feat(scripts.downloads): add scripts/downloads.py (#735)

* add scripts/downloads.py

* add total cumulative downloads to title

* add module docstring

* pagination

* add datetime

* accumulate by release_date

* black/flake8

scripts/downloads.py

@@ -0,0 +1,103 @@
+"""Plot downloads over time."""
+
+import requests
+import matplotlib.pyplot as plt
+from datetime import datetime
+from pprint import pformat
+
+import numpy as np
+
+
+def fetch_download_data(api_url: str) -> dict:
+    """Fetches download data from GitHub API and returns it as a dictionary.
+
+    Supports pagination.
+
+    Args:
+        api_url (str): The URL of the GitHub API endpoint for releases.
+
+    Returns:
+        dict: A dictionary with dates as keys and download counts as values.
+    """
+    download_data = {}
+    ignored_names = set()
+    page = 1
+    while True:
+        response = requests.get(f"{api_url}?per_page=30&page={page}")
+        releases = response.json()
+        if not releases:  # Break the loop if no more releases are returned
+            break
+        for release in releases:
+            release_date = release["published_at"][:10]
+            print(
+                release["name"],
+                list(
+                    (asset["name"], asset["download_count"])
+                    for asset in release["assets"]
+                ),
+            )
+            ignored_names |= set(
+                [
+                    asset["name"]
+                    for asset in release["assets"]
+                    if not asset["name"].endswith(".zip")
+                ]
+            )
+            total_downloads = sum(
+                asset["download_count"]
+                for asset in release["assets"]
+                if asset["name"].endswith(".zip")
+            )
+            download_data.setdefault(release_date, 0)
+            download_data[release_date] += total_downloads
+        page += 1  # Increment page number for the next API request
+    print(f"ignored_names=\n{pformat(ignored_names)}")
+    return download_data
+
+
+def plot_downloads(data: dict) -> None:
+    """Plots number of downloads and cumulative downloads over time using matplotlib.
+
+    Includes total cumulative in the title.
+
+    Args:
+        data (dict): A dictionary with dates as keys and download counts as values.
+    """
+    dates = [datetime.strptime(date, "%Y-%m-%d") for date in sorted(data.keys())]
+    downloads = [data[date.strftime("%Y-%m-%d")] for date in dates]
+    cumulative_downloads = np.cumsum(downloads)
+    total_cumulative_downloads = (
+        cumulative_downloads[-1] if cumulative_downloads.size > 0 else 0
+    )
+
+    plt.figure(figsize=(12, 6))
+    plt.plot(
+        dates, downloads, marker="o", linestyle="-", color="b", label="Daily Downloads"
+    )
+    plt.plot(
+        dates,
+        cumulative_downloads,
+        marker=None,
+        linestyle="--",
+        color="r",
+        label="Cumulative Downloads",
+    )
+    current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    plt.title(
+        "Downloads Over Time"
+        f"\n(Total Cumulative: {total_cumulative_downloads}) "
+        f"\n{current_time}"
+    )
+    plt.xlabel("Date")
+    plt.ylabel("Number of Downloads")
+    plt.grid(True)
+    plt.xticks(rotation=45)
+    plt.legend()
+    plt.tight_layout()
+    plt.show()
+
+
+if __name__ == "__main__":
+    api_url = "https://api.github.com/repos/OpenAdaptAI/OpenAdapt/releases"
+    download_data = fetch_download_data(api_url)
+    plot_downloads(download_data)