QuantRocket

https://www.quantrocket.com/docs
Admin
QuantRocket is an open-source platform for algorithmic trading, backtesting, and quantitative...
Tokens:785,451
Snippets:2,281
Trust Score:8.5
Update:5 months ago
Show doc for...
Tokens:
Raw
### Create Bundle from History DB (Example 1)

Source: https://www.quantrocket.com/docs/api

Example of creating a Zipline bundle from a history database named 'es-fut-1min'. It specifies the calendar and start date for the data.

```bash
quantrocket zipline create-bundle-from-db es-fut-1min --from-db es-fut-1min --calendar us_futures --start-date 2015-01-01
```

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

### Custom Setup Script for Satellite

Source: https://www.quantrocket.com/docs

Create a `quantrocket.satellite.setup.sh` script in `/codeload` for advanced setup tasks. The script is executed by the satellite service upon container startup. It supports package installations and configuration.

```bash
#!/bin/bash

# bail on errors
set -e

# Install gsutil https://cloud.google.com/storage/docs/gsutil_install
echo "deb [signed-by=/usr/share/keyrings/cloud.google.gpg] https://packages.cloud.google.com/apt cloud-sdk main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
apt-get install -y apt-transport-https ca-certificates gnupg
curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key --keyring /usr/share/keyrings/cloud.google.gpg add -
apt-get update && apt-get install -y google-cloud-sdk

# https://cloud.google.com/storage/docs/gsutil_install#authenticate
gcloud config set pass_credentials_to_gsutil false

# Install boto3 and aws cli
pip install boto3==1.12.7 awscli
```

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

### Get Account Balances Example URI

Source: https://www.quantrocket.com/docs/api

Example URI for querying account balances. Specify output format, date range, accounts, and optional filters like 'below' or 'fields'. Use 'force_refresh' to ensure the latest data.

```http
GET http://houston/account/balances.csv?start_date=2017-01-01&end_date=2018-01-01&latest=true&accounts=U123456&below=Cushion:0.05&fields=NetLiquidation&force_refresh=true
```

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

### Install Custom Python Packages

Source: https://www.quantrocket.com/docs

Create a `quantrocket.satellite.pip.txt` file in `/codeload` to specify Python packages for installation. Each package should be on a new line. Packages are installed using pip.

```text
beautifulsoup4
docopt==0.6.1
```

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

### Universe Management Examples

Source: https://www.quantrocket.com/docs/api?http=

Examples demonstrating how to download stock data, create, append to, and copy universes with specific criteria.

```APIDOC
## Universe Management Examples

### Description
Examples demonstrating how to download stock data, create, append to, and copy universes with specific criteria.

### Examples

Download a CSV of Italian stocks then upload it to create a universe called “italy-stk”:
```
quantrocket master get --exchanges BVME --sec-types STK -f italy.csv
quantrocket master universe "italy-stk" -f italy.csv
```

In one line, download a CSV of all ARCA ETFs and append to a universe called “arca-etf”:
```
quantrocket master get --exchanges ARCA --sec-types ETF | quantrocket master universe "arca-etf" --append --infile -
```

Create a universe consisting of several existing universes:
```
quantrocket master universe "asx" --from-universes "asx-sml" "asx-mid" "asx-lrg"
```

Copy a universe but exclude delisted securities:
```
quantrocket master universe "hong-kong-active" --from-universes "hong-kong" --exclude-delisted
```
```

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

### Get Account Portfolio Example URI

Source: https://www.quantrocket.com/docs/api

Example URI for downloading account portfolio data. Filter by brokers, accounts, security types, exchanges, sids, symbols, and include zero positions. Specify desired fields.

```http
GET http://houston/account/portfolio.csv?brokers=ibkr&accounts=U12345&sec_types=STK&exchanges=XNYS&sids=FI12345&symbols=AAPL&include_zero=true&fields=Sid
```

