Export to PNG (#1)
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4 changed files with 109 additions and 62 deletions
4
.gitignore
vendored
4
.gitignore
vendored
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/lib
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/lib
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pyvenv.cfg
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pyvenv.cfg
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/.vscode
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.env
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.env
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.cache
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.cache
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*.csv
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*.png
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19
README.md
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README.md
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# GeneRatio
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# [GeneRatio](https://twitter.com/Mylloon/status/1699226564519514358)
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- Installe les dépendances : `pip install -r requirements.txt`
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- Installe les dépendances : `pip install -r requirements.txt`
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- Remplir un .env avec les champs suivant :
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- Remplir un .env avec les champs suivant :
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@ -9,18 +9,7 @@ SPOTIPY_CLIENT_SECRET="XXXXX"
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SPOTIPY_REDIRECT_URI="http://127.0.0.1:9090"
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SPOTIPY_REDIRECT_URI="http://127.0.0.1:9090"
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```
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```
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Les données devraient correspondre avec tes infos persos de Spotify Dashboard
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> Les données devraient correspondre avec tes infos persos
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> de [Spotify Dashboard](https://developer.spotify.com/dashboard)
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Le script va probablement te demander d'ouvrir un lien, il faudra cliquer dessus,
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Suis les étapes du script, à la fin, il devrait y avoir un resultat.png.
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attendre, et envoyer l'URL final dans le script au final (me DM si c'est pas claire)
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---
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Quand le script est fini, faut ouvrir google sheets,
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Colonne D: `=DATEVAL(C2)` (donne un chiffre chelou, étendre tout du long)
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Colonne E: `=ANNEE(D2)` (donne l'année correspondant a la musique, étendre tout du long)
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Colonne F: Faire une liste des années (pour le graphique final)
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Colonne G: `=NB.SI(E:E;F2)` (donne le nombre d'occurence, étendre jusqu'a la fin de la colonne F)
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[Faire un graphique dans l'interface de Google](https://twitter.com/Mylloon/status/1699226564519514358)
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107
main.py
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main.py
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import spotipy
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from matplotlib import pyplot as plt
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from spotipy.oauth2 import SpotifyOAuth
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from dotenv import load_dotenv
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from dotenv import load_dotenv
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from spotipy import Spotify, exceptions
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from spotipy.oauth2 import SpotifyOAuth
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# Load .env
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load_dotenv()
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# Connect to spotify
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def get_user_tracks(spotify: Spotify) -> list:
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spotify = spotipy.Spotify(auth_manager=SpotifyOAuth(
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"""Fetch the saved tracks of a specified user."""
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scope="user-library-read",
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open_browser=False))
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# Fetch the saved tracks of a specified user
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offset = 0
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offset = 0
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saved_tracks = []
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saved_tracks = []
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limit = 50
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limit = 50
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# Loop until either we reach the end of the playlist, or we getting limited
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# by the API
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while True:
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while True:
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try:
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try:
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print(f"Récupération {offset}-{offset + limit}")
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print(f"Récupération {offset}-{offset + limit}")
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results = spotify.current_user_saved_tracks(limit=limit, offset=offset)
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results: dict | None = spotify.current_user_saved_tracks(
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except spotipy.exceptions.SpotifyException as e:
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limit=limit,
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offset=offset
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)
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if results is None:
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print("L'API de Spotify délire")
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exit(1)
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except exceptions.SpotifyException as e:
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if e.http_status == 429:
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if e.http_status == 429:
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print("Récolte terminé, l'API a bien mangé.")
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print("Récolte terminé, l'API a bien mangé.")
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break
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break
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@ -29,24 +34,74 @@ while True:
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offset += limit
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offset += limit
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# Break the loop if we reach the end
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# Break the loop if we reach the end
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if len(results['items']) == 0:
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if len(results["items"]) == 0:
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break
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break
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saved_tracks.extend(results['items'])
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saved_tracks.extend(results["items"])
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return saved_tracks
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with open("result.csv", "w") as file:
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def get_years(data: list) -> list:
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file.write("titre;artiste;date\n")
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"""Extract data"""
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years = []
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for item in data:
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track = item["track"]
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years.append(int(track['album']['release_date'][:4]))
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# Extract data
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return years
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buffer = ""
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for item in saved_tracks:
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track = item['track']
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buffer += f"{track['name'].replace(';', ',')};"
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def get_occurences(years: list) -> dict:
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buffer += f"{track['artists'][0]['name'].replace(';', ',')};"
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"""
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buffer += f"{track['album']['release_date']}\n"
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Map of all the years and how many times there is an occurence,
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sorted by years
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"""
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year_count = {}
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for year in years:
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if year in year_count:
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year_count[year] += 1
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else:
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if year > 0:
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year_count[year] = 1
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# Save to a file
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return dict(sorted(year_count.items()))
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with open("result.csv", "a") as file:
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file.write(buffer)
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def export_data(color) -> str:
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"""Build a graphic"""
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plt.clf()
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match color:
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case "light":
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pass
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case "dark":
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plt.style.use("dark_background")
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case _:
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print("Comprends pas cette couleur")
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exit(1)
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filename = f"resultat_{color}.png"
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plt.plot(occurences.keys(), occurences.values())
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plt.title("Occurrences of what I've listened to over the years")
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plt.xlabel("Year")
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plt.ylabel("Occurrence")
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plt.savefig(filename)
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return filename
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if __name__ == '__main__':
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# Load .env
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load_dotenv()
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# Connect to spotify
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spotify = Spotify(
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auth_manager=SpotifyOAuth(scope="user-library-read", open_browser=False)
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)
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# Get of release year of liked user tracks
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saved_tracks = get_user_tracks(spotify)
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years = get_years(saved_tracks)
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# Get how many time each years appears in the data
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occurences = get_occurences(years)
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# Build chart
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light, dark = export_data("light"), export_data("dark")
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print(f"Check ton graph:\n- {light}\n- {dark}")
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python-dotenv==1.0.0
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python-dotenv==1.0.0
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spotipy==2.23.0
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spotipy==2.23.0
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matplotlib==3.7.2
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