Chicken Dinner

Python PUBG JSON API Wrapper and (optional) playback visualizer.

Samples

Installation

To install chicken-dinner, use pip. This will install the core dependencies (requests library) which provide functionality to the API wrapper classes.

pip install chicken-dinner

To use the playback visualizations you will need to install the library with extra dependencies for plotting (matplotlib and pillow). For this you can also use pip:

pip install chicken-dinner[visual]

To generate the animations you will also need ffmpeg installed on your machine. On Max OSX you can install ffmpeg using brew.

brew install ffmpeg

You can install ffmpeg on other systems from here.

Usage

Working with the low-level API class.

from chicken_dinner.pubgapi import PUBGCore

api_key = "your_api_key"
pubgcore = PUBGCore(api_key, "pc-na")
shroud = pubgcore.players("player_names", "shroud")
print(shroud)

# {'data': [{'type': 'player', 'id': 'account.d50f...

Working with the high-level API class.

from chicken_dinner.pubgapi import PUBG

api_key = "your_api_key"
pubg = PUBG(api_key, "pc-na")
shroud = pubg.players_from_names("shroud")[0]
shroud_season = shroud.get_current_season()
squad_fpp_stats = shroud_season.game_mode_stats("squad", "fpp")
print(squad_fpp_stats)

# {'assists': 136, 'boosts': 313, 'dbnos': 550, 'daily_kills':...

Visualizing telemetry data

from chicken_dinner.pubgapi import PUBG

api_key = "your_api_key"
pubg = PUBG(api_key, "pc-na")
shroud = pubg.players_from_names("shroud")[0]
recent_match_id = shroud.match_ids[0]
recent_match = pubg.match(recent_match_id)
recent_match_telemetry = recent_match.get_telemetry()
recent_match_telemetry.playback_animation("recent_match.html")

Recommended playback settings:

telemetry.playback_animation(
    "match.html",
    zoom=True,
    labels=True,
    label_players=[],
    highlight_winner=True,
    label_highlights=True,
    size=6,
    end_frames=60,
    use_hi_res=False,
    color_teams=True,
    interpolate=True,
    damage=True,
    interval=2,
    fps=30,
)

See the documentation for more details.

Release files for chicken-dinner 0.5.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for chicken-dinner 0.5.1
File	Size	Uploaded
chicken_dinner-0.5.1.tar.gz	12.1 MB	Oct 13, 2018	Details

Built distribution (wheel)

Table of built distributions (wheels) for chicken-dinner 0.5.1
File	Interpreter	ABI	Platform	Reset
chicken_dinner-0.5.1-py3-none-any.whl 12.1 MB Oct 13, 2018	Python 3	none	any	Details

Total release size: 24.3 MB

Release files / chicken_dinner-0.5.1.tar.gz

Download URL	chicken_dinner-0.5.1.tar.gz
Size	12.1 MB
Tags	Source
SHA-256 checksum How to use checksums	`42225f9a1e4bccf009ce4650df2a92d79ab3b2fc7525aade1831ac73e60ae9d4`
BLAKE2b-256 checksum How to use checksums	`1de9d3f7e74d9668bb052e7e273d62a49da73be3788f76d90e1687a26d37d9f3`
Upload date	Oct 13, 2018
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.3`

Release files / chicken_dinner-0.5.1-py3-none-any.whl

Download URL	chicken_dinner-0.5.1-py3-none-any.whl
Size	12.1 MB
Tags	Python 3
SHA-256 checksum How to use checksums	`c0c73941e6fa76340462d0f1779195115992822972394f0480e0e7b728b3461c`
BLAKE2b-256 checksum How to use checksums	`ebbc1ac83c21970997bb42b82207578bce8b34c341b7e13d99fd26863896ad45`
Upload date	Oct 13, 2018
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.3`