cargo +nightly fmt

rustfmt has changed its formatting rules, apply it project wide

src/cmd/dedup.rs

@@ -119,11 +119,12 @@ pub fn run(argv: &[&str]) -> CliResult<()> {
             };
             let a = sel.select(&record);
             let b = sel.select(&next_record);
-            let comparison = if ignore_case {
-                iter_cmp_ignore_case(a, b)
-            } else {
-                iter_cmp(a, b)
-            };
+            let comparison =
+                if ignore_case {
+                    iter_cmp_ignore_case(a, b)
+                } else {
+                    iter_cmp(a, b)
+                };
             match comparison {
                 cmp::Ordering::Equal => {
                     dupe_count += 1;

src/cmd/describegpt.rs

@@ -185,61 +185,63 @@ fn is_valid_model(client: &Client, api_key: Option<&str>, args: &Args) -> CliRes
 
 fn get_prompt_file(args: &Args) -> CliResult<PromptFile> {
     // Get prompt file if --prompt-file is used
-    let prompt_file = if let Some(prompt_file) = args.flag_prompt_file.clone() {
-        // Read prompt file
-        let prompt_file = fs::read_to_string(prompt_file)?;
-        // Try to parse prompt file as JSON, if error then show it in JSON format
-        let prompt_file: PromptFile = match serde_json::from_str(&prompt_file) {
-            Ok(val) => val,
-            Err(e) => {
-                let error_json = json!({"error": e.to_string()});
-                return fail_clierror!("{error_json}");
-            },
-        };
-        prompt_file
-    }
-    // Otherwise, get default prompt file
-    else {
-        #[allow(clippy::let_and_return)]
-        let default_prompt_file = PromptFile {
-            name:               "My Prompt File".to_string(),
-            description:        "My prompt file for qsv's describegpt command.".to_string(),
-            author:             "My Name".to_string(),
-            version:            "1.0.0".to_string(),
-            tokens:             50,
-            dictionary_prompt:  "Here are the columns for each field in a data dictionary:\n\n- \
-                                 Type: the data type of this column\n- Label: a human-friendly \
-                                 label for this column\n- Description: a full description for \
-                                 this column (can be multiple sentences)\n\nGenerate a data \
-                                 dictionary as aforementioned (in JSON output) where each field \
-                                 has Name, Type, Label, and Description (so four columns in \
-                                 total) based on the following summary statistics and frequency \
-                                 data from a CSV file.\n\nSummary \
-                                 Statistics:\n\n{stats}\n\nFrequency:\n\n{frequency}"
-                .to_string(),
-            description_prompt: "Generate only a description that is within 8 sentences about the \
-                                 entire dataset{json_add} based on the following summary \
-                                 statistics and frequency data derived from the CSV file it came \
-                                 from.\n\nSummary \
-                                 Statistics:\n\n{stats}\n\nFrequency:\n\n{frequency}\n\nDo not \
-                                 output the summary statistics for each field. Do not output the \
-                                 frequency for each field. Do not output data about each field \
-                                 individually, but instead output about the dataset as a whole in \
-                                 one 1-8 sentence description."
-                .to_string(),
-            tags_prompt:        "A tag is a keyword or label that categorizes datasets with \
-                                 other, similar datasets. Using the right tags makes it easier \
-                                 for others to find and use datasets.\n\nGenerate single-word \
-                                 tags{json_add} about the dataset (lowercase only and remove all \
-                                 whitespace) based on the following summary statistics and \