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

### Install QuantRocket Client

Source: https://www.quantrocket.com/docs

Install the quantrocket-client using pip. Ensure the MAJOR.MINOR version matches your deployment.

```bash
$ pip install 'quantrocket-client'
```

```bash
$ pip install 'quantrocket-client>=2.1,<2.2'
```

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

### quantrocket ibg start

Source: https://www.quantrocket.com/docs/api

Starts the IB Gateway service using the QuantRocket CLI.

```APIDOC
## quantrocket ibg start

### Description
Starts the IB Gateway service using the QuantRocket CLI.

### Command
`quantrocket ibg start`

### Usage
```bash
quantrocket ibg start [-h]
```
```

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

### Start Specific IB Gateway via CLI

Source: https://www.quantrocket.com/docs

Start a particular IB Gateway service using the `--gateways` parameter with the `quantrocket ibg start` command.

```bash
$ quantrocket ibg start --gateways 'ibg2'
status: the gateways will be started asynchronously
```

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

### Daily Returns Example

Source: https://www.quantrocket.com/docs/api

Example of daily returns data format for strategy performance analysis.

```python
2015-07-16    -0.012143
2015-07-17    0.045350
2015-07-20    0.030957
2015-07-21    0.004902

```

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

### Clone QuantRocket Demo Repository

Source: https://www.quantrocket.com/docs/api

Clones the 'umd' demo repository provided by QuantRocket. This is a simple way to get started with example code.

```bash
quantrocket codeload clone umd
```

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

### Install Custom Linux Packages

Source: https://www.quantrocket.com/docs

Create a `quantrocket.satellite.apt.txt` file in `/codeload` to list Linux packages for installation via `apt-get`. Each package should be on a new line.

```text
procps
r-base
```

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

### Get Installed Crontab

Source: https://www.quantrocket.com/docs

Retrieve the currently installed crontab from the countdown service using the client or HTTP API.

```shell
$ quantrocket countdown crontab
```

```python
>>> from quantrocket.countdown import get_crontab
>>> get_crontab()
```

```shell
$ curl -X GET 'http://houston/countdown/crontab'
```

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

### Start IB Gateway and Collect Data (CLI)

Source: https://www.quantrocket.com/docs

Use the CLI to start the IB Gateway and then begin collecting real-time market data for a specified tick database.

```bash
$ quantrocket ibg start --wait
ibg1:
  status: running
$ quantrocket realtime collect 'fang-stk-tick'
status: the market data will be collected until canceled
```

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

### Get Exchange Status Example URI

Source: https://www.quantrocket.com/docs/api

Example URI for checking exchange open/closed status with various parameters.

```http
GET http://houston/master/calendar/?exchanges=ARCA&sec_type=STK&in=1h&ago=30min&outside_rth=false
```

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

### Complete `before_trading_start` Function for Live Trading

Source: https://www.quantrocket.com/docs

A comprehensive example of the `before_trading_start` function, demonstrating how to fetch candidate securities, initiate real-time data collection, and configure the real-time database for live trading. It includes environment checks to differentiate between live trading and backtesting.

```python
import zipline.api as algo
from quantrocket.realtime import collect_market_data

def before_trading_start(context: algo.Context, data: algo.BarData):

    # Get candidate stocks from pipeline
    candidates = algo.pipeline_output("my_pipeline")

    # Only do this in live trading, not backtesting
    if algo.get_environment("arena") == "trade":

        # start real-time tick data collection for our candidates...
        sids = [asset.real_sid for asset in candidates.index]

        if sids:
            collect_market_data(
                "us-stk-realtime",
                sids=sids,
                until="16:01:00 America/New_York")

        # ...and point Zipline to the derived aggregate db.
        # For Alpaca databases:
        algo.set_realtime_db(
            "us-stk-realtime-1min",
            fields={
                "close": "MinuteCloseClose",
                "open": "MinuteOpenOpen",
                "high": "MinuteHighHigh",
                "low": "MinuteLowLow",
                "volume": "MinuteVolumeSum"})

        # For Interactive Brokers databases:
        # algo.set_realtime_db(
        #     "us-stk-realtime-1min",
        #     fields={
        #         "close": "LastPriceClose",
        #         "open": "LastPriceOpen",
        #         "high": "LastPriceHigh",
        #         "low": "LastPriceLow",
        #        "volume": "LastSizeSum"})
```

