# Zipline 0.8.0 Release Notes

## Highlights

  * New documentation system with a new website at [zipline.io](http://www.zipline.io)
  * Major performance enhancements.
  * Dynamic history.

## Bug Fixes (BUG)

### Fix a bug where the reported returns could sharply dip for random periods of time. [PR378](https://github.com/quantopian/zipline/pull/378)

## Enhancements (ENH)

### Account object: Adds an account object to conext to track information about the trading account. [PR396](https://github.com/quantopian/zipline/pull/396)

  > Example:

  > ```
  > context.account.settled_cash
  > ```

  > Returns the settled cash value that is stored on the account object. This
  > value is updated accordingly as the algorithm is run.

### HistoryContainer can now grow dynamically. [PR412](https://github.com/quantopian/zipline/pull/412)

  > Calls to `history` will now be able to increase the size or change the shape
  > of the history container to be able to service the call. `add_history` now
  > acts as a preformance hint to pre-allocate sufficient space in the
  > container. This change is backwards compatible with `history`, all existing
  > algorithms should continue to work as intended.

### Simple transforms ported from quantopian and use history. [PR429](https://github.com/quantopian/zipline/pull/429)

  > SIDData now has methods for:

  > - `stddev`
  > - `mavg`
  > - `vwap`
  > - `returns`

  > These methods, except for `returns`, accept a number of days. If you are
  > running with minute data, then this will calculate the number of minutes in
  > those days, accounting for early closes and the current time and apply the
  > transform over the set of minutes. `returns` takes no parameters and will
  > return the daily returns of the given asset.

  > Example:
```python
data[security].stddev(3)
```

### New fields in Performance Period [PR464](https://github.com/quantopian/zipline/pull/464)

  > Performance Period has new fields accessible in return value of to_dict:

  > - gross leverage
  > - net leverage
  > - short exposure
  > - long exposure
  > - shorts count
  > - longs count


### Allow order_percent to work with various market values (by Jeremiah Lowin) [PR477](https://github.com/quantopian/zipline/pull/477)

  > Currently, `order_percent()` and `order_target_percent()` both operate as a percentage of `self.portfolio.portfolio_value`. This PR lets them operate as percentages of other important MVs.

  > Also adds `context.get_market_value()`, which enables this functionality.

  > For example:
  > ```python
  # this is how it works today (and this still works)
  # put 50% of my portfolio in AAPL
  order_percent('AAPL', 0.5)
  # note that if this were a fully invested portfolio, it would become 150% levered.
  >
  # take half of my available cash and buy AAPL
  order_percent('AAPL', 0.5, percent_of='cash')
  >
  # rebalance my short position, as a percentage of my current short book
  order_target_percent('MSFT', 0.1, percent_of='shorts')
  >
  # rebalance within a custom group of stocks
  tech_stocks = ('AAPL', 'MSFT', 'GOOGL')
  tech_filter = lambda p: p.sid in tech_stocks
  for stock in tech_stocks:
     order_target_percent(stock, 1/3, percent_of_fn=tech_filter)
  ```

### Major performance enhancements to history (by Dale Jung) [PR488](https://github.com/quantopian/zipline/commit/38e8d5214d46f089020703712dc6b3f4f6ee084d)

### Command line option to for printing algo to stdout (by Andrea D'Amore) [PR545](https://github.com/quantopian/zipline/pull/545)

## Contributors

The following people have contributed to this release, ordered by numbers of commit:
```
    39  Thomas Wiecki
    36  Joe Jevnik
    26  John Fawcett
    24  Scott Sanderson
    11  Delaney Granizo-Mackenzie
     8  John Ricklefs
     5  Brian Fink
     5  Eddie Hebert
     2  Dale Jung
     2  Jeremiah Lowin
     2  Jonathan Kamens
     2  Richard Frank
     1  David Edwards
     1  Luke Schiefelbein
     1  Mete Atamel
     1  Nicholas Pezolano
     1  Philipp Kosel
     1  Andrea D'Amore
```