-                                 frequency data from a CSV file.\n\nSummary \
-                                 Statistics:\n\n{stats}\n\nFrequency:\n\n{frequency}"
-                .to_string(),
-            json:               true,
-            jsonl:              false,
+    let prompt_file =
+        if let Some(prompt_file) = args.flag_prompt_file.clone() {
+            // Read prompt file
+            let prompt_file = fs::read_to_string(prompt_file)?;
+            // Try to parse prompt file as JSON, if error then show it in JSON format
+            let prompt_file: PromptFile = match serde_json::from_str(&prompt_file) {
+                Ok(val) => val,
+                Err(e) => {
+                    let error_json = json!({"error": e.to_string()});
+                    return fail_clierror!("{error_json}");
+                },
+            };
+            prompt_file
+        }
+        // Otherwise, get default prompt file
+        else {
+            #[allow(clippy::let_and_return)]
+            let default_prompt_file = PromptFile {
+                name:               "My Prompt File".to_string(),
+                description:        "My prompt file for qsv's describegpt command.".to_string(),
+                author:             "My Name".to_string(),
+                version:            "1.0.0".to_string(),
+                tokens:             50,
+                dictionary_prompt:  "Here are the columns for each field in a data \
+                                     dictionary:\n\n- Type: the data type of this column\n- \
+                                     Label: a human-friendly label for this column\n- \
+                                     Description: a full description for this column (can be \
+                                     multiple sentences)\n\nGenerate a data dictionary as \
+                                     aforementioned (in JSON output) where each field has Name, \
+                                     Type, Label, and Description (so four columns in total) \
+                                     based on the following summary statistics and frequency data \
+                                     from a CSV file.\n\nSummary \
+                                     Statistics:\n\n{stats}\n\nFrequency:\n\n{frequency}"
+                    .to_string(),
+                description_prompt: "Generate only a description that is within 8 sentences about \
+                                     the entire dataset{json_add} based on the following summary \
+                                     statistics and frequency data derived from the CSV file it \
+                                     came from.\n\nSummary \
+                                     Statistics:\n\n{stats}\n\nFrequency:\n\n{frequency}\n\nDo \
+                                     not output the summary statistics for each field. Do not \
+                                     output the frequency for each field. Do not output data \
+                                     about each field individually, but instead output about the \
+                                     dataset as a whole in one 1-8 sentence description."
+                    .to_string(),
+                tags_prompt:        "A tag is a keyword or label that categorizes datasets with \
+                                     other, similar datasets. Using the right tags makes it \
+                                     easier for others to find and use datasets.\n\nGenerate \
+                                     single-word tags{json_add} about the dataset (lowercase only \
+                                     and remove all whitespace) based on the following summary \
+                                     statistics and frequency data from a CSV file.\n\nSummary \
+                                     Statistics:\n\n{stats}\n\nFrequency:\n\n{frequency}"
+                    .to_string(),
+                json:               true,
+                jsonl:              false,
+            };
+            default_prompt_file
         };
-        default_prompt_file
-    };
     Ok(prompt_file)
 }
 