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

### Get Timezone Example

Source: https://www.quantrocket.com/docs/api

Example URI to retrieve the timezone of a specific service. Replace 'countdown-usa' with the actual service name.

```http
GET http://houston/countdown-usa/timezone
```

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

### Make GET Request via Houston Session

Source: https://www.quantrocket.com/docs/api?http=

Use the Houston session object to make HTTP GET requests to Houston API endpoints. Provide the path starting with '/'.

```python
response = houston.get("/countdown/crontab")
```

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

### Preview Downloaded 8-K Data via CLI

Source: https://www.quantrocket.com/docs

Preview the first 5 rows of the downloaded bankruptcies CSV file using `csvlook`.

```text
| Sid            |       DATE | TICKER | EVENTCODE |
| -------------- | ---------- | ------ | --------- |
| FIBBG000BXNJ07 | 1994-01-05 | CY     |        13 |
| FIBBG000BCPB71 | 1994-01-06 | AVT    |        13 |
| FIBBG000BRKN86 | 1994-01-20 | PPW    |        13 |
| FIBBG000DM86Y7 | 1994-01-21 | CCI1   |        13 |
| FIBBG000BKFZM4 | 1994-01-24 | GLW    |        13 |
```

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

### Install Packages from File

Source: https://www.quantrocket.com/docs

Install packages into the activated 'myclone' environment using a package file saved in the '/codeload' directory. This assumes the package file 'quantrocket.jupyter.conda.myclone.txt' exists.

```bash
(myclone) $ conda install --file '/codeload/quantrocket.jupyter.conda.myclone.txt'
```

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

### Zipline Get Bundle Config Response

Source: https://www.quantrocket.com/docs/api?http=

Example JSON response showing the configuration of a Zipline bundle.

```json
{
  "ingest_type": "usstock",
  "sids": null,
  "universes": null,
  "free": false,
  "data_frequency": "minute",
  "calendar": "XNYS",
  "start_date": "2007-01-03"
}
```

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

### Create Free US Stock Minute Bundle (CLI)

Source: https://www.quantrocket.com/docs

Create a Zipline bundle for free sample US stock minute data using the CLI. The `--free` flag indicates sample data.

```bash
$ quantrocket zipline create-usstock-bundle 'free-usstock-1min' --free
msg: successfully created free-usstock-1min bundle
status: success
```

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

### Create Free US Stock Minute Bundle (HTTP)

Source: https://www.quantrocket.com/docs

Create a Zipline bundle for free sample US stock minute data via HTTP. Include `free=true` in the query parameters.

```bash
$ curl -X PUT 'http://houston/zipline/bundles/free-usstock-1min?ingest_type=usstock&free=true'
{"status": "success", "msg": "successfully created free-usstock-1min bundle"}
```

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

### Get Exchange Rates Example URI

Source: https://www.quantrocket.com/docs/api

Example URI for querying exchange rates. Specify output format, date range, and optionally filter by base and quote currencies. Rates are sourced from the European Central Bank.

```http
GET http://houston/account/rates.csv?start_date=2017-01-01&end_date=2018-01-01&latest=true&base_currencies=USD&quote_currencies=CAD
```

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

### Get Futures Prices

Source: https://www.quantrocket.com/docs

Fetches historical closing prices for a specified futures contract. Ensure you have the 'quantrocket' library installed and configured.

```python
from quantrocket import get_prices
prices = get_prices("cl-fut-1d", fields=["Close"])
closes = prices.loc["Close"]
```

