary to manually assign a delay via the `delays` kwarg. `delays` can also be passed to override the default delay that would otherwise be assigned to a specific symbol or symbols.\n", + "\n", + "(NB an inaccurately evaluated delay can have the effect that the latest real-time prices 'stick' rather than update on further requests, or that data is unavailable at the most recent time for which it would be expected to be available.)\n", + "\n", + "`delays` can take an `int`, a `list` or a `dict`, as described by the `PricesYahoo` class documentation.\n", + "\n", + "### `adj_close`\n", + "\n", + "The `adj_close` argument simply provides for setting daily close prices to the 'adjusted close' price available via the Yahoo API. By default (False) close prices represent the non-adjusted close.\n", + "\n", + "### `PricesYahoo` doc\n", + "See the `PricesYahoo` class doc for full documentation of all class parameters..." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# or PricesYahoo?\n", + "help(PricesYahoo)" ] }, { + "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "For each symbol `market_prices` also requires knowledge of any real-time delay in the price data (this is in order to evaluate periods to 'now').\n", + "## `PricesCsv`\n", "\n", - "By default, PricesYahoo attempts to evaluate the delay for each symbol via fields made available by the Yahoo API and some hardcoded mappings. A `ValueError` is raised if a delay cannot be ascertained for a symbol. In this case it's necessary to manually assign a delay via the `delays` kwarg. `delays` can also be passed to override the default delay that would otherwise be assigned to a specific symbol or symbols.\n", + "The `PricesCsv` class provides for retrieving and serving prices data stored in locally saved .csv files.\n", "\n", - "(NB an inaccurately evaluated delay can have the effect that the latest real-time prices 'stick' rather than update on further requests, or that data is unavailable at the most recent time for which it would be expected to be available.)\n", + "The following example uses example .csv files that are copies of files used for testing. The raised warnings offer examples of the types of advices offered when there are issues with the .csv files. (Note: this example requries that the .csv files are located in a directory named 'resources' located in the same folder as this tutorial file. The .csv files can be found [here](https://github.com/maread99/market_prices/tree/master/docs/tutorials/resources).)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "import pathlib, os\n", + "path = pathlib.Path(os.path.abspath('')) / \"resources\"\n", + "assert path.is_dir()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "calendars = {\n", + " \"MSFT\": \"XNYS\",\n", + " \"AZN.L\": \"XLON\",\n", + " \"9988.HK\": \"XHKG\",\n", + "}\n", + "\n", + "prices = PricesCsv(\n", + " path,\n", + " symbols=list(calendars.keys()),\n", + " calendars=calendars,\n", + " lead_symbol = \"AZN.L\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```\n", + "PricesCsvParsingConsolidatedWarning: Price data has been found for all symbols at a least one interval, however, you may find that not all the expected price data is available. See the `limits` property for available base intervals and the limits between which price data is available at each of these intervals. See the `csv_paths` property for paths to all csv files that were found for the requested symbols. See the 'path' parameter and 'Notes' sections of help(PricesCsv) for advices on how csv files should be named and formatted and for use of the `read_csv_kwargs` parameter.\n", + "\n", + "The following errors and/or warnings occurred during parsing:\n", + "\n", + "0) Unable to create dataframe from csv file at 'f_AZN.L_H1_fails_on_vol_dtype.csv' due to the following error:\n", + "\t 'volume' column will not convert to 'float64' dtype.