معرفی شرکت ها
draftfast-3.8.0
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
A tool to automate and optimize DraftKings and FanDuel lineup construction.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | draftfast-3.8.0 |
| نام | draftfast |
| نسخه کتابخانه | 3.8.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Ben Brostoff |
| ایمیل نویسنده | ben.brostoff@gmail.com |
| آدرس صفحه اصلی | https://github.com/BenBrostoff/draftfast |
| آدرس اینترنتی | https://pypi.org/project/draftfast/ |
| مجوز | - |
## Introduction · [](https://travis-ci.org/BenBrostoff/draftfast) · [](https://draftfast.herokuapp.com/)
An incredibly powerful tool that automates and optimizes lineup building, allowing you to enter thousands of lineups in any DraftKings or FanDuel contest in the time it takes you to grab a coffee.
## Installation
Requires Python 3.9+.
```bash
pip install draftfast
```
## Usage
Example usage ([you can experiment with these examples in repl.it](https://repl.it/@BenBrostoff/AllWarlikeDemoware)):
```python
from draftfast import rules
from draftfast.optimize import run
from draftfast.orm import Player
from draftfast.csv_parse import salary_download
# Create players for a classic DraftKings game
player_pool = [
Player(name='A1', cost=5500, proj=55, pos='PG'),
Player(name='A2', cost=5500, proj=55, pos='PG'),
Player(name='A3', cost=5500, proj=55, pos='SG'),
Player(name='A4', cost=5500, proj=55, pos='SG'),
Player(name='A5', cost=5500, proj=55, pos='SF'),
Player(name='A6', cost=5500, proj=55, pos='SF'),
Player(name='A7', cost=5500, proj=55, pos='PF'),
Player(name='A8', cost=5500, proj=55, pos='PF'),
Player(name='A9', cost=5500, proj=55, pos='C'),
Player(name='A10', cost=5500, proj=55, pos='C'),
]
roster = run(
rule_set=rules.DK_NBA_RULE_SET,
player_pool=player_pool,
verbose=True,
)
# Or, alternatively, generate players from a CSV
players = salary_download.generate_players_from_csvs(
salary_file_location='./salaries.csv',
game=rules.DRAFT_KINGS,
)
roster = run(
rule_set=rules.DK_NBA_RULE_SET,
player_pool=players,
verbose=True,
)
```
You can see more examples in the [`examples` directory](https://github.com/BenBrostoff/draftfast/tree/master/examples).
## Game Rules
Optimizing for a particular game is as easy as setting the `RuleSet` (see the example above). Game rules in the library are in the table below:
| League | Site | Reference |
| ------------- |:-------------:| :-----:|
| NFL | DraftKings | `DK_NFL_RULE_SET` |
| NFL | FanDuel | `FD_NFL_RULE_SET` |
| NBA | DraftKings | `DK_NBA_RULE_SET` |
| NBA | FanDuel | `FD_NBA_RULE_SET` |
| MLB | DraftKings | `DK_MLB_RULE_SET` |
| MLB | FanDuel | `FD_MLB_RULE_SET` |
| WNBA | DraftKings | `DK_WNBA_RULE_SET` |
| WNBA | FanDuel | `FD_WNBA_RULE_SET` |
| PGA | FanDuel | `FD_PGA_RULE_SET` |
| PGA | DraftKings | `DK_PGA_RULE_SET` |
| PGA_CAPTAIN | DraftKings | `DK_PGA_CAPTAIN_RULE_SET` |
| NASCAR | FanDuel | `FD_NASCAR_RULE_SET` |
| NASCAR | DraftKings | `DK_NASCAR_RULE_SET` |
| SOCCER | DraftKings | `DK_SOCCER_RULE_SET` |
| EuroLeague | DraftKings | `DK_EURO_LEAGUE_RULE_SET` |
| NHL | DraftKings | `DK_NHL_RULE_SET` |
| NBA Pickem | DraftKings | `DK_NBA_PICKEM_RULE_SET` |
| NFL Showdown | DraftKings | `DK_NFL_SHOWDOWN_RULE_SET` |
| NBA Showdown | DraftKings | `DK_NBA_SHOWDOWN_RULE_SET` |
| MLB Showdown | DraftKings | `DK_MLB_SHOWDOWN_RULE_SET` |
| XFL | DraftKings | `DK_XFL_CLASSIC_RULE_SET` |
| Tennis | DraftKings | `DK_TEN_CLASSIC_RULE_SET` |
| CS:GO | DraftKings | `DK_CSGO_SHOWDOWN` |
| F1 | DraftKings | `DK_F1_SHOWDOWN` |
| NFL MVP | FanDuel | `FD_NFL_MVP_RULE_SET` |
| MLB MVP | FanDuel | `FD_MLB_MVP_RULE_SET` |
| NBA MVP | FanDuel | `FD_NBA_MVP_RULE_SET` |
Note that you can also tune `draftfast` for any game of your choice even if it's not implemented in the library (PRs welcome!). Using the `RuleSet` class, you can generate your own game rules that specific number of players, salary, etc. Example:
```python
from draftfast import rules
golf_rules = rules.RuleSet(
site=rules.DRAFT_KINGS,
league='PGA',
roster_size='6',
position_limits=[['G', 6, 6]],
salary_max=50_000,
)
```
## Settings
Usage example:
```python
class Showdown(Roster):
POSITION_ORDER = {
'M': 0,
'F': 1,
'D': 2,
'GK': 3,
}
showdown_limits = [
['M', 0, 6],
['F', 0, 6],
['D', 0, 6],
['GK', 0, 6],
]
soccer_rules = rules.RuleSet(
site=rules.DRAFT_KINGS,
league='SOCCER_SHOWDOWN',
roster_size=6,
position_limits=showdown_limits,
salary_max=50_000,
general_position_limits=[],
)
player_pool = salary_download.generate_players_from_csvs(
salary_file_location=salary_file,
game=rules.DRAFT_KINGS,
)
roster = run(
rule_set=soccer_rules,
player_pool=player_pool,
verbose=True,
roster_gen=Showdown,
)
```
`PlayerPoolSettings`
- `min_proj`
- `max_proj`
- `min_salary`
- `max_salary`
- `min_avg`
- `max_avg`
`OptimizerSettings`
- `stacks` - A list of `Stack` objects. Example:
```python
roster = run(
rule_set=rules.DK_NHL_RULE_SET,
player_pool=player_pool,
verbose=True,
optimizer_settings=OptimizerSettings(
stacks=[
Stack(team='PHI', count=3),
Stack(team='FLA', count=3),
Stack(team='NSH', count=2),
]
),
)
```
`Stack` can also be tuned to support different combinations of positions. For NFL,
to only specify a QB-WRs based stack of five:
```python
Stack(
team='NE',
count=5,
stack_lock_pos=['QB'],
stack_eligible_pos=['WR'],
)
```
- `custom_rules` - Define rules that set if / then conditions for lineups.