@@ -297,18 +299,19 @@ fn get_completion(
     }
 
     // If --max-tokens is specified, use it
-    let max_tokens = if arg_is_some("--max-tokens") {
-        args.flag_max_tokens
-    }
-    // If --prompt-file is used, use the tokens field from the prompt file
-    else if args.flag_prompt_file.clone().is_some() {
-        let prompt_file = get_prompt_file(args)?;
-        prompt_file.tokens
-    }
-    // Else use the default max tokens value in USAGE
-    else {
-        args.flag_max_tokens
-    };
+    let max_tokens =
+        if arg_is_some("--max-tokens") {
+            args.flag_max_tokens
+        }
+        // If --prompt-file is used, use the tokens field from the prompt file
+        else if args.flag_prompt_file.clone().is_some() {
+            let prompt_file = get_prompt_file(args)?;
+            prompt_file.tokens
+        }
+        // Else use the default max tokens value in USAGE
+        else {
+            args.flag_max_tokens
+        };
 
     // Create request data
     let request_data = json!({

src/cmd/excel.rs

@@ -226,32 +226,34 @@ pub fn run(argv: &[&str]) -> CliResult<()> {
         .and_then(std::ffi::OsStr::to_str)
         .unwrap_or_default()
         .to_lowercase();
-    let ods_flag = match format.as_str() {
-        "xls" | "xlsx" | "xlsm" | "xlsb" => false,
-        "ods" => true,
-        _ => {
-            return fail_incorrectusage_clierror!(
-                "\"{format}\" not supported. The excel command only supports the following file \
-                 formats - xls, xlsx, xlsm, xlsb and ods."
-            );
-        },
-    };
+    let ods_flag =
+        match format.as_str() {
+            "xls" | "xlsx" | "xlsm" | "xlsb" => false,
+            "ods" => true,
+            _ => {
+                return fail_incorrectusage_clierror!(
+                    "\"{format}\" not supported. The excel command only supports the following \
+                     file formats - xls, xlsx, xlsm, xlsb and ods."
+                );
+            },
+        };
 
     let requested_range = args.flag_range.to_lowercase();
 
-    let mut workbook = match open_workbook_auto(path) {
-        Ok(workbook) => workbook,
-        Err(e) => {
-            let es = e.to_string();
-            // password protected errors come in different flavors for Excel
-            if es.starts_with("Xls error: Cfb error")
-                || es.starts_with("Xlsx error: Zip error: invalid Zip archive")
-            {
-                return fail_clierror!("{path} may be a password-protected workbook: {e}.");
-            }
-            return fail_clierror!("Cannot open workbook: {e}.");
-        },
-    };
+    let mut workbook =
+        match open_workbook_auto(path) {
+            Ok(workbook) => workbook,
+            Err(e) => {
+                let es = e.to_string();
+                // password protected errors come in different flavors for Excel
+                if es.starts_with("Xls error: Cfb error")
+                    || es.starts_with("Xlsx error: Zip error: invalid Zip archive")
+                {
+                    return fail_clierror!("{path} may be a password-protected workbook: {e}.");
+                }
+                return fail_clierror!("Cannot open workbook: {e}.");
+            },
+        };
 
     let sheet_names = workbook.sheet_names();
     if sheet_names.is_empty() {
@@ -264,10 +266,11 @@ pub fn run(argv: &[&str]) -> CliResult<()> {
     #[allow(clippy::redundant_clone)]
     let sheet_vec = sheet_names.clone();
 
-    let mut wtr = Config::new(&args.flag_output)
-        .flexible(args.flag_flexible)
-        .delimiter(args.flag_delimiter)
-        .writer()?;
+    let mut wtr =
+        Config::new(&args.flag_output)
+            .flexible(args.flag_flexible)
+            .delimiter(args.flag_delimiter)
+            .writer()?;
 
     // set Metadata Mode
     let first_letter = args.flag_metadata.chars().next().unwrap_or_default();

src/cmd/extdedup.rs

@@ -63,13 +63,14 @@ pub fn run(argv: &[&str]) -> CliResult<()> {
     // if we can detect the total memory, use 10% of it by default
     // and up to --memory-limit (capped at 50%),
     // otherwise, if we cannot detect the free memory use a default of 100 MB
-    let mem_limited_buffer = if System::IS_SUPPORTED {
-        let mut sys = System::new();
-        sys.refresh_memory();
-        (sys.total_memory() * 1000) / u8::min(args.flag_memory_limit.unwrap_or(10), 50) as u64
-    } else {
-        MEMORY_LIMITED_BUFFER
-    };
+    let mem_limited_buffer =
+        if System::IS_SUPPORTED {
+            let mut sys = System::new();
+            sys.refresh_memory();
+            (sys.total_memory() * 1000) / u8::min(args.flag_memory_limit.unwrap_or(10), 50) as u64
+        } else {
+            MEMORY_LIMITED_BUFFER
+        };
     log::info!("{mem_limited_buffer} bytes used for memory buffer for on-disk hash table...");
 
     let input_reader: Box<dyn BufRead> = match &args.arg_input {
@@ -93,10 +94,12 @@ pub fn run(argv: &[&str]) -> CliResult<()> {
             config::DEFAULT_WTR_BUFFER_CAPACITY,
             fs::File::create(output_path)?,
         )),
-        None => Box::new(io::BufWriter::with_capacity(
-            config::DEFAULT_WTR_BUFFER_CAPACITY,
-            stdout().lock(),
-        )),
+        None => {
+            Box::new(io::BufWriter::with_capacity(
+                config::DEFAULT_WTR_BUFFER_CAPACITY,
+                stdout().lock(),
+            ))
+        },
     };
 