\n", + "The source error's message was:\n", + "\t: could not convert string to float: 'not a volume'\n", + "\n", + "1) Unable to create dataframe from csv file at 'f_AZN.L_H1_fails_on_vol_dtype.csv' due to the following error:\n", + "\t Date indices do not reflect the expected interval.\n", + "\n", + "2) Unable to create dataframe from csv file at 'f_MSFT_H1_fails_on_no_data.csv' due to the following error:\n", + "\t No price data parsed from csv file.\n", + "\n", + "3) Unable to create dataframe from csv file at 'f_MSFT_H1_fails_on_no_data.csv' due to the following error:\n", + "\t Date indices do not reflect the expected interval.\n", "\n", - "`delays` can take an `int`, a `list` or a `dict`, as described by the `PricesYahoo` class documentation..." + "4) Prices are not available at base interval 1:00:00 as data was not found at this interval for symbols '['AZN.L', 'MSFT']'.\n", + "\n", + "5) For symbol 'MSFT' at base interval 0:05:00 the csv file included the following indices that are not aligned with the evaluated index and: have therefore been ignored:\n", + "DatetimeIndex(['2022-04-18 16:02:00+00:00'], dtype='datetime64[ns, UTC]', freq=None)\n", + " warnings.warn(\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In addition to the parameters passed in the example above:\n", + "- `read_csv_kwargs` provides for defining arguments to pass to `pandas.read_csv` in order to customise parsing of data from the .csv files.\n", + "- `ohlc_thres` defines a threshold that determines the degree of incongruent data that will be accepted in a .csv file.\n", + "- `pm_subsession_origin` declares how price data for exchanges with breaks is indexed.\n", + "- `verbose` provides for including underlying error messages with any warnings (default False).\n", + "\n", + "Note that as the `PricesCsv` does not provide for live prices, there is no `delays` argument.\n", + "\n", + "### `PricesCsv` doc\n", + "See the `PricesCsv` class doc for full documentation of all parameters together with **how .csv files should be arranged and named...**" ] }, { @@ -722,16 +830,297 @@ "metadata": {}, "outputs": [], "source": [ - "# or PricesYahoo?\n", - "help(PricesYahoo)" + "# or PricesCsv?\n", + "help(PricesCsv)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "```\n", + "Help on class PricesCsv in module market_prices.prices.csv:\n", + "\n", + "class PricesCsv(market_prices.prices.base.PricesBase)\n", + " | PricesCsv(path: 'Annotated[Union[str, Path], Coerce(Path)]', symbols: 'Union[str, list[str]]', calendars: 'mptypes.Calendars', lead_symbol: 'Optional[str]' = None, read_csv_kwargs: 'Optional[dict[str, Any]]' = None, ohlc_thres: 'float' = 0.08, pm_subsession_origin: \"Literal['open', 'break_end']\" = 'open', verbose: 'bool' = False)\n", + " | \n", + " | Retrieve and serve historic price data sourced from local csv files.\n", + " | \n", + " | Parameters\n", + " | ----------\n", + " | path : str | pathlib.Path\n", + " | Path to directory containing .csv files and/or a hierarchy of\n", + " | subdirectories containing .csv files. Files and folders should\n", + " | conform with requirements detailed here and to the 'Notes' section.\n", + " | \n", + " | The constructor will search for .csv files in this directory and\n", + " | all directories under it. All files without the .csv extension will\n", + " | be ignored.