Merge pull request #1 from Huxingyu/feat/likes

feat: add likes command to fetch authenticated user's liked tweets

README.md

@@ -19,6 +19,7 @@ A terminal-first CLI for Twitter/X: read timelines, bookmarks, and user profiles
 
 - Timeline: fetch `for-you` and `following` feeds
 - Bookmarks: list saved tweets from your account
+- Likes: view your liked tweets
 - User lookup: fetch user profile and recent tweets
 - JSON output: export feed/bookmarks/user tweets for scripting
 - Optional scoring filter: rank tweets by engagement weights
@@ -67,6 +68,10 @@ twitter feed --input tweets.json
 twitter favorite
 twitter favorite --max 30 --json
 
+# Likes (your own liked tweets)
+twitter likes
+twitter likes --max 20 --json
+
 # User
 twitter user elonmusk
 twitter user-posts elonmusk --max 20
@@ -198,6 +203,7 @@ After installation, OpenClaw can call `twitter-cli` commands directly.
 
 - 时间线读取：支持 `for-you` 和 `following`
 - 收藏读取：查看账号书签推文
+- 点赞列表：查看自己的点赞推文
 - 用户查询：查看用户资料和用户推文
 - JSON 输出：便于脚本处理
 - 可选筛选：按 engagement score 排序
@@ -228,6 +234,9 @@ twitter feed --filter
 # 收藏
 twitter favorite
 
+# 点赞列表
+twitter likes
+
 # 用户
 twitter user elonmusk
 twitter user-posts elonmusk --max 20

SKILL.md

@@ -34,6 +34,9 @@ twitter feed -t following
 # Bookmarks
 twitter favorite
 
+# Likes (own liked tweets)
+twitter likes
+
 # User profile and posts
 twitter user <screen_name>
 twitter user-posts <screen_name> --max 20
@@ -56,6 +59,7 @@ Filtering is opt-in (disabled by default). Enable with `--filter`.
 ```bash
 twitter feed --filter
 twitter favorite --filter
+twitter likes --filter
 ```
 
 The scoring formula:

tests/test_cli.py

@@ -26,3 +26,21 @@ def test_cli_feed_json_input_path(tmp_path, tweet_factory) -> None:
     result = runner.invoke(cli, ["feed", "--input", str(json_path), "--json"])
     assert result.exit_code == 0
     assert '"id": "1"' in result.output
+
+
+def test_cli_likes_command(monkeypatch, tweet_factory) -> None:
+    fake_tweets = [tweet_factory("10"), tweet_factory("11")]
+
+    class FakeClient:
+        def fetch_current_user_id(self) -> str:
+            return "999"
+
+        def fetch_likes(self, user_id: str, count: int = 20):
+            return fake_tweets
+
+    monkeypatch.setattr("twitter_cli.cli._get_client", lambda: FakeClient())
+    runner = CliRunner()
+    result = runner.invoke(cli, ["likes", "--max", "5", "--json"])
+    assert result.exit_code == 0
+    assert '"id": "10"' in result.output
+    assert '"id": "11"' in result.output

twitter_cli/cli.py

@@ -193,6 +193,43 @@ def favorite(max_count, as_json, output_file, do_filter):
     console.print()
 
 
+@cli.command()
+@click.option("--max", "-n", "max_count", type=int, default=None, help="Max number of tweets to fetch.")
+@click.option("--json", "as_json", is_flag=True, help="Output as JSON.")
+@click.option("--output", "-o", "output_file", type=str, default=None, help="Save tweets to JSON file.")
+@click.option("--filter", "do_filter", is_flag=True, help="Enable score-based filtering.")
+def likes(max_count, as_json, output_file, do_filter):
+    # type: (Optional[int], bool, Optional[str], bool) -> None
+    """Fetch your liked tweets (only available for the authenticated user)."""
+    config = load_config()
+    try:
+        fetch_count = _resolve_fetch_count(max_count, config.get("fetch", {}).get("count", 50))
+        client = _get_client()
+        console.print("👤 Resolving your user ID...")
+        user_id = client.fetch_current_user_id()
+        console.print("❤️ Fetching likes (%d tweets)...\n" % fetch_count)
+        start = time.time()
+        tweets = client.fetch_likes(user_id, fetch_count)
+        elapsed = time.time() - start
+        console.print("✅ Fetched %d likes in %.1fs\n" % (len(tweets), elapsed))
+    except RuntimeError as exc:
+        console.print("[red]❌ %s[/red]" % exc)
+        sys.exit(1)
+
+    filtered = _apply_filter(tweets, do_filter, config)
+
+    if output_file:
+        Path(output_file).write_text(tweets_to_json(filtered), encoding="utf-8")
+        console.print("💾 Saved to %s\n" % output_file)
+
+    if as_json:
+        click.echo(tweets_to_json(filtered))
+        return
+
+    print_tweet_table(filtered, console, title="❤️ Likes — %d tweets" % len(filtered))
+    console.print()
+
+
 @cli.command()
 @click.argument("screen_name")
 def user(screen_name):

twitter_cli/client.py

@@ -27,6 +27,8 @@ FALLBACK_QUERY_IDS = {
     "Bookmarks": "VFdMm9iVZxlU6hD86gfW_A",
     "UserByScreenName": "1VOOyvKkiI3FMmkeDNxM9A",
     "UserTweets": "E3opETHurmVJflFsUBVuUQ",
+    "Likes": "yrFhBQCFo96rIBH28a4T2A",
+    "Viewer": "zWQLM9HIVahRSUvzUH4lDw",
 }
 
 TWITTER_OPENAPI_URL = (
@@ -302,6 +304,31 @@ class TwitterClient:
             },
         )
 
+    def fetch_current_user_id(self):
+        # type: () -> str
+        """Fetch the authenticated user's ID via the Viewer endpoint."""
+        features = {
+            "responsive_web_graphql_exclude_directive_enabled": True,
+            "verified_phone_label_enabled": False,
+            "responsive_web_graphql_skip_user_profile_image_extensions_enabled": False,
+            "responsive_web_graphql_timeline_navigation_enabled": True,
+        }
+        data = self._graphql_get("Viewer", {}, features)
+        user_id = _deep_get(data, "data", "viewer", "user_results", "result", "rest_id")
+        if not user_id:
+            raise RuntimeError("Could not resolve current user ID")
+        return user_id
+
+    def fetch_likes(self, user_id, count=20):
+        # type: (str, int) -> List[Tweet]
+        """Fetch liked tweets for a user (only works for the authenticated user)."""
+        return self._fetch_timeline(
+            "Likes",
+            count,
+            lambda data: _deep_get(data, "data", "user", "result", "timeline", "timeline", "instructions"),
+            extra_variables={"userId": user_id},
+        )
+
     def _fetch_timeline(self, operation_name, count, get_instructions, extra_variables=None):
         # type: (str, int, Callable[[Any], Any], Optional[Dict[str, Any]]) -> List[Tweet]
         """Generic timeline fetcher with pagination and deduplication."""