     let mut write_dupes = false;

src/cmd/extsort.rs

@@ -55,13 +55,14 @@ pub fn run(argv: &[&str]) -> CliResult<()> {
     // if we can detect the total memory, use 10% of it by default
     // and up to --memory-limit (capped at 50%),
     // otherwise, if we cannot detect the free memory use a default of 100 MB
-    let mem_limited_buffer = if System::IS_SUPPORTED {
-        let mut sys = System::new();
-        sys.refresh_memory();
-        (sys.total_memory() * 1000) / u8::min(args.flag_memory_limit.unwrap_or(10), 50) as u64
-    } else {
-        MEMORY_LIMITED_BUFFER
-    };
+    let mem_limited_buffer =
+        if System::IS_SUPPORTED {
+            let mut sys = System::new();
+            sys.refresh_memory();
+            (sys.total_memory() * 1000) / u8::min(args.flag_memory_limit.unwrap_or(10), 50) as u64
+        } else {
+            MEMORY_LIMITED_BUFFER
+        };
     log::info!("{mem_limited_buffer} bytes used for in memory mergesort buffer...");
 
     let mut input_reader: Box<dyn BufRead> = match &args.arg_input {
@@ -93,10 +94,7 @@ pub fn run(argv: &[&str]) -> CliResult<()> {
                 fs::File::create(output_path)?,
             ))
         },
-        None => Box::new(io::BufWriter::with_capacity(
-            RW_BUFFER_CAPACITY,
-            stdout().lock(),
-        )),
+        None => Box::new(io::BufWriter::with_capacity(RW_BUFFER_CAPACITY, stdout().lock())),
     };
 
     let sorter: ExternalSorter<String, io::Error, MemoryLimitedBufferBuilder> =

src/cmd/fetch.rs

@@ -500,10 +500,7 @@ pub fn run(argv: &[&str]) -> CliResult<()> {
                 .template("{bar:37.red/white} {percent}%{msg} ({per_sec:7})")
                 .unwrap(),
         );
-        error_progress.set_message(format!(
-            " of {} max errors",
-            HumanCount(args.flag_max_errors)
-        ));
+        error_progress.set_message(format!(" of {} max errors", HumanCount(args.flag_max_errors)));
     } else {
         error_progress.set_draw_target(ProgressDrawTarget::hidden());
     }
@@ -544,11 +541,12 @@ pub fn run(argv: &[&str]) -> CliResult<()> {
             .unwrap_or_else(|| "stdin.csv".to_string());
 
         report_wtr = Config::new(&Some(report_path.clone() + FETCH_REPORT_SUFFIX)).writer()?;
-        let mut report_headers = if report == ReportKind::Detailed {
-            headers.clone()
-        } else {
-            csv::ByteRecord::new()
-        };
+        let mut report_headers =
+            if report == ReportKind::Detailed {
+                headers.clone()
+            } else {
+                csv::ByteRecord::new()
+            };
         let rptcol_prefix = if report == ReportKind::Detailed {
             FETCH_REPORT_PREFIX
         } else {
@@ -594,16 +592,18 @@ pub fn run(argv: &[&str]) -> CliResult<()> {
         },
     };
     let mut final_value = String::with_capacity(150);
-    let mut final_response = FetchResponse {
-        response:    String::new(),
-        status_code: 0_u16,
-        retries:     0_u8,
-    };
-    let empty_response = FetchResponse {
-        response:    String::new(),
-        status_code: 0_u16,
-        retries:     0_u8,
-    };
+    let mut final_response =
+        FetchResponse {
+            response:    String::new(),
+            status_code: 0_u16,
+            retries:     0_u8,
+        };
+    let empty_response =
+        FetchResponse {
+            response:    String::new(),
+            status_code: 0_u16,
+            retries:     0_u8,
+        };
     let mut running_error_count = 0_u64;
     let mut running_success_count = 0_u64;
     let mut was_cached;