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

### Run Moonshot Backtest (HTTP POST Example)

Source: https://www.quantrocket.com/docs/api

Example URI for running a backtest via HTTP POST. This demonstrates how to specify strategies, date ranges, segments, allocations, net liquidation value, parameters, and output format.

```http
POST http://houston/moonshot/backtests.csv?strategies=umd-nyse&start_date=2015-02-01&end_date=2017-06-06&segment=A&allocations=umd-nyse:0.25&nlv=USD:500000&params=BENCHMARK:None&details=true&no_cache=false
```

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

### Response Body for Get Tick Database Config

Source: https://www.quantrocket.com/docs/api?python=

Example JSON response body showing the configuration details of a tick database.

```json
{
  "universes": [
    "cme-fut"
  ],
  "vendor": "ibkr",
  "fields": [
    "Last",
    "Volume",
    "Bid",
    "Ask",
    "BidSize",
    "AskSize"
  ]
}
```

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

### List Databases with Disk Usage Details (CLI)

Source: https://www.quantrocket.com/docs

Obtain detailed information about each database, including its size in megabytes, using the 'quantrocket db list --detail' command.

```bash
$ quantrocket db list --detail
postgres:
- name: quantrocket_v2_realtime_usa_liquid_taq
  size_in_mb: 2049.0
sqlite:
- last_modified: '2020-09-05T15:49:02'
  name: quantrocket.v2.account.balance.sqlite
  path: /var/lib/quantrocket/quantrocket.v2.account.balance.sqlite
  size_in_mb: 0.33
- last_modified: '2020-09-05T15:01:05'
  name: quantrocket.v2.account.rates.sqlite
  path: /var/lib/quantrocket/quantrocket.v2.account.rates.sqlite
  size_in_mb: 0.29
- last_modified: '2020-09-05T13:00:38'
  name: quantrocket.v2.blotter.errors.sqlite
  path: /var/lib/quantrocket/quantrocket.v2.blotter.errors.sqlite
  size_in_mb: 0.45
- last_modified: '2020-09-05T15:49:53'
  name: quantrocket.v2.blotter.executions.sqlite
  path: /var/lib/quantrocket/quantrocket.v2.blotter.executions.sqlite
  size_in_mb: 7.25
 ...
```

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

### Get Configuration for 'usstock-1min' Bundle

Source: https://www.quantrocket.com/docs/api

Example of retrieving the configuration for a Zipline bundle named 'usstock-1min'. This command shows all the settings associated with this bundle.

```bash
quantrocket zipline config usstock-1min
```

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

### Execute Python Function via Satellite CLI

Source: https://www.quantrocket.com/docs/api?http=

Example of executing a Python function on a satellite service. The function must be specified in dot notation and start with 'codeload.'.

```bash
quantrocket satellite exec -s satellite codeload.my_module.my_function param1:value1 param2:value2
```

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

### Bring Up Deployment 1

Source: https://www.quantrocket.com/docs

Bring up the first QuantRocket deployment by navigating to its local folder and specifying the Docker context. This is used for managing multiple cloud deployments.

```bash
$ cd ~/quantrocket1
$ docker compose --context cloud1 up -d
```

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

### List Active Zipline Strategies

Source: https://www.quantrocket.com/docs/api

Use this command to view all currently active Zipline strategies managed by QuantRocket. No setup or imports are required beyond having QuantRocket installed.

```bash
quantrocket zipline active

```

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

### Set Per-Share Equity Commission Example

Source: https://www.quantrocket.com/docs/api

Example showing how to set a commission model for US equities at a cost of 0.001 per share.

```python
import zipline.api as algo
algo.set_commission(algo.commission.PerShare(cost=0.001))
```

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

### Create Periodic Pipeline Factors

Source: https://www.quantrocket.com/docs/software-update

Use periodic Pipeline factors and filters to perform computations with lookback windows on fundamental data. Refer to the usage guide for detailed examples.

```python
from zipline.pipeline.factors import Returns

# Example: Calculate average dividend per share over the previous 4 quarters
# (Actual implementation would involve specific periodic factor usage)
```

