Tab access

Access any of Screaming Frog’s 628 mapped export tabs, list available tabs, inspect columns, and apply GUI filters.

In addition to the typed crawl.pages() and crawl.links() views, you can access any exported tab by name using crawl.tab().

Accessing a tab

from screamingfrog import Crawl

crawl = Crawl.load("./exports")

# Access a tab by file name (extension optional)
for row in crawl.tab("response_codes_all"):
    print(row["Address"], row["Status Code"])

Tab names are normalised automatically. The following are all equivalent:

• "Page Titles" → resolves to page_titles_all.csv
• "page_titles" → resolves to page_titles_all.csv
• "page_titles_all" → used directly

Listing available tabs

Use crawl.tabs to see which tabs are available for the current backend:

print(crawl.tabs)

CSV backend — exposes any *.csv file found in the export directory.

Derby backend — exposes all tabs mapped in schemas/mapping.json (601 of 628 tabs fully mapped).

SQLite backend — supports a smaller high-value set: response codes, page titles, meta description, and internal_all.

Filtering tab rows

Filter using column names (or their snake_case equivalents):

for row in crawl.tab("internal_all").filter(status_code="404"):
    print(row["Address"])

GUI filter shortcut

Apply a Screaming Frog GUI filter by name using the gui keyword:

for row in crawl.tab("page_titles").filter(gui="Missing"):
    print(row["Address"], row["Title 1"])

You can also pass a list of GUI filter names:

for row in crawl.tab("page_titles").filter(gui_filters=["Missing", "Duplicate"]):
    print(row["Address"])

For exact GUI filter behaviour, use CSV exports. The export_profile="kitchen_sink" option exports all filter variants from the Screaming Frog UI.

Inspecting tab metadata

List GUI filter names

print(crawl.tab_filters("Page Titles"))
# ['Missing', 'Duplicate', 'Over 60 Characters', 'Below 30 Characters', ...]

Inspect columns

print(crawl.tab_columns("page_titles"))
# ['Address', 'Title 1', 'Title 1 Length', 'Title 1 Pixel Width', ...]

Describe a tab (columns + filters in one call)

print(crawl.describe_tab("page_titles"))
# {
#   'tab': 'page_titles',
#   'columns': ['Address', 'Title 1', ...],
#   'filters': ['Missing', 'Duplicate', ...]
# }

TabView methods

crawl.tab() returns a TabView. All standard view methods are available:

tab = crawl.tab("response_codes_all")

# Count rows
count = tab.filter(status_code="404").count()

# Collect as list
rows = tab.filter(status_code="404").collect()

# First row
first = tab.first()

# Convert to DataFrame
df = tab.to_pandas()
df_polars = tab.to_polars()

Backend differences

CSV

Exposes any *.csv file in the export directory. GUI filters rely on exported filter variants — use export_profile="kitchen_sink" to get all filter columns.

crawl = Crawl.load("./exports")
for row in crawl.tab("page_titles").filter(gui="Missing"):
    print(row["Address"])

Derby

Exposes all 601 mapped tabs from schemas/mapping.json. Derby natively supports tabs that require computed fields:

• Response Codes > Internal Redirect Chain
• Hreflang > Not Using Canonical

Derby-backed crawl.internal also materialises computed mapped fields like Indexability and Indexability Status.

Derby filters work against mapped expression fields and header-derived fields in both crawl.internal and crawl.tab(...).

crawl = Crawl.load("./crawl.dbseospider", dbseospider_backend="derby", csv_fallback=False)
for row in crawl.tab("hreflang_not_using_canonical"):
    print(row["Address"])

Hybrid Derby+CSV

The default for Crawl.load with Derby sources. Exports missing tabs on demand and caches them next to the crawl.

# Default — CSV fallback enabled
crawl = Crawl.load("./crawl.dbseospider")

Set csv_fallback=False to disable automatic CSV exports:

crawl = Crawl.load("./crawl.dbseospider", csv_fallback=False)

Full example: response codes

from screamingfrog import Crawl

crawl = Crawl.load("./exports")

# List available tabs
print(crawl.tabs)

# All 4xx and 5xx pages
for row in crawl.tab("response_codes_all").filter(status_code="404"):
    print(row["Address"], row["Status Code"])

# Check available filters
print(crawl.tab_filters("Response Codes"))

# Apply a GUI filter by name
for row in crawl.tab("response_codes_all").filter(gui="Internal Client Error (4xx)"):
    print(row["Address"])