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Begin work on web interface

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Hugo Locurcio
2023-06-30 01:19:28 +02:00
parent 7804561961
commit 299ae8d6d4
6 changed files with 95 additions and 10 deletions
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5
.gitignore vendored
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@@ -1,7 +1,10 @@
# Python virtualenv
# Python virtualenv.
venv/
.mypy_cache/
# Environment variables (contains credentials).
.env
# JSON file output by running `main.py`.
statistics.json

61
index.html Normal file
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@@ -0,0 +1,61 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Document</title>
<link rel="stylesheet" href="thirdparty/water.min.css">
<style>
</style>
<script src="thirdparty/frappe-charts.umd.min.js"></script>
<script src="thirdparty/ky.umd.min.js"></script>
<script type="module">
document.addEventListener("DOMContentLoaded", async function () {
const statistics = await ky.get('statistics.json').json();
const colorAmd = "#b91c1c";
const colorIntel = "#2074d9";
const colorNvidia = "#65a30d";
// Function that sums all values in an array (use with `reduce()`).
const sum = (partialSum, value) => partialSum + value;
new frappe.Chart("#chart-cpu-vendor", {
data: {
labels: ["AMD", "Intel"],
datasets: [{ values: [Object.values(statistics.cpu.amd).reduce(sum, 0), Object.values(statistics.cpu.intel).reduce(sum, 0)] }],
},
type: "percentage",
colors: [colorAmd, colorIntel],
});
new frappe.Chart("#chart-gpu-vendor", {
data: {
labels: ["AMD", "Intel", "NVIDIA"],
datasets: [{ values: [Object.values(statistics.gpu.amd).reduce(sum, 0), Object.values(statistics.gpu.intel).reduce(sum, 0), Object.values(statistics.gpu.nvidia).reduce(sum, 0)] }],
},
type: "percentage",
colors: [colorAmd, colorIntel, colorNvidia],
});
});
</script>
</head>
<body>
<h1>Statistics</h1>
<h2>CPU vendor</h2>
<div id="chart-cpu-vendor"></div>
<h2>GPU vendor</h2>
<div id="chart-gpu-vendor"></div>
<footer>
© 2023-present Hugo Locurcio and contributors<br>
<a href="https://github.com/godot-issues-stats/godot-issues-stats.github.io">Website source on GitHub</a>
</footer>
</body>
</html>

26
main.py
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@@ -3,6 +3,7 @@ from gql import gql, Client
from gql.transport.aiohttp import AIOHTTPTransport
from dotenv import load_dotenv
import os
import json
def main() -> None:
@@ -18,9 +19,11 @@ def main() -> None:
results = []
cursor = None
# Get the 10×100 = 1000 last issues.
# Get the 30×100 = 3,000 last issues.
# TODO: Retry requests a few times if they fail.
for _ in range(10):
num_queries = 30
for i in range(num_queries):
print(f"Running query #{i + 1} of {num_queries}...")
query = gql(
"""
query($cursor: String) {
@@ -343,7 +346,6 @@ def main() -> None:
"pro", ""
) # Makes it easier to parse "Ryzen PRO" (these are very close to their non-PRO counterparts).
)
print(system_information_trimmed)
# Gather statistics for each issue reported.
if "windows11" in system_information_trimmed:
@@ -2943,12 +2945,20 @@ def main() -> None:
):
statistics["gpu"]["intel"]["unknown"].add(user)
for info in user_system_infos:
print(info["user"], " \t", info["system_information"])
print(f"Number of scannable reports: {len(user_system_infos)}")
print()
print(statistics)
output_path = "statistics.json"
with open(output_path, "w") as out_file:
# Serialize Python sets as their length as an integer, since we only need to know how many users
# match each metric (and not who exactly).
def set_default(obj):
if isinstance(obj, set):
return len(obj)
raise TypeError
json.dump(statistics, out_file, default=set_default)
print(f"Wrote statistics to: {output_path}")
if __name__ == "__main__":

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