\n", + " | \n", + " | Each csv file must contain data for a single symbol and for a\n", + " | single interval. The symbol and interval should be included within\n", + " | the filename and separated from each other and/or any other parts\n", + " | of the filename with a '_' separator. The following are examples\n", + " | of valid filenames:\n", + " | MSFT_5T.csv\n", + " | 5T_MSFT.csv\n", + " | whatever_MSFT_5T.csv\n", + " | MSFT_5T_whatever.csv\n", + " | whatever_MSFT_5T_whatever.csv\n", + " | whatever_MSFT_whatever_5T_whatever.csv\n", + " | whatever_whatever_5T_whatever_MSFT_whatever.csv\n", + " | \n", + " | The interval part expresses the duration of the period corresonding\n", + " | with each row of data. The interval comprises two parts, a unit and\n", + " | a value. Valid units are:\n", + " | MIN - to describe mintues\n", + " | T - to describe mintues\n", + " | H - to describe hours\n", + " | D - to describe hours\n", + " | Units are not case-sensitive, for example T, t, Min, MIN and mIN\n", + " | are all valid units.\n", + " | \n", + " | The interval value defines the mulitple of units, for example '5T'\n", + " | defines the interval as 5 minutes. If the value is omitted then it\n", + " | will be assumed as 1, for example 'MSFT_T.csv' will be assumed to\n", + " | contain 1 minute data for MSFT.\n", + " | \n", + " | The value for daily data cannot be higher than 1, i.e. there is no\n", + " | support for weekly or monthly data. (Whilst the `get` method\n", + " | supports requests for weekly or monthly data, the request is\n", + " | fulfilled by resampling daily data.)\n", + " | \n", + " | The interval can optionally be omitted for daily data, for example\n", + " | all of 'MSFT.csv', 'MSFT_1D' and 'MSFT_D' will be assumed as\n", + " | containing daily data for MSFT.\n", + " | \n", + " | The following are all examples of valid filenames:\n", + " | 5T_MSFT.csv\n", + " | other_5t_MSFT_123.csv\n", + " | MSFT_t_231116 MSFT.csv (assumed as minute data)\n", + " | MSFT_something_else.csv (assumed as daily data)\n", + " | \n", + " | Any files containing malformed intervals will be ignored.\n", + " | \n", + " | The following are examples of invalid filenames that will result in\n", + " | the file being ignored:\n", + " | MSFT_p5T_else.csv (malformed interval)\n", + " | MSFT_5T_15T,csv (ambiguous interval)\n", + " | MSFT_5T_TSLA.csv (two symbols)\n", + " | MSFT_2D.csv (if interval unit is day then value cannot be\n", + " | greater than one)\n", + " | MSFT.txt (not a .csv file)\n", + " | \n", + " | The `csv_paths` property shows all the csv files that have been\n", + " | included, by symbol by interval.\n", + " | \n", + " | symbols : str | list[str]\n", + " | Symbols for which require price data. For example:\n", + " | 'AMZN'\n", + " | 'FB AAPL AMZN NFLX GOOG MSFT'\n", + " | ['FB', 'AAPL', 'AMZN']\n", + " | \n", + " | calendars :\n", + " | mptypes.Calendar |\n", + " | list[myptypes.Calendar] |\n", + " | dict[str, mytypes.Calendar]\n", + " | \n", + " | Calendar(s) defining trading times and timezones for `symbols`.\n", + " | \n", + " | A single calendar representing all `symbols` can be passed as\n", + " | an mptype.Calendar, specifically any of:\n", + " | Instance of a subclass of\n", + " | `exchange_calendars.ExchangeCalendar`. Calendar 'side' must\n", + " | be \"left\".\n", + " | \n", + " | `str` of ISO Code of an exchange for which the\n", + " | `exchange_calendars` package maintains a calendar. See\n", + " | https://github.com/gerrymanoim/exchange_calendars#calendars\n", + " | or call market_prices.get_exchange_info`. For example:\n", + " | calendars=\"XLON\",\n", + " | \n", + " | `str` of any other calendar name supported by\n", + " | `exchange_calendars`, as returned by\n", + " | `exchange_calendars.get_calendar_names`\n", + " | \n", + " | Multiple calendars, each representing one or more symbols, can\n", + " | be passed as any of:\n", + " | List of mptypes.Calendar (i.e. defined as for a single\n", + " | calendar). List should have same length as `symbols` with each\n", + " | element relating to the symbol at the corresponding index.