For example, if two WRs from the same team are in a naturally optimized lineup, then the QB must also be in the lineup. You can find some good examples of rules in `draftfast/test/test_custom_rules.py`.
```python
from draftfast.optimize import run
from draftfast.settings import OptimizerSettings, CustomRule
# If two WRs on one team, play the QB from same team
settings = OptimizerSettings(
custom_rules=[
CustomRule(
group_a=lambda p: p.pos == 'WR' and p.team == 'Patriots',
group_b=lambda p: p.pos == 'QB' and p.team == 'Patriots',
comparison=lambda sum, a, b: sum(a) + 1 <= sum(b)
)
]
)
roster = run(
rule_set=rules.DK_NFL_RULE_SET,
player_pool=nfl_pool,
verbose=True,
optimizer_settings=settings,
)
```
Another common use case is given one player is in a lineup, always play another player:
```python
from draftfast.optimize import run
from draftfast.settings import OptimizerSettings, CustomRule
# If Player A, always play Player B and vice versa
settings = OptimizerSettings(
custom_rules=[
CustomRule(
group_a=lambda p: p.name == 'Tom Brady',
group_b=lambda p: p.name == 'Rob Gronkowski',
comparison=lambda sum, a, b: sum(a) == sum(b)
)
]
)
roster = run(
rule_set=rules.DK_NFL_RULE_SET,
player_pool=nfl_pool,
verbose=True,
optimizer_settings=settings,
)
```
Custom rules also don't have to make a comparison between two groups. You can say "never play these two players in the same lineup" by using the `CustomRule#comparison` property.
```python
# Never play these two players together
settings = OptimizerSettings(
custom_rules=[
CustomRule(
group_a=lambda p: p,
group_b=lambda p: p.name == 'Devon Booker' or p.name == 'Chris Paul',
comparison=lambda sum, a, b: sum(b) <= 1
)
]
)
roster = run(
rule_set=rules.DK_NBA_RULE_SET,
player_pool=nba_pool,
verbose=True,
optimizer_settings=settings,
)
```
Importantly, as of this writing, passing closures into `CustomRule`s does not work (ex. `lambda p: p.team == team`),
so dynamically generating rules is not possible. PRs welcome for a fix here, I believe this is a limitation of `ortools`.
`LineupConstraints`
- `locked` - list of players to lock
- `banned` - list of players to ban
- `groups` - list of player groups constraints. See below
```python
roster = run(
rule_set=rules.DK_NFL_RULE_SET,
player_pool=player_pool,
verbose=True,
constraints=LineupConstraints(
locked=['Rob Gronkowski'],
banned=['Mark Ingram', 'Doug Martin'],
groups=[
[('Todd Gurley', 'Melvin Gordon', 'Christian McCaffrey'), (2, 3)],
[('Chris Carson', 'Mike Davis'), 1],
]
)
)
```
- `no_offense_against_defense` - Do not allow offensive players to be matched up against defensive players in the optimized lineup. Currently only implemented for soccer, NHL, and NFL -- PRs welcome!
## CSV Upload
```python
from draftfast.csv_parse import uploaders
uploader = uploaders.DraftKingsNBAUploader(
pid_file='./pid_file.csv',
)
uploader.write_rosters(rosters)
```
## Support and Consulting
DFS optimization is only one part of a sustainable strategy. Long-term DFS winners have the best:
- Player projections
- Bankroll management
- Diversification in contests played
- Diversification across lineups (see `draftfast.exposure`)
- Research process
- 1 hour before gametime lineup changes
- ...and so much more
DraftFast provides support and consulting services that can help with all of these. [Let's get in touch today](mailto:ben.brostoff@gmail.com).
# Contributing
Run tests or set of tests:
```sh
# All tests
nosetests
# Single file
nosetests draftfast/test/test_soccer.py
# Single test
nosetests draftfast/test/test_soccer.py:test_soccer_dk_no_opp_d
```
Run linting
```
flake8 draftfast
```
# Credits
Special thanks to [swanson](https://github.com/swanson/), who authored [this repo](https://github.com/swanson/degenerate), which was the inspiration for this one.
Current project maintainers:
- [BenBrostoff](https://github.com/BenBrostoff)
- [sharkiteuthis](https://github.com/sharkiteuthis)
نحوه نصب
نصب پکیج whl draftfast-3.8.0:
pip install draftfast-3.8.0.whl
نصب پکیج tar.gz draftfast-3.8.0:
pip install draftfast-3.8.0.tar.gz