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

### QuantRocket Account CLI Help

Source: https://www.quantrocket.com/docs/api?python=

Displays help information for the QuantRocket account CLI, listing available subcommands.

```bash
usage: quantrocket account [-h] {balance,portfolio,rates} ...
```

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

### Download Blotter Executions via HTTP

Source: https://www.quantrocket.com/docs

Download raw execution records from the blotter using an HTTP GET request. Parameters for order references and start date can be included in the URL.

```bash
$ curl -X GET 'http://houston/blotter/executions.csv?order_refs=dma-tech&start_date=2018-03-01' > executions.csv
```

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

### Query Order Statuses via HTTP GET Request

Source: https://www.quantrocket.com/docs

This command-line example shows how to request specific order fields using curl and format the output with json2yaml. It demonstrates retrieving 'OrderType' and 'LmtPrice'.

```bash
$ # request OrderType and LmtPrice in output
$ # (Tip: if CSV becomes too wide for terminal, try requesting json and using json2yaml)
$ curl -X GET 'http://houston/blotter/orders.json?order_ids=6001%3A64&fields=OrderType&fields=LmtPrice' | json2yaml
```

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

### Generate Orders Example URI

Source: https://www.quantrocket.com/docs/api

Example URI for generating orders from strategies. Specify strategies, accounts, review date, and output format.

```http
GET http://houston/moonshot/orders.csv?strategies=umd-nyse&accounts=U12345&review_date=2018-05-18
```

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

### Get Zipline Execution Environment

Source: https://www.quantrocket.com/docs/api

Query specific fields of the Zipline execution environment, such as data frequency, start/end dates, or capital base. This is useful for conditionally executing code, for example, only during live trading.

```python
import zipline.api as algo
if algo.get_environment("arena") == "trade":
    ...
```

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

### List Available Zipline Bundles (Example)

Source: https://www.quantrocket.com/docs/api

Executes the command to list all available Zipline data bundles and their ingestion status.

```bash
quantrocket zipline list-bundles
```

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

### Query Aggregate Data via HTTP

Source: https://www.quantrocket.com/docs

Access aggregate data using an HTTP GET request. The endpoint requires the aggregate database name and can accept parameters for start date and security IDs. The response is typically in CSV format.

```bash
$ curl -X GET 'http://houston/realtime/fang-stk-tick-1min.csv?start_date=2020-04-08&sids=FIBBG000B9XRY4' | head
```

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

### Download Tick Data via CLI

Source: https://www.quantrocket.com/docs

Use the quantrocket realtime get command to download tick data. Specify the database, start date, security IDs, and desired fields. The output can be piped to `csvlook` for a formatted table view.

```bash
$ quantrocket realtime get 'fang-stk-tick' --start-date '2020-04-08' --sids 'FIBBG000B9XRY4' --fields 'LastPrice' 'BidPrice' 'AskPrice' | csvlook
```

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

### Create Bundle from History DB (Example 2)

Source: https://www.quantrocket.com/docs/api

Creates a Zipline bundle for US 1-minute stock data from a specific history database, limiting the data to the year 2017. The calendar is set to XNYS.

```bash
quantrocket zipline create-bundle-from-db usa-stk-1min-2017 --from-db usa-stk-1min -s 2017-01-01 -e 2017-12-31 --calendar XNYS
```

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

### Download Tick Data via HTTP Request

Source: https://www.quantrocket.com/docs

Access tick data directly through an HTTP GET request to the Houston API. Construct the URL with the database name, start date, security IDs, and fields. The output is a CSV file that can be processed with tools like `head` to view the initial rows.

```bash
$ curl -X GET 'http://houston/realtime/fang-stk-tick.csv?start_date=2020-04-08&sids=FIBBG000B9XRY4&fields=LastPrice&fields=BidPrice&fields=AskPrice' | head
```
Tokens:
Raw