\n", + " | \n", + " | Dictionary mapping each symbol with a calendar.\n", + " | key: str\n", + " | symbol.\n", + " | value: mptypes.Calendar (i.e. as for a single calendar)\n", + " | Calendar corresponding with symbol.\n", + " | \n", + " | For example:\n", + " | calendars = {\"MSFT\": \"XNYS\", \"AZN.L\": \"XLON\"}\n", + " | \n", + " | Each Calendar should have a first session no later than the first\n", + " | session from which prices are available for any symbol\n", + " | corresponding with that calendar.\n", + " | \n", + " | lead_symbol : str\n", + " | Symbol with calendar that should be used as the default calendar to\n", + " | evaluate period from period parameters. If not passed default\n", + " | calendar will be defined as the most common calendar (and if there\n", + " | is no single most common calendar then the calendar associated\n", + " | with the first symbol passed that's associated with one of the most\n", + " | common calendars).\n", + " | \n", + " | read_csv_kwargs : Optional[dict[str, Any]]\n", + " | Keyword argumnets to pass to `pandas.read_csv` to parse a csv file\n", + " | to a pandas DataFrame. See the 'Notes' section for how a csv file\n", + " | can be formatted such that it parses under the default\n", + " | implementation.\n", + " | \n", + " | market_prices requires that the DataFrame parses with:\n", + " | index as a `pd.DatetimeIndex` named 'date'.\n", + " | \n", + " | columns labelled 'open', 'high', 'low', 'close' and optionally\n", + " | 'volume', each with dtype \"float64\".\n", + " | \n", + " | If the following kwargs are not included to `read_csv_kwargs` then\n", + " | by default they will be passed to `pandas.read_csv` with the\n", + " | following values:\n", + " | \"header\": 0,\n", + " | \"usecols\": lambda x: x.lower() in [\n", + " | \"date\", \"open\", \"high\", \"low\", \"close\", \"volume\"\n", + " | ],\n", + " | \"index_col\": \"date\",\n", + " | \"parse_dates\": [\"date\"],\n", + " | \n", + " | See help(pandas.read_csv) for all available kwargs.\n", + " | \n", + " | Note that the following arguments will always be passed by\n", + " | market_prices to `pandas.read_csv` with the following values (these\n", + " | values cannot be overriden by `read_csv_kwargs`):\n", + " | \"filepath_or_buffer\": \n", + " | \"dtype\": {\n", + " | 'open': \"float64\",\n", + " | 'high': \"float64\",\n", + " | 'low': \"float64\",\n", + " | 'close': \"float64\",\n", + " | }\n", + " | \n", + " | EXAMPLE USAGE\n", + " | If in the csv files the:\n", + " | date column is labelled 'timestamp'\n", + " | close column is labelled 'price'\n", + " | volume column is labelled 'vol'\n", + " | Then the `names` kwarg can be used to override the labels that\n", + " | would otherwise be assigned to each column. If the columns in the\n", + " | csv file were ordered 'timestamp', 'price', 'low', 'high', 'open',\n", + " | 'vol' then `read_csv_kwargs` could be passed as:\n", + " | read_csv_kwargs = {\n", + " | \"names\": ['date', 'close', 'low', 'high', 'open', 'volume'],\n", + " | }\n", + " | This would override the names as defined in the csv file's first\n", + " | row with the required values. Note that all references to column\n", + " | names in other kwargs, such as 'usecols' and 'dtype', will now\n", + " | refer to the overridden names (as required), not the names as\n", + " | defined in the csv files.\n", + " | \n", + " | ohlc_thres : float, default: 0.08\n", + " | Threshold to reject incongruent ohlc data, in terms of maximum\n", + " | percentage of incongrument rows to permit. For example, pass as 0.1\n", + " | to reject data if more than 10% of rows exhibit incongruent data.\n", + " | \n", + " | If the number of incongruent rows are below the threshold then\n", + " | adjustements will be made to force congruence.\n", + " | \n", + " | A row of data will be considered incongruent if any of:\n", + " | close is higher than high\n", + " | within threshold, high will be forced to close\n", + " | close is lower than low\n", + " | within threshold, low will be forced to close\n", + " | open is lower than low\n", + " | within threshold, open will be forced to low\n", + " | open is higher than high\n", + " | within threshold, open will be forced to high\n", + " | \n", + " | Note: Data will always be rejected if any row has a high value\n", + " | lower than the low value. No provision is made to permit this\n", + " | circumstance.\n", + " | \n", + " | pm_subsession_origin : Literal[\"open\", \"break_end\"], default: \"open\"\n", + " | How to evaluate indices of sessions that include a break. (The\n", + " | 'Notes' covers how, in order to offer a complete data set, prices\n", + " | are reindexed against an index evaluated in accordance with the\n", + " | corresponding calendar. This parameter determines the basis on\n", + " | which that index is evaluated for sessions that have a break.)\n", + " | \n", + " | 'open' - evaluate all indices for a session based on the session\n", + " | open. If the session open and pm subsession open are not aligned\n", + " | then indices will be included through the break (i.e. treat as if\n", + " | the session did not have a break).\n", + " | \n", + " | 'break_end' - evaluate indices for the am subsession based on the\n", + " | session open and indices for the pm subsession based on the\n", + " | pm subsession open (i.e. based on the break end). No indices will\n", + " | be included that would fall during the break.\n", + " | \n", + " | verbose : bool, default: False\n", + " | Within error and warning messages concerning the parsing of csv\n", + " | files, include the full traceback of any underlying errors.\n", + " | \n", + " | Notes\n", + " | -----\n", + " | By default csv files should have headers in the first line that include\n", + " | 'date', 'open', 'high', 'low', 'close' and optionally 'volume'. Each\n", + " | further line should represent a single period starting on the value in\n", + " | 'date' column and lasting a period corresponding with the interval\n", + " | declared in the filename. It is NOT necessary for every period to be\n", + " | represented (it's common for data sources to exclude intraday data for\n", + " | periods during which a symbol did not register a trade). The price data\n", + " | will be reindexed against expected indices as evaluated from the\n", + " | corresponding calendar of `calendars`.\n", + " | \n", + " | For daily price data values in the 'date' column should represent a\n", + " | date, for example '2023-11-16'.\n", + " | \n", + " | For intraday price data the values in the 'date' column should express\n", + " | either:\n", + " | a date and UTC time, for example '2023-11-16 15:30' or\n", + " | '2023-11-16 15:30:00'\n", + " | \n", + " | a date, local time and GMT offset for that local time, for example\n", + " | '2023-11-16 12:53:00-04:00'\n", + " | \n", + " | If the csv does not confrom with the above then the `read_csv_kwargs`\n", + " | parameter can be passed to define paramters to pass to\n", + " | `pandas.read_csv_kwargs` in order to parse the file as required.\n", + " | \n", + " | -- Alignment of Intraday 'date' values --\n", + " | Intraday 'date' values can define the time of a (sub)session open\n", + " | (according to the corresopnding calendar) and any time thereafter which\n", + " | is aligned with the interval, based on the (sub)session open, and which\n", + " | falls before the corresonding (sub)session close. See the\n", + " | `pm_subsession_origin` parameter for how to determine how indices are\n", + " | evaluated for sessions that include a break.\n", + " | \n", + " | Examples\n", + " | If a session opens at 10:00 and the interval is 15T then\n", + " | '2023-11-16 10:00' is a valid value and so is '2023-11-16 10:15',\n", + " | although '2023-11-16 10:10' is not as it does not align with the\n", + " | declared interval. All unaligned indices will be ignored.\n", + " | \n", + " | If the same session closes at 17:00 then the latest valid value for\n", + " | that session will be '2023-11-16 16:45'. '2023-11-16 17:00' is not\n", + " | valid as it would represent a period outside of trading hours, i.e. the\n", + " | 15 minutes following the session close. All values that lie outside of\n", + " | regular trading hours will be ignored.\n", + " ```" ] } ], "metadata": { "kernelspec": { - "display_name": "Python38 mkt_prices_venv", + "display_name": "market_prices_ve_39", "language": "python", - "name": "38mp_venv" + "name": "market_prices_ve_39" }, "language_info": { "codemirror_mode": { @@ -743,7 +1132,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.9.13" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/docs/tutorials/resources/9988.HK_D1.csv b/docs/tutorials/resources/9988.HK_D1.csv new file mode 100644 index 0000000..7abdf26 --- /dev/null +++ b/docs/tutorials/resources/9988.HK_D1.csv @@ -0,0 +1,629 @@ +date,open,high,low,close,volume +2019-11-26,187.0,189.5,187.0,187.60000610351562,74549578 +2019-11-27,190.0,195.3000030517578,189.3000030517578,193.1999969482422,53617241 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16:25:00+00:00,250.5800018310547,250.5800018310547,250.19000244140625,250.22000122070312,211927 +2022-06-15 16:30:00+00:00,250.2100067138672,250.5,250.11000061035156,250.15499877929688,170872 +2022-06-15 16:35:00+00:00,250.16000366210938,250.35000610351562,249.9600067138672,249.97000122070312,120091 +2022-06-15 16:40:00+00:00,249.97999572753906,250.02999877929688,249.5399932861328,249.58999633789062,147957 +2022-06-15 16:45:00+00:00,249.58999633789062,249.60000610351562,249.38999938964844,249.49960327148438,138852 +2022-06-15 16:50:00+00:00,249.47000122070312,249.51499938964844,249.38999938964844,249.4550018310547,29318 diff --git a/docs/tutorials/resources/f_MSFT_H1_fails_on_no_data.csv b/docs/tutorials/resources/f_MSFT_H1_fails_on_no_data.csv new file mode 100644 index 0000000..ba9ce49 --- /dev/null +++ b/docs/tutorials/resources/f_MSFT_H1_fails_on_no_data.csv @@ -0,0 +1,2 @@ +date,open,high,low,close,volume +2020-06-15 17:30:00+00:00,,,,, diff --git a/docs/tutorials_docs.md b/docs/tutorials_docs.md index 433e436..f532974 100644 --- a/docs/tutorials_docs.md +++ b/docs/tutorials_docs.md @@ -13,7 +13,7 @@ To get a good appreciation of what `market_prices` offers and how it works it's These tutorials covers all aspects of the Prices classes `get` method which is used to get a prices dataset. * [**prices.ipynb**](./tutorials/prices.ipynb) - * Create a prices object from `PricesYahoo`. + * Create a prices object from `PricesYahoo` or `PricesCsv`. * [**intervals.ipynb**](./tutorials/intervals.ipynb) * Define the time interval represented by each row of a prices table. * [**periods.ipynb**](./tutorials/periods.ipynb) diff --git a/src/market_prices/__init__.py b/src/market_prices/__init__.py index 7c61e01..27ae9f4 100644 --- a/src/market_prices/__init__.py +++ b/src/market_prices/__init__.py @@ -1,9 +1,10 @@ """Market Prices.""" from .prices.yahoo import PricesYahoo +from .prices.csv import PricesCsv from .utils.calendar_utils import get_exchange_info -__all__ = [PricesYahoo, get_exchange_info] +__all__ = [PricesYahoo, PricesCsv, get_exchange_info] __copyright__ = "Copyright (c) 2022 Marcus Read" diff --git a/src/market_prices/daterange.py b/src/market_prices/daterange.py index 80fc3cd..cac0094 100644 --- a/src/market_prices/daterange.py +++ b/src/market_prices/daterange.py @@ -76,9 +76,9 @@ def __init__( # pylint: disable=too-many-arguments pp: mptypes.PP | None = None, ds_interval: intervals.PTInterval | None = None, strict=True, - limit_right: pd.Timestamp - | Callable[[intervals.BI], pd.Timestamp | None] - | None = None, + limit_right: ( + pd.Timestamp | Callable[[intervals.BI], pd.Timestamp | None] | None + ) = None, ): self._cal = calendar self._limit = limit @@ -728,9 +728,9 @@ def __init__( # pylint: disable=too-many-arguments anchor: mptypes.Anchor = mptypes.Anchor.OPEN, end_alignment: mptypes.Alignment = mptypes.Alignment.BI, strict: bool = True, - limit_right: pd.Timestamp - | Callable[[intervals.BI], pd.Timestamp | None] - | None = None, + limit_right: ( + pd.Timestamp | Callable[[intervals.BI], pd.Timestamp | None] | None + ) = None, ): self._cc = composite_calendar self._delay = delay diff --git a/src/market_prices/prices/csv.py b/src/market_prices/prices/csv.py index 10763ce..5f45c81 100644 --- a/src/market_prices/prices/csv.py +++ b/src/market_prices/prices/csv.py @@ -336,7 +336,7 @@ def str_inc_orig(self, verbose: bool = False) -> str: try: raise self.source - except: + except Exception: msg += f"\nThe source error's traceback was:\n{traceback.format_exc()}"[:-2] return msg @@ -910,9 +910,10 @@ class PricesCsv(base.PricesBase): lead_symbol : str Symbol with calendar that should be used as the default calendar to evaluate period from period parameters. If not passed default - calendar will be defined as the most common calendar (and if more - than one calendar is the most common then of those the the calendar - that's defined 'first' in the list or dictionary). + calendar will be defined as the most common calendar (and if there + is no single most common calendar then the calendar associated + with the first symbol passed that's associated with one of the most + common calendars). read_csv_kwargs : Optional[dict[str, Any]] Keyword argumnets to pass to `pandas.read_csv` to parse a csv file @@ -1220,7 +1221,7 @@ def csv_paths(self) -> dict[str, dict[TDInterval, Path]]: def _request_data( self, - interval: BI, + interval: intervals.BI, start: pd.Timestamp | None, end: pd.Timestamp, ) -> pd.DataFrame: diff --git a/tests/test_base.py b/tests/test_base.py index 3f0f097..f7a5d59 100644 --- a/tests/test_base.py +++ b/tests/test_base.py @@ -909,9 +909,7 @@ def left_limits() -> abc.Iterator[dict[intervals.TDInterval, pd.Timestamp]]: @pytest.fixture -def prices_mock_base_intervals( - daily_limit, right_limits, left_limits -) -> abc.Iterator[ +def prices_mock_base_intervals(daily_limit, right_limits, left_limits) -> abc.Iterator[ tuple[ type[intervals._BaseInterval], dict[intervals._BaseInterval, pd.Timedelta | pd.Timestamp], @@ -961,9 +959,7 @@ def prices_mock_base_intervals( @pytest.fixture -def prices_mock_base_intervals_intraday_only( - left_limits, right_limits -) -> abc.Iterator[ +def prices_mock_base_intervals_intraday_only(left_limits, right_limits) -> abc.Iterator[ tuple[ type[intervals._BaseInterval], dict[intervals._BaseInterval, pd.Timedelta], @@ -1007,9 +1003,7 @@ def prices_mock_base_intervals_intraday_only( @pytest.fixture -def prices_mock_base_intervals_daily_only( - daily_limit, right_limits -) -> abc.Iterator[ +def prices_mock_base_intervals_daily_only(daily_limit, right_limits) -> abc.Iterator[ tuple[ type[intervals._BaseInterval], dict[intervals._BaseInterval, pd.Timestamp], @@ -1186,8 +1180,9 @@ class GetterMock_(daterange.GetterIntraday): def __init__( self, - daterange: tuple[tuple[pd.Timestamp, pd.Timestamp], pd.Timestamp] - | None = None, + daterange: ( + tuple[tuple[pd.Timestamp, pd.Timestamp], pd.Timestamp] | None + ) = None, daterange_sessions: tuple[pd.Timestamp, pd.Timestamp] | None = None, interval: intervals.BI | None = None, calendar: xcals.ExchangeCalendar | None = None, diff --git a/tests/test_base_prices.py b/tests/test_base_prices.py index 4c9c22e..e325982 100644 --- a/tests/test_base_prices.py +++ b/tests/test_base_prices.py @@ -86,8 +86,8 @@ def get_tst_symbol_for_calendar(name: str) -> str: name Name of calendar for which require a test symbol. """ - for symb, data in TST_SYMBOLS.items(): - if data.calendar == name: + for symb, data_ in TST_SYMBOLS.items(): + if data_.calendar == name: return symb raise ValueError(f"There is no test symbol for a calendar with name {name}.") @@ -143,9 +143,9 @@ def __init__( prices_tables: dict[str, pd.DataFrame], lead_symbol: str | None = None, recon_symbols: bool = True, - calendars: list[xcals.ExchangeCalendar] - | dict[str, xcals.ExchangeCalendar] - | None = None, + calendars: ( + list[xcals.ExchangeCalendar] | dict[str, xcals.ExchangeCalendar] | None + ) = None, delays: list[int] | dict[str, int] | None = None, ): self._prices_tables = prices_tables diff --git a/tests/test_csv.py b/tests/test_csv.py index 79ba558..afb7170 100644 --- a/tests/test_csv.py +++ b/tests/test_csv.py @@ -22,7 +22,7 @@ RESOURCES_PATH, get_resource_pbt, ) - + @pytest.fixture def csv_dir() -> abc.Iterator[Path]: diff --git a/tests/test_daterange.py b/tests/test_daterange.py index 327fc8d..6df72c4 100644 --- a/tests/test_daterange.py +++ b/tests/test_daterange.py @@ -1035,9 +1035,9 @@ def get_drg( anchor: Anchor = Anchor.OPEN, end_alignment: Alignment = Alignment.BI, strict: bool = True, - limit_right: pd.Timestamp - | abc.Callable[[intervals.BI], pd.Timestamp | None] - | None = None, + limit_right: ( + pd.Timestamp | abc.Callable[[intervals.BI], pd.Timestamp | None] | None + ) = None, ) -> m.GetterIntraday: """Get m.GetterIntraday with default arguments unless otherwise passed.""" if composite_calendar is None: @@ -2452,8 +2452,8 @@ def test_daterange_add_a_row_errors( drg = self.get_drg(cal, pp, strict=True, **drg_kwargs) match = ( - f"Prices unavailable as start evaluates to \d\d\d\d-\d\d-\d\d \d\d:\d\d UTC" - " which is earlier than the earliest minute for which price data is" + rf"Prices unavailable as start evaluates to \d\d\d\d-\d\d-\d\d \d\d:\d\d" + " UTC which is earlier than the earliest minute for which price data is" f" available. The earliest minute for which prices are available is" f" {helpers.fts(limit)}.\nNB The evaluated start falls earlier than first" " available minute due only to 'add_a_row=True'." diff --git a/tests/test_parsing.py b/tests/test_parsing.py index 8d2e3b0..8ce3964 100644 --- a/tests/test_parsing.py +++ b/tests/test_parsing.py @@ -700,9 +700,7 @@ class StartEnd: expected_as_time: pd.Timestamp @pytest.fixture - def f_starts_ends( - self, f_with_ans, one_min, today - ) -> abc.Iterator[ + def f_starts_ends(self, f_with_ans, one_min, today) -> abc.Iterator[ tuple[ Callable, list[tuple[pd.Timestamp, pd.Timestamp, pd.Timestamp]], diff --git a/tests/test_yahoo.py b/tests/test_yahoo.py index 9c570ad..4c4ef47 100644 --- a/tests/test_yahoo.py +++ b/tests/test_yahoo.py @@ -16,7 +16,7 @@ import yahooquery as yq import market_prices.prices.yahoo as m -from market_prices import data, daterange, helpers, intervals, errors +from market_prices import daterange, helpers, intervals, errors from market_prices.helpers import UTC from market_prices.support import tutorial_helpers as th from market_prices.utils import calendar_utils as calutils diff --git a/tests/utils.py b/tests/utils.py index 8c2ab2c..d7ffaa3 100644 --- a/tests/utils.py +++ b/tests/utils.py @@ -261,7 +261,6 @@ def get_resource_pbt(key: str) -> tuple[dict[str, pd.DataFrame], pd.Timstamp]: # functions to administer _temp folder TEMP_DIR = TEST_ROOT / r"./_temp" -assert TEMP_DIR.is_dir() ENCODING